My econometric estimates allow me to make several predictions about how rising temperatures will affect the agricultural labor sector. To do this, I develop a model of a firm choosing an optimal piece rate wage under some exogenous environmental condition .My model produces two interesting sets of comparative statics. First, I show that temperature’s effect on the optimal piece rate wage depends on how temperature affects labor productivity directly, and how temperature affects labor productivity’s responsiveness to the wage. Plugging my empirical estimates into this model, I find that an optimizing blueberry farm would pay its workers a higher piece rate wage on particularly cool days, ceteris paribus. Second, I show that temperature’s effect on overall farm profits has the same sign as temperature’s direct effect on labor productivity. In the case of California blueberry farms, where cool temperatures have meaningful negative effects on productivity, this suggests that the first-order effect of rising temperatures on profits is likely to be positive. However, in contexts where cool temperatures do not lower labor productivity, the opposite is likely to be true. The remainder of this paper is organized as follows: in section 1.2, I develop a simple theoretical model of workers’ optimal effort under a piece rate wage scheme. In section 1.3, I describe the institutional details of the two California blueberry farms I study in this paper. I then discuss my data and report summary statistics in section 1.4. Section 1.5 outlines my empirical strategy, and section 1.6 reports my results. I discuss my findings in section 1.7, giving particular attention to how rising temperatures are likely to affect the agricultural labor sector. Finally, in section 1.8, I conclude.

There has been relatively little theoretical work done on piece rate wage schemes in the past, partly because their structure is so straightforward,blackberries in containers and partly because they are so much less common than salaries or hourly wage schemes. Nonetheless, previous research has highlighted several important aspects of piece rate wages that are relevant to this paper. Prendergast and Brown both provide good summaries of when and where piece rates are likely to be effective. Specifically, in cases where firms can cheaply monitor productivity and ensure quality control, piece rates should correctly align workers’ incentives with those of their employer, maximizing labor productivity.10 Several papers have confirmed the prediction that, under the correct circumstances, piece rate wage schemes better incentivize labor productivity than do more traditional wage schemes. Lazear , studying an auto glass company, finds that a switch from hourly to piece rate wages boosts output per worker by an average of 44%. Shi , studying a tree-thinning company, estimates a more modest effect of 23%. Shearer , studying tree-planters in British Columbia, also finds an effect near 20%. Bandiera et al. study agricultural workers in the United Kingdom and come to a similar conclusion, noting that piece rates based on individual production eliminate cross-worker externalities found in relative incentive schemes. In a non-causal study from California, Billikopf and Norton also provide evidence that piece rate wages boost vine-pruners’ performance relative to hourly wages. Such increases in productivity under piece rates seem to come from increased worker effort, as Foster and Rosenzweig demonstrate by measuring workers’ net calorie expenditures under different pay schemes. None of the papers cited above, however, estimate how labor productivity responds to changes in a piece rate wage.Among the most well-known papers that have attempted to do so are Paarsch and Shearer and Haley . In both cases, the authors calibrate a structural model of worker effort in order to address piece rates’ endogeneity.

They find positive elasticities of effort with respect to wages, of 2.14 and 1.51 respectively, in line with theoretical predictionsOther papers have relied on natural experiments or natural field experiments to try and recover the effect of piece rate wage levels on productivity. For instance, Treble exploits a natural experiment from the 1890s in an English coal mine to derive a nearunit-elastic productivity response. In a more recent setting, Paarsch and Shearer implement a natural field experiment with tree-planters in British Columbia and estimate a productivity elasticity of 0.39. While the authors note that this estimate is “substantially smaller” than that of Paarsch and Shearer and Haley , it is unclear wether they think this result invalidates the earlier estimates.Finally, Guiteras and Jack conduct an experiment in rural Malawi to explore how variation in piece rate wages affects both quantity and quality of worker output. Despite the theoretical simplicity of a piece rate wage scheme, it is not immune to employees’ behavioral responses. Even though a firm may be able to set a different piece rate every day, doing so may foment unrest among employees if the changes are seen as arbitrary . In other situations, high piece rates may operate as efficiency wages – à la Yellen , Shapiro and Stiglitz , and Newbery and Stiglitz – especially if a firm is trying to retain high-quality workers . An additional consideration is that variable piece rate wages may lead to a less reliable supply of labor on the intensive margin. In other words, piece rate employees may work fewer or more hours depending on the day’s wage. Such behavior would be consistent with a reference-dependent preference model like that of Kőszegi and Rabin where workers have some internal reference point for how much money they intend to earn in a particular day.Finally, piece rate wages are much more common in seasonal specialty agriculture than in many other industries or settings. Tasks such as picking, pruning, or planting can be easily measured and tracked, making piece rates feasible. In these cases, productive workers can earn considerably higher incomes under a piece rate scheme than under an hourly wage scheme: Moretti and Perloff find that US agricultural workers paid by piece rate earn 26% more than their hourly counterparts. This number is slightly misleading, and certainly not causal, considering that workers select into particular work in part based on the compensation scheme. Rubin and Perloff note that piece rate workers tend to be disproportionately young or old: “[a]pparently, prime-age workers find that higher earnings in piece-rate jobs do not compensate for the difficulty of more intensive effort, more variable incomes, and possible greater injury risk or shortened farm-work career” . However,these selection issues are irrelevant if the goal is to understand how piece rates affect the productivity of workers who select into such work in the first place. Harvesting fresh blueberries is a labor intensive process. Berries grow in small bunches and ripen at differing times. This means that a single blueberry bush can be harvested multiple times each season. However, since each berry-bunch contains both ripe and unripe berries, pickers must harvest fruit carefully by hand. Mechanized blueberry harvesters exist, but they are imprecise and are used primarily for harvesting berries destined for the processing market.Berry-pickers collect fruit in small buckets fastened on the front of their bodies. Once the buckets are full,blackberry container the workers carry their harvest to a weigh-station at the end of a field row. Workers pour their berries into standardized bins which are then weighed, packed into trucks, and driven to a refrigerated packing plant. Because blueberries are delicate and perishable, they must be refrigerated quickly after being picked. When workers bring their berries to be weighed, a foreman closely watches the process to ensure quality control. If a picker’s fruit is intermingled with too many twigs, leaves, or unripe berries, the foreman will warn the picker that their quality must improve to keep their job.

The farms I study both utilize an automated system to track workers’ productivity and calculate payroll.Each picker is given a unique barcode that they wear as a badge, and each fruit tray is assigned its own barcode as well. When a picker brings their fruit to be weighed, the weigher scans both the picker’s barcode and the tray’s barcode to record the tray weight. The picker then receives a receipt of their weigh-in. The farmer likes the barcode system because it is quick, automatic, reliable, provides real-time data, and replaces a cumbersome paper-and-pencil system. Pickers like the barcode system because they are able to witness the fruit-weighing and are thus confident that the farmer is paying them honestly for the fruit they pick. At the beginning of each work day, around 6:00 or 6:30 a.m., the farmer sets the day’s piece rate wage and posts the wage in a public spot for all workers to see.Workers are paid the piece rate for each pound of berries they harvest, and the rate does not change throughout the day. The piece rate does, however, change over the course of the season . As fruit becomes more abundant on the bushes through May and June, picker productivity rises. Farmers therefore generally lower the piece rate wage throughout the season as more and more berries ripen. Anecdotally, farmers say they lower their piece rates “when there’s a lot of fruit in the field” with the goal of maintaining a relatively stable effective hourly wage for the average berry picker.If any one worker picks a small enough quantity of fruit that their effective hourly wage for the day falls below the legal minimum wage, the farmer pays them according to the hourly minimum wage. In these cases, the farmer often then gives the picker in question additional training and a warning that they may be fired if they do not quickly improve. Anecdotally, the hourly minimum wage is most likely to bind during a new employee’s first few days on the job as they develop their skills as a fruit picker. If a worker consistently falls below the minimum wage cutoff, they frequently quit on their own accord or are effectively fired and asked not to return the next day. Because blueberries are delicate and highly perishable, they are not bought and sold in a central commodity market. Instead, individual producers set short-term contracts with different marketers or buyers to provide a certain quantity of berries in particular packaging at a particular time. These contracts are set on a near-daily basis, and prices can change quickly throughout the season. While there is certainly some quality differentiation within the blueberry market, buyers and marketers view different producers as close substitutes. This means that individual producers have relatively little, if any, market power. I thus take California blueberry contract prices as an accurate reflection of a competitive market price for blueberries in the state. Blueberry prices in California are highly seasonal: prices are quite high at the beginning of the season in April, and much lower near the end of the season in June. This seasonality in price is largely explained by variation in aggregate production throughout California, and variation in the availability of blueberries from other global producers. In the early spring, the United States imports fresh blueberries at high prices from Mexico or other countries since domestic production is agronomically infeasible. By mid-to-late-June, farms in northern states such as Washington, Oregon, and Michigan begin to produce berries in large quantities, driving down the market price. California blueberry farmers therefore face a relatively short season when it is profitable to harvest and sell their fruit. While blueberry bushes continue to yield berries through June and into July, labor costs are too high relative to market prices at that time for California farmers to justify continued production. To summarize, the California blueberry season begins agronomically, but ends economically. Organic blueberries regularly command a price premium of around two dollars per pound. While the harvesting process is identical for conventional and organic berries, organic bushes produce fewer berries per bunch. Thus, pickers of organic berries spend more time finding and harvesting berries than do their conventional counterparts. Additionally, fruit quality is more variable in organic blueberries. This leads to a smaller proportion of berries ultimately reaching market. As described in the previous section, the farms I study use a digital fruit weigh-in system to track worker productivity and generate payroll data. I utilize data from these weigh-ins to conduct my analyses.

The successful diabetes induction was confirmed with blood glucose measurements from the tail vein with a glucometer , all the measurements were taken during fasting and postprandial periods during 3 days after injection. Values of fasting glucose higher than 200 mg/dl indicated a successful establishment of T2DM rat model. The BB extract was diluted in 1ml of water and administrated by oral gavage for 31 days. The fasting glucose levels in blood were tested every 2 days per week from the tail vein. Water and food consumption were quantified every day and body weight was monitored once a week. At the end of the treatment period, the rats were anesthetized via intraperitoneal with 3% pentobarbital sodium . Blood samples were collected by cardiac puncture, the blood was centrifuged for 15 min at 13,000 rpm and the plasma was recovered and stored in aliquots of 500 µl at −20◦C until use. Retroperitoneal adipose tissue was aliquoted, isolated, and washed with PBS and frozen immediately with liquid nitrogen. The frozen samples were stored at −80◦C. The stored serum samples were thawed at 4◦C. Insulin levels were quantified using the Rat Insulin ELISA kit RayBio R. Peachtree Corners, GA. The levels of total cholesterol, triglycerides, HDL-Cholesterol, and LDL-Cholesterol in the serum samples were measured with commercial kits for colorimetric assays. Tumor Necrosis Factor alpha was quantified with ELISA kit according to manufacturer protocols. RNA extraction from adipose tissue samples were carried out according to the protocol proposed in the RNeasy Lipid Tissue Mini Kit . The sequencing library was prepared by random fragmentation of the cDNA,raspbery container followed by the 5 ’and 3’ ligation adapters. Adapter-ligated fragments were amplified by PCR and visualized on agarose gels. Double stranded next generation sequencing RNAseq was commercially performed by MAcrogen on Illumina HiSeq4000 by triplicate in each group.

All RNAseq data are available at GEO database under accession number GSE215903. fter a low dose injection of STZ, rats in BB and DB groups showed significantly increased fasting blood glucose levels compared with animals from HE group, this tendence was observable during the 5 weeks treatment and at the end of the treatment as showed in Figure 1C. Furthermore, STZ administration resulted in decreased body weight in BB and DB groups , but no difference was observed on adipose tissue weight . These findings demonstrate the success of T2DM induction in Wistar rats.Two of the main characteristics of diabetic patients are the body weight decrease and the chronic increase of blood glucose levels. As exposed in Figure 1, the body weight of all the rats increased progressively, and their blood glucose levels were normal. However, the growth rate of the rats in the HE group was slower. Conversely, after STZ administration, the body weight of all rats started to decrease, and their blood glucose levels augmented significantly compared with rats in HE group. Moreover, rats in both the BB and DB groups tended to show a decrease in weight after STZ administration. The effect of BB on the fasting blood glucose level of the rats is shown in Figure 1A, from which it is obvious that the blood glucose levels of rats in the BB group decreased gradually after 1 week of treatment. At the end of treatment period, rats in BB group showed significant decreases in fasting blood glucose levels. The levels of insulin showed a down trend, even though the decreases were not significant between BB and DB groups . Further, TNF-α levels in the BB group exhibited a significant decrease when compared with DB group . With the aim to identify genomic impact of BB extract on genomic profile in adipose tissue, we performed global RNAseq. Following statistical analysis, we identified 566 significantly differentially expressed genes. A closer understanding into identified differentially expressed genes demonstrated that there are 406 among them that are protein coding genes , 33 are miRNA family genes, 39 are long non-coding genes, 3 are snRNAs and 85 are unidentified . The fold changes of these genes were observed to fluctuate from −1.15 to −13.45 for down regulated genes and from 1.14 to 22.91 for up-regulated genes.

These data suggest that the consumption of BB extract can considerably affect the expression of genes, not only protein coding but also protein non-coding genes in adipose tissue. The list of differentially expressed genes were then submitted to functional bio-informatic analyses.With the objective to inquire in the cellular functions of significantly moderated protein coding genes, we first conducted gene ontology enrichment analysis using Meta scape and Cytoscape tools. Gene ontology analysis by p-value indicated that black bean extract impacted numerous biological functional categories that include cell substrate junction assembly, phosphatidylinositol phosphate binding, fat pad development, regulation of cysteine-type endopeptidase activity, among others . Additionally, we performed a network analysis of over-represented gene ontologies where terms with a p-value <0.05, a minimum count of 3, and an enrichment factor >1.5 are collected and grouped into clusters based on their similarities . To obtain a more detailed understanding of the cellular functions that are regulated by protein coding genes significantly modulated by black bean extract, we then performed pathway enrichment analysis of up- and down-regulated differentially expressed genes using Metascape tool . The results showed that anthocyanin-rich BB extract changed the expression of genes up regulating important pathways in T2DM pathogenesis like insulin secretion, cell-substrate junction assembly, ER organization, phosphatidylserine binding, phosphatidylinositol 3-kinase binding, among others. On the other hand, BB extract also altered the expression of genes that down regulate signaling pathways involved with regulation of NIK/NF-kappaB, regulation of response to extracellular stimulus, positive regulation of cell junction assembly, negative regulation of cell population proliferation, cell adhesion molecules and negative regulation of actin filament polymerization.

Our next step was to use STRING database to explore the potential protein–protein interactions of genes identified as differentially expressed by black bean extract intake. The analysis revealed a network of interactions between identified proteins as presented in Figure 5A, as well as genes that form nodes in the network. The next step was to select the genes with the highest number of interactions with other genes and which potentially play an important role in multi-genomic effects. The number of interactions reached 12 for UBB , or 11 for MST1R and RRAS2 , or proteins like INS1 or INPPL1 with 5 or more interactions . Interestingly, pathway enrichment analyses of hub proteins conducted in GeneTrail revealed that these genes are involved in insulin signaling, mature onset of diabetes, insulin resistance, inositol phosphate metabolism or AMPK signaling pathway . Our next objective was to identify transcriptional regulators involved in the observed changes of genes, that is, transcription factors which could have their activity altered by black bean extract and affect the expression of identified significantly modulated genes. To this end, we used the database TRANSFAC and JASPAR using the Enrichr platform. Among the top ten transcription factors identified are GATA2, POU2AF1, IRF3, GATA1, NR2F2 or PPARA . It could be suggested that circulating polyphenol metabolites generated after BB extract intake could interact with transcription factors and/or cell signaling proteins regulating their activity. With the aim to test this hypothesis, we searched the capacity of major metabolites of black bean to interact and bind to these proteins using a 3D docking online server. We assessed the binding capacity of 3 major metabolites, delphinidin 3-glucoside, petunidin 3-glucoside and malvidin 3-glucoside: delphinidin 3-glucoside to GATA2 ; delphinidin 3-glucoside to POU2AF1 ; petunidin 3-glucoside to GATA2 ; malvidin 3-glucoside to GATA2 and malvidin 3-glucoside to POU2AF1 . We observed that petunidin 3-glucoside showed potential binding capacity of -6.4 kcal/mol to POU2AF1, as well as petunidin 3-glucoside and delphinidin 3-glucoside with GATA2 , and POU2AF1 , respectively. These results shows that anthocyanins in BB can interact with cell signaling proteins and produce changes in their kinase activity,growing raspberries in container this modulates the activity of downstream cell signaling proteins and consequently transcription factors.The described changes could result in the observed gene expression modifications. Our gene expression analysis also allowed us to surmise that BB can also lead to alterations in the expression of not only protein coding RNAs but also non-coding RNAs,such as miRNAs. We observed changes in expression of 33 miRNAs, including Mir615, Mir152, Mir219a1 or Mir384. Using existing database, we searched for target genes of the identified miRNAs, and nearly 500 target genes were identified. These target genes and identified miRNAs form a network of interactions as presented in the Figure 7A. To identify potential cellular functions affected by these miRNAs, we cross-examined the Mienturnet database to reveal over-represented pathways from both KEGG and Reactome databases, that is pathways associated with each of the miRNA recognized as differentially expressed by black bean extract. Among the pathways identified are PI3K- signaling pathway, Ras signaling pathway, type 1 diabetes mellitus, Insulin receptor substrate 1 related pathway, and regulation of insulin-like growth factor.

As we mentioned in the materials and methods section, we were not able to perform the RNA-lncRNAs interaction analysis in LncRRI research web server. However, in Supplementary Figure 1 we show the list of 39 lncRNAs with their fold changes that were modulated by the anthocyanin-rich BB extract.Together with identification of cellular mechanisms affected by different types of RNAs, we also aimed to identify diseases associated with identified differentially expressed genes. We used the Enrichr database OMIM disease tool that interconnects differentially expressed genes with diseases, revealing their possible role in prevention or development of these disorders. We observed that our genes differentially expressed between the BB and DB groups are significantly associated with metabolic disease, nutrition disorder, cardiovascular disease, and immune system disease . In this research we investigated the potential health benefits and the multigenomic mode of action of a rich-anthocyanin extract from BB on adipose tissue in the context of dietstreptozocin-induced type 2 diabetes mellitus. After 4 weeks dietary supplementation, we found that black bean extract improved the symptoms of T2DM and insulin resistance, controlled the levels of blood glucose, and pro-inflammatory cytokines. The use of RNAseq revealed a complex multigenomic mode action of these bio-active compounds in adipose tissue by modulating expression of protein coding, miRNA, transcription factors, and lncRNAs , regulating processes like inflammation, metabolism and cell signaling. In the last years, special interest was given to research on natural and non-toxic antidiabetic agents. Functional foods contain bio-active compounds that can exert health advantages beyond their natural properties when consumed in a regular and consistent manner through diet . Anthocyanins are an important class of polyphenols featured by their promising effects on T2DM acting on suppression of carbohydrate-metabolizing enzymes; decrease of glucose transporters expression or activity; inhibition of glycogenolysis and modifying the gut microbiota by anthocyanin breakdown products . In this research we found that an anthocyanin-rich BB extract improved glucose levels on diabetic rats. One of the effects of anthocyanins in T2DM is the suppression of postprandial glycaemia through the inhibition of α-amylase and α-glucosidase enzymes. In a study conducted by Törrönen et al., the authors evaluated the effect of berries, naturally rich in anthocyanins, on postprandial glucose levels in healthy volunteer adults. Another study showed that consumption of a rich-anthocyanin puree containing bilberries, blackcurrants, cranberries, strawberries, and 35 g of sucrose resulted, after 15 and 30 min, in lower levels of glucose when compared with the control group that only consumed sucrose . Using in silico and in vivo studies, pelargonidin-3-O-rutinose present in strawberries exhibited the potential to improve postprandial hyperglycemia by inhibiting α-glucosidase . Another mechanism of action of anthocyanins is their impact on glucose transporters. It was demonstrated that an anthocyaninrich berry-extract considerably decreased sodium-dependent and sodium-independent transporters in Caco-2 cells and also reduced the expression of genes encoding SGLT1 and GLUT2, suggesting that anthocyanins can regulate the rate of glucose absorption . The over-expression of glycogenolysis in the liver releases glucose into the bloodstream; glycogen synthase kinase is a key liver enzyme that inhibits glycogen synthase enzyme to convert glycogen to glucose. Herrera-Balandrano et al., investigated the hypoglycemic effects of malvidin from a blueberry anthocyanin extract and observed that BAE could improve insulin sensitivity by inhibiting GSK3β and glycogen synthase in the insulinindependent pathway . Moreover, a recent systematic review describes that anthocyanins can also exert their health effects by modulating the gut microbiota composition, particularly by increasing Bacteroidetes and decreasing Firmicutes. These changes will result in higher production of short chain fatty acids, lower intestinal permeability and pH, greater number of goblet cells and improvement of villi anatomy .

Certain polyphenol compounds found in fruits and vegetables can inhibit the activation of pattern recognition receptors .Cyanidin-3-glucoside and their metabolites suppress LPS-induced cytokine production in THP-1 monocytes . BB supplementation did not affect postprandial FFA and cytokine concentrations ; however, it attenuated the propensity of monocyte activation induced by elevated concentrations of FFAs in LPL-treated blood ex vivo . Supplementation with 2 and 4 servings of BBs with the breakfast meal resulted in decreased LPL-induced secretion of IL-1b and IL-6, respectively, in postprandial whole blood without affecting concentrations of FFAs released . These results suggest that the consumption of BB powder with the breakfast meal could decrease the propensity of postprandial monocyte activation in the micro-environment where blood monocytes directly interact with endothelial cells that secrete LPL. The inhibitory effect of the BB powder on LPL induced cytokine production is likely due to the inhibitory effects of polyphenols on FFA-induced activation of pattern recognition receptors including TLRs rather than potential off target effects on LPL because BB intake did not alter the concentrations of FFAs released. It was reported that intake of strawberries , orange juice , tomatoes , or blackcurrants with a high-fat meal was cardioprotective by decreasing selective inflammatory markers . Because postprandial FFA concentrations may change in time, the impact of polyphenol-rich BBs on FFA-induced postprandial inflammatory status will need to be studied in the future with blood samples taken at multiple time points, including the period when FFA concentrations rebound close to or exceed fasting concentrations. The study has several limitations. The study was not powered to look at interactions between sex and consumption of BB powder. In addition, the subjects were allowed to return to their normal daily activities after consumption of the test meal until their return for the postprandial blood draw. Because sex differences and physical activity could have affected postprandial responses,square plant pots recruitment strategies to create a balanced sex distribution and control of physical activity may need to be implemented in future studies.

In summary, consumption of an MHF breakfast decreased postprandial plasma FFA and cytokine concentrations compared with those of fasting plasma, suggesting that eating breakfast acutely attenuates the inflammatory status in postprandial blood. Plasma FFA concentrations may be an important determinant modulating monocyte activation as assessed by TLR-mediated IL-1b secretion and the expression of adhesion molecules . These results corroborate the results from our previous mechanistic studies that both palmitic acid and endogenous FFAs can directly activate TLR2 and induce the expression of proin- flammatory cytokines in primary monocytes and whole blood. A corollary of these results is that the concentration of plasma FFAs may be one of the important determinants affecting the inflammatory status in blood. Plasma FFA concentrations are generally elevated in obesity and diabetic patients. Thus, our results lead to the next translational question as to whether plasma FFA concentrations can be a target of dietary or pharmacological intervention to alleviate the increased inflammation in metabolic diseases. Supplementation with BB powder did not affect the postprandial FFA and cytokine concentrations; however, it suppressed FFA-induced cytokine production in LPL-treated blood.Unhealthy diets, e.g. Western style diets high in fats and carbohydrates, can trigger inflammatory conditions that are associated with the development of several pathologies including type 2 diabetes , nonalcoholic fatty liver disease , cardiovascular disease, cancer, and certain neuropathies. Oral intake of bio-actives to counteract inflammation is a strategy with the potential for high impact on human health, especially when these bio-actives are present in diets and dietary components, e.g. fruits and vegetables, in amounts provided by realistic intakes. Following the ingestion of any food, a physiological postprandial response occurs as a result of nutrient absorption and metabolism. However, excess consumption of lipids and/or carbohydrates leads to a series of short-term events described as postprandial dysmetabolism. These events include alterations in glucose and lipid metabolism, endotoxemia, inflammation and oxidative stress.

Importantly, postprandial dysmetabolism has been associated with a higher risk, among other pathologies, for cardiovascular disease and mortality, nonalcoholic fatty liver disease, and T2D progression. It is well documented that even a single meal high in fat and/or carbohydrates can lead to postprandial hyperglycemia, hypertriglyceridemia and/or endotoxemia. High fat diets cause metabolic endotoxemia mainly through intestinal permeabilization and/or co-transport of lipopolysaccharides with chylomicrons. Once in the circulation, endotoxins can reach different cells and organs where they promote, among other effects, the production of proinflammatory molecules, e.g. cytokines and chemokines, leading to systemic inflammation and oxidative stress, which directly affect metabolic pathways. Additionally, postprandial dyslipidemia per se contributes to altered glucose metabolism, insulin resistance and inflammation. Mechanisms involved in inflammation- and oxidative stress-associated insulin resistance include the activation of the redox sensitive kinases, i.e. c-Jun N-terminal kinases and IκB kinase , and of transcription factor NF-κB downstream of IKK. The activation of both, JNK and IKK, as well as the upregulation of the NF-κB-regulated protein tyrosine phosphatase 1B, inhibit the insulin signaling pathway resulting in tissue insulin resistance. As a counterbalance to the aforementioned proinflammatory consequences of high fat diets, the consumption of select fruits and vegetables could prevent and/or attenuate these unhealthy conditions. Evidence for the latter is complex when considering overall intakes, types of fruits and vegetables consumed, and other variables associated with population-based studies. On the other hand, a large body of evidence from experimental animal models suggests consistent benefits of select phytochemicals against the development of obesity and associated pathologies mainly triggered by consumption of high fructose and/or high fat diets. Among those phytochemicals, anthocyanidins are being actively investigated for their potential to mitigate unhealthy conditions, particularly metabolic disorders. In this regard, mounting evidence supports a potential beneficial action of AC consumption on T2D and cardiovascular disease. Furthermore, consumption of AC-rich foods has been inversely correlated with overall mortality. Chemically, AC are aglycones of anthocyanins, which are the flavonoids that provide color to grapes, dark berries , purple/black corn, and black rice, among other fruits and vegetables. According to the number and position of functional groups around the flavonoid scaffold, AC are sub-classified into cyanidins, delphinidins, malvidins, petunidins, peonidins and pelargonidins. These differences in substitutions have been shown to have a major impact on their mechanisms of action. In this regard, we recently reported that cyanidin and delphinidin were more effective than malvidin, petunidin and peonidin at mitigating inflammation, e.g. preventing tumor necrosis factor alpha -induced activation of transcription factor NF-κB in an intestinal cell model.

Understanding the mechanisms by which AC modify cellular functions is crucial to define public health recommendations in terms of diets, i.e. foods and potential supplementation. Regulation of inflammation and oxidative stress are central mechanisms involved in the capacity of cyanidin- and delphinidin-rich extracts to mitigate the deleterious gastrointestinal and metabolic effects of chronic high fat dietary consumption in mice. In terms of redox regulation, it is unfeasible that AC could act as direct antioxidants given their poor intestinal absorption that results in low tissue concentrations. However, AC and/or AC metabolites can act regulating redox homeostasis, e.g. modulating NADPH oxidase expression, oxidative stress and inflammation. Importantly, cyanidin and delphinidin have been shown to prevent high fat diet-induced endotoxemia in mice by regulating intestinal permeability through redox-dependent and independent mechanisms. This study investigated the beneficial effects of supplementation in healthy individuals with a cyanidin- and delphinidin-rich extract , firstly, on parameters of inflammation, i.e. endotoxemia, and secondly,plastic pots for planting on parameters of lipid and glucose metabolism and redox signaling. These parameters were associated with changes in redox homeostasis and signaling. Volunteers consumed a 1026-kcal high-fat meal simultaneously with either the CDRE, or a placebo in a randomly assigned, double blind, placebo-controlled crossover intervention. The CDRE mitigated HFM-induced acute endotoxemia and several parameters of postprandial dysmetabolism associated with the consumption of the HFM. The study was a randomly assigned, double blind, placebo-controlled crossover intervention comparing the effects of supplementation with CDRE or placebo. Each intervention lasted 5 h after consumption of the HFM and supplements, separated by a washout period of 7–30 d between visits. The study was conducted at the Ragle Facility at the University of California, Davis in accordance with the Declaration of Helsinki guidelines. All procedures were approved by UCD IRB administration and UCD Social & Behavioral Committee. Written informed consent was obtained from the study volunteers. Clinical interventions were conducted between December 2017 and March 2018. Recruitment and screening followed the Consolidated Standards of Reporting Trials strategy . Briefly, female and male volunteers that showed interest in the study were provided with information about the design and the procedures. If willing to commit to the study, a screening phone interview was conducted to assess their potential eligibility. Those who showed interest and met the basics of the inclusion and exclusion criteria were called for an in-person visit . Participants were asked to attend in a fasted state . The written informed consent was explained, and upon approval, anthropometric parameters were recorded and a finger-prick blood sample was obtained to determine glucose and triglycerides using a CardioCheck analyzer . Participants that met inclusion criteria were invited to be part of the clinical study and to schedule two in-person visits separated by a washout period of: i) at least 7 d to prevent significant carryover effects based on the fact that AC and their metabolites tend to disappear from circulation within 48 h of intake; ii) less than 30 d, to prevent major changes in lifestyle, especially those associated to periods of food over consumption and seasonal influences.

The day of visit 0, participants were provided with dietary restriction and guideline instructions asking them to: i) not consume phenolrich foods for 24 h before each of the study visits; ii) consume a similar low-fat dinner the evening before each meal ; and iii) complete a 3-d food record before visits 1 and 2 to assess compliance with the dietary requirements. The days of the study visits, upon arrival glucose and triglyceride levels were assessed in blood samples collected by finger prick using the CardioCheck analyzer to confirm that participants were in a fasted state and their adherence to the inclusion/exclusion criteria. Body weight and blood pressure were also determined. Participants were then asked to consume the placebo or CDRE following the randomization scheme. Powders were packaged in sealed black sachets, which were coded to blind the study personnel to the treatment. Study personnel dissolved the powder in 200 mL of water, which was provided to each participant along with the prepared HFM. The participants were asked to drink the CDRE supplement drink and then eat the HFM within 15 min. The HFM consisted of English muffin bread, sausage, egg and cheese, obtained from the US market with carotenoid-free palm oil added to bring the total dietary fat to the desired level. The total energy content of the HFM was 1026 Kcal with 70.5 g of fat , 270 mg cholesterol, 70.2 g carbohydrate, and 33 g protein with a total of 62% of the energy originated from fat, 25% from carbohydrates, and 13% from protein. Venous blood was taken at time 0 and 0.5, 1, 2, 3, and 5 h after consumption of the HFM, and collected in three separated tubes for plasma, serum and peripheral blood mononuclear cells isolation. The primary end-point of the present study was to assess whether or not the CDRE could attenuate postprandial endotoxemia induced by consumption of a HFM. Postprandial endotoxemia was evaluated using two biomarkers, plasma LPS and LBP. For LPS, there was a significant effect for time where consumption of the HFM triggered increased plasma LPS levels in both groups. The treatment effect confirmed that plasma LPS concentrations were lower in the CDRE group compared to the placebo group. The time-by-treatment interaction was not significant . The total AUC was calculated in order to evaluate the extent of exposure to LPS in each group over the 5- h postprandial time period. AUC values were 44% lower when participants received CDRE compared to when they received placebo with the HFM . Plasma LBP showed a significant treatment effect , wherein average LBP concentrations were lower in the CDRE group compared to the placebo group. Time and time-by-treatment interaction were non-significant. Consistent with plasma LPS, and the observed treatment effect, a significant effect of CDRE was observed for the LBP AUC . Thus, the CDRE treatment elicited a smaller LBP AUC response over the 5-h postprandial time period compared to the placebo .

Depending on the outcome measure, detectable effects may take weeks or months for the intervention. Only a limited number of studies exist assessing the impact of nut or berry intake on the incidence or severity of diseases or metabolic dysfunction, which require durations of months or years. Moving Forward: Precision Nutrition, Multi-omics, and Biomonitoring Precision nutrition evaluates an individual’s unique biological characteristics such as genotype and phenotype, including DNA expression, influences of the gut microbiome, and metabolic response to specific foods or dietary patterns, as well as dietary habits and external factors influencing outcomes such as social determinants of health, to determine the most effective dietary strategies to improve health and prevent disease. Understanding the sources of interindividual variability that contribute to metabolic heterogeneity and applying mathematical modeling and computational algorithms will be essential to refining dietary recommendations. Several recent publications comprehensively review research gaps and study design considerations in the field of precision nutrition and specifically concerning phenolic-rich plant foods. Precision nutrition will lead to important discoveries pertaining to interindividual responsiveness to the intake of nuts and berries. Ultimately, this information can be applied via targeted recommendations to individuals and groups for achievable and sustainable dietary intake of nuts and berries to promote optimal health. The incorporation of bio-monitoring technologies into study designs may also be used for precision nutrition. Current and emerging mobile devices can provide continuous data collection in free-living populations with minimal participant burden. The study of nuts and berries would be enhanced with the use of devices that can capture real-time physiological outputs at home that reflect normal living conditions.

Further collaborative efforts in the fields of bioengineering and artificial intelligence hold promise for advancing the understanding of benefits from nuts or berries. An emerging personal bio-monitoring technology is the Precision Health Toilet,square pot which collects and evaluates human urine and stool, which are then analyzed using artificial intelligence to determine flow rate and volume of urine, as well as fecal analysis via the Bristol Stool Scale. A second type of toilet seat, the Heart Seat, has recently been approved by the US Food and Drug Administration for home use to monitor heart rate and oxygen saturation, with future plans to add sensors that monitor systolic and diastolic blood pressure. Assessment of metabolites in the excreta seems like a feasible goal for future development, which may be useful, for example in the detection of urinary and fecal metabolites that can reflect the metabolism of ellagic acid to urolithins and of -epicatechin to γ-valerolactone. A third example is an ingestible capsule containing a biological photosensor that can detect gut inflammation. Bioluminescence can be monitored from bacteria that have been engineered to illuminate when they come into contact with a molecule for which they have been coded, such as urolithins from berries or lipid-sensitive metabolites from nuts. Finally, another type of ingestible capsule has recently been detailed that collects samples from multiple regions of the human intestinal tract during normal digestion. This device has been used to explore the role of the gut microbiome in physiology and disease, with novel findings that intestinal and stool metabolomes differ dramatically. The ability of nut or berry intake to alter such metabolomes, and their association with changes in physiological function and health outcomes, would be an interesting area for future research. Although these technologies are still in their infancy, they have promise to further precision nutrition research efforts on nuts and berries. Research addressing the issue of “responders” compared with “nonresponders” is important in understanding the metabolic discrepancies in many studies on nuts and berries. For example, platelet aggregation phenotypes can vary significantly by individual responsiveness to oxylipins, bio-active lipid mediators derived from polyunsaturated fatty acids present in nuts as well as in extra virgin olive oil.

Variations in circulating metabolites and microvascular function following the intake of freeze-dried strawberry powder have been reported. Those individuals producing increased nitrate and nitrite levels showed favorable changes in function whereas those showing no change in nitrate or nitrite levels did not. Another example is illustrated by a recent letter in response to a systematic review of almond intake and inflammatory biomarkers. The letter notes that while the review included amounts of almonds ranging from 10 to 113 g/d, favorable responses only occurred at intake of <60 g/d. Further, the authors note that although the review reports beneficial effects of almond intake on reduction in C-reactive protein and interleukin-6, subgroup analyses showed that the effects on these 2 outcomes were not significant among those with obesity or who were rated as unhealthy prior to the intervention. Characterizing participants according to precision nutrition, including the use of genetic phenotyping to identify target genes that may result in “responders” and “nonresponders” prior to enrollment may be helpful for clinical trials but does not reflect responses in a free-living population. Furthermore, in addition to physiological variations, sociobehavioral differences among individuals that may modulate responses to berries and nuts must also considered. Nonetheless, innovative precision nutrition models that can identify inter individual differences would be useful in defining mechanisms of action and potentially who would benefit the most from regular nut or berry consumption. Plasma and serum concentrations are useful to identify the bio-availability and bioefficacy of key nutrients and phytochemicals found in nuts and berries. Some compounds, such as small molecular weight polyphenols, are first absorbed in their native state in the small intestine. Other polyphenols can be biotransformed via the host microbiota to a second set of compounds that are subsequently absorbed and confer additional bio-activity beyond that obtained from the parent molecules. Monitoring both host and microbial metabolites in the blood and urine, and those that may accumulate in tissues of interest such as the liver and gastrointestinal epithelium, among other tissues, would be useful in understanding the dynamics of nut and berry bio-activity and specific association with site of actions.

Broader application of orthogonal approaches that combine untargeted with targeted metabolomic platforms and combined with the use of advanced informatics will support new understanding about the absorption, distribution, metabolism, and excretion of compounds found in nuts and berries. For example, the UC Davis West Coast Metabolomics Center conducts both targeted and untargeted assays that assess plasma microbial metabolites using a bio-genic amine panel that identifies and quantifies acylcarnitines, trimethylamine N-oxide, cholines, betaines, nucleotides and nucleosides, methylated and acetylated amines, di- and oligo-peptides, and a number of microbially modified food-derived metabolites. Some inter individual differences in response to nut or berry intake have been attributed to the composition of the gut microbiome. For example, ellagitannins are polyphenolic compounds present in strawberries, raspberries, and walnuts that are metabolized by gut bacteria into an array of urolithins . The production of urolithins relies on the capacity of specific microbes, Gordonibacter pamelaeae and Gordonibacterurolithinfaciens. Urolithins may decrease symptoms of chronic metabolic diseases, including inflammation and dyslipidemia. Following a single intake of red raspberries, individuals with prediabetes and insulin resistance had lower concentrations of circulating urolithins compared to levels found in those who were metabolically healthy, a result related to gut microbiome composition. In the same population, consuming red raspberries for 4 wk improved hepatic insulin resistance and total and LDL cholesterol in the prediabetes group, and the effects were related to decreased R. gnavus and increased E. eligins. Overall, including a practical amount of red raspberry in the diet regularly is a low-calorie dietary strategy that improves gut microbiota composition and function in individuals with prediabetes and insulin resistance resulting in improvements in metabolic health. With a sustained emphasis on the role of gut microbiota in nutrition research, advances in our understanding of food-gut dynamics will provide new insights about the role of nuts and berries in human health and performance. Although research on a specific nut or berry provides insight into bio-activity and potential mechanisms of action,square plastic planter such focus also creates the potential for fragmentation because the search for overall dietary patterns is not addressed. The composition of fruits and nuts differ at the molecular level, and a broader view assessing similarities in chemistry and health benefits is critical for translational research as well as for messaging purposes. For example, blueberries, strawberries, pomegranate, walnuts, and grapes all have reported benefits for cardiovascular health, driven largely by the presence of similar polyphenols, which are present at varying quantities in each of these foods. Although health professionals and consumers often hear messaging on a single berry or nut, the potential benefits of increasing consumption of the broader category may be obscured or lost. This challenges the ability to maintain consistent messaging and align better with translatable dietary guidance. Future interventions that combine nuts and berries with one or more other foods within a food matrix at dietary achievable doses and in more diverse populations are warranted. To date, multi-omics technologies have provided valuable insights into exposure-disease relationships.

Coupled with artificial intelligence, predictive modeling and continuous, personalized monitoring, these data-intensive outcomes can provide further insights about the health benefits associated with regular intake of nuts or berries. Use of highly personalized data collection devices will require secure data repositories. One of the challenges of similar foods being studied in differing formats and by various research groups is the utility of the data as a combined set. Differences in test materials and experimental designs make integration of data difficult. The proper curation of combined data, whether physiologic, metabolomic, or genomic, is critical to ensure that combined datasets provide synergy, statistical power, and enhanced usefulness.The cardiometabolic benefits from regular consumption of nuts or berries are widely reported and include improved vascular function, reduction of cardiovascular disease risk factors, improved insulin sensitivity, and reduced risk of type 2 diabetes mellitus. Antioxidant and anti-inflammatory capacity and activity have also been noted. Metabolic outcomes may be context-specific and related to the physiologic state of the individual and host microbiome composition, among other factors. Examples include findings of ellagitannin and ellagic acid rich foods resulting in differential responses in healthy individuals compared to those with prediabetes, who are dependent on gut microbial-derived metabolite profiles. Many factors contribute to inter individual variability in response to diet that can extend to context-specific aspects influencing the magnitude of health benefits and reinforces the importance for further research aimed at advancing discoveries in precision nutrition. Additional health outcomes related to nut or berry intake are outlined below.Adding nuts or berries to the daily diet may be advantageous for weight management for several physiological reasons. One is that these foods produce feelings of satiety, helping to reduce the desire to consume calorie-rich snacks that are low in vitamins, minerals, and fibers, ultimately improving body composition over time. A second possibility is due to urolithins, secondary metabolites produced from ellagitannins in nuts and berries. Urolithins increase the activation of the adenosine monophosphate-activated protein kinase pathway, resulting in anti-obesogenic properties in vitro and in animal models. AMPK increases fatty acid oxidation and decreases triglyceride accumulation. Phosphorylation of AMPK may also decrease cholesterol synthesis and lipogenesis by down regulating 3-hydroxy-3-methylglutaryl coenzyme A reductase activity and sterol regulatory-element binding protein expression. In clinical studies exploring the relationship between food and body composition, the incorporation of nuts and berries into the diet was associated with weight loss or maintenance.Regular consumption of nuts or berries has been reported to support brain health and cognitive function, motor control, mood, and executive function at physiologically relevant intakes. Middle-aged and older adults experienced improvements in balance, gait, and memory, and children experienced higher executive function and positive affect after acute and regular intake of both strawberries and blueberries. These beneficial effects may be the result of direct effects on brain signaling or indirect effects through oxidant defense and anti-inflammatory properties of polyphenols and other bio-active compounds in nuts and berry foods. The gut-brain axis is an emerging area of research. Most studies are preclinical in nature using animal models but are suggestive of a significant role of gut microbial-derived ellagitannin metabolites on brain health and neuroprotection.Regular intake of almonds, a good source of fatty acids and polyphenols, has been associated with a significant decrease in facial hyperpigmentation and wrinkle severity.

Numerous studies on blueberry treatment of murine cell lines use TLR4-activated models, through the addition of the bacterial cell wall component LPS at doses varying from 0.01 to 10 μg/mL . This produces a strong inflammatory response through, but not limited to, the expression of IL-6, TNF-α, or NO . The capacity of blueberry components to reduce proinflammatory marker gene expression and secretion inLPS-induced murine cell models has been shown in several studies, although the anti-inflammatory effect seems to be carried out by an array of compounds rather than an individual blueberry phenolic fraction. Diverse blueberry products, including blueberry pomace, whole blueberry extracts, polyphenol-rich extracts, or specific phenolic fractions lowered the production of cytokines by the cells in a dose-dependent manner. Further details on the treatments and doses used in the studies are reported in Table 1. For instance, blueberry phytochemicals reduced the gene expression and secretion of proinflammatory cytokines induced by LPS, particularly IL-6 , IL-1β , and TNF-αin RAW 264.7 cells and BMDMs compared with the LPS-induced control. However, it is not clear which fraction or specific phenolic compound exerts a more potent effect, especially since their activities seem to be cytokine specific. For example, Esposito et al. reported a better ability of a proanthocyanidin fraction to reduce IL-1β compared with the polyphenol extract, anthocyanin, or phenolic acid fractions. However, IL-6 gene expression was not suppressed by that same proanthocyandin fraction, and monocyte chemoattractant protein -1 expression , a chemokine that regulates monocyte infiltration ,drainage planter pot was inhibited by the blueberry anthocyanins but not by the other phenolic fractions. Although the large variation between the blueberry treatment doses used across different reports hinders direct comparisons between the studies, most have shown a dose-dependent regulation of cytokines .

Cheng et al. , however, reported 40–60% inhibition of IL-1β gene expression with ≤200 μg/mL blueberry extract, but no effect when the treatment dose was increased to 400 μg/mL . This observation was tentatively explained by the increased phagocytic activity of the macrophages in the presence of a high polyphenol concentration. iNOS is an enzyme responsible for the synthesis of NO, a mediator secreted by neutrophils and macrophages to induce vasodilation, mediate the immune response, or regulate apoptosis . After stimulation of RAW 264.7 cells by LPS, blueberry extracts inhibited iNOS gene expression and NO production , with extracts from anthocyanin-rich cultivars and blueberry proanthocyanidin fractions being particularly effective . COX-2 also plays a central role in the induction of inflammation. It is involved in the formation of prostaglandins, including prostaglandin E2 responsible for the induction of pain . Blueberry extracts have consistently reduced COX-2 gene expression in RAW 264.7 cells , although Mueller et al. and Grace et al. did not report a significant reduction of iNOS and COX-2 gene expression by whole blueberry or polyphenol-rich extracts. Although most studies have focused on blueberry polyphenols, Gu et al. reported the anti-inflammatory effect of the volatile extracts of several berries compared with their phenolic counterpart. Volatile and phenolic blueberry extracts showedsimilar inhibitory effects on inflammatory cytokines, NO, and COX-2 production, even though the volatile fraction was tested at a lower concentration than the phenolic fraction. This provides initial evidence that the volatile fraction of blueberries also contains molecules with anti-inflammation properties, but this remains to be validated. The anti-inflammatory activities of blueberry phytochemicals have also been demonstrated in cell lines derived from humans , including the U-937 and THP-1 monocytelike cells, that can be differentiated into macrophages after stimulation with phorbol-12-myristate-13-acetate , and human primary peripheral blood mononuclear cells . In the context of blueberry studies, a variety of compounds have been used to induce inflammation, including Fusobacterium nucleatum bacteria , LPS , or cytokines .

Blueberry extracts exerted an inhibitory effect toward cytokine secretion and matrix metalloproteinase -8 and 9 production , in cells triggered by bacteria or LPS. Blueberry extracts decreased TNF-α gene expression induced by LPS in THP-1 monocytes and U937 macrophages , but on the contrary, increased its expression in THP- 1 differentiated macrophages . The regulatory effect reported in most studies was associated with a decrease in NF-κB translocation in THP-1 cells . In PBMCs and THP-1 cells alternatively induced with either IFN-γ or TNF- α, the effects of a blueberry treatment were less robust . Cytokine secretion and adhesion molecule gene expression were inhibited by a blueberry extract in IFN- γ -induced PBMCs, but the same blueberry extract further increased the proinflammatory marker secretion when the cells were induced with TNF-α . These observations were tentatively explained by looking at the pathways activated by the different cytokines : the signal transducers and activators of transcription pathway activation was inhibited by coincubation of IFN-γ with the berry treatment, but NF-κB was enhanced by the addition of TNF-α combined with a blueberry extract . A follow-up study demonstrated that the IFN-γ receptor 2, responsible for transducing the signal conveyed by the proinflammatory cytokines, was inhibited by the blueberry anthocyanins . These observations on cell models induced with non-LPS ligands suggest that the immunomodulatory effects of blueberry compounds are context and pathway specific. In summary, blueberry phenolic and polyphenolic extracts have been shown to dampen inflammation in RAW 264.7, U-937, BMDMs, and PBMCs challenged with inflammation inducers, through the reduction of proinflammatory cytokine gene expression and secretion, and inhibition of NF-κB translocation to the nucleus. No specific fraction emerges as being more potent, suggesting a general effect of multiple phytomolecules rather than a single compound. More studies are warranted to better define molecular targets of blueberry-derived molecules and to assess the involvement of TLR-dependent and -independent pathways.ROS and free radicals are natural by-products of enzymatic reactions produced during metabolism .

When controlled, ROS production is used for signaling in metabolic processes . Environmental factors, lifestyle, and pathologies contribute to an unbalanced state, where ROS production overwhelms the defense capacity of the cells and induces oxidative stress . This state leads to protein and nucleic oxidation, and lipid peroxidation, which can impair enzymatic processes, induce breakage of DNA strands, and may lead to cell death . Endogenous antioxidant defense mechanisms exist in the body to limit the production and deleterious effects of ROS. Superoxide dismutase , found in the membrane or cytosolic fractions of cells, converts superoxide radicals to H2O2 and O2 . Glutathione peroxidase , via the oxidation of glutathione S-transferase, reduces lipid peroxide and converts H2O2 to H2O . Enzymes, including DNA glycosylases, repair damaged DNA . Oxidation and inflammation are intricately related, as cytokines and chemokines secreted by inflammatory cells can trigger ROS production. In turn, ROS activate proinflammatory pathways, including NF- κB, and sustain the cycle of oxidative and inflammatory stress . These conditions favor the development of chronic pathologies such as cancer , cardiovascular , inflammatory , and neurodegenerative diseases . The effect of blueberry phytochemicals on oxidative stress has been evaluated using several cell models, including neurons , fibroblasts , hepatocytes , enterocytes , and epithelial cells . Despite the diversity in models used, studies overlap in terms of the endpoints measured, which focus on evaluation of the modulation in ROS production and lipid peroxidation, increases in antioxidant enzyme activities, and protection of DNA against oxidative damage . The induction of oxidative stress in a variety of cells was attenuated by treatment with blueberry extracts, principally through the decreased formation of ROS , but also increased scavenging activity , and/or reduction of lipid peroxidation . This effect, however,plant pot with drainage was only partly explained by the regulatory effect of the blueberry compounds on antioxidant enzymes, which were upregulated in neuronal cells treated with blueberry juice and Caco-2 cells incubated with a polyphenol-rich blueberry extract . Glutathione concentrations, however, remained unchanged in Caco-2 cells treated with an anthocyanin fraction . In addition, a blueberry pomace extract tested on Chinese hamster ovary epithelial cells and a human colon cancer cell line failed to stimulate the transcription of detoxification enzymes such as heme oxygenase and NADPH quinone oxidoreductase- 1 , both involved in the antioxidant/oxidant balance . In contrast with those observations made on blueberry parent compounds, phloroglucinol aldehyde increased thetranscription activity of nuclear factor erythroid 2-related factor 2 , which when induced by oxidative stress stimulates the transcription of HO-1 and NQO-1 .A consequence of oxidation is DNA damage and potentially increases in cell death. Blueberry extracts demonstrated a protection against DNA damage induced by hydroxide peroxide and tert-butylhydroperoxide , although in Caco-2 cells, only the blueberry phenolcarbonic acid fraction reduced DNA damage compared with whole blueberry extract, anthocyanin, and polymeric fractions . Protective effects in terms of DNA damage and cell death were attributed to blueberry anthocyanin fractions in liver cells and pulmonary epithelial cells exposed to light or ionizing radiation, through modulation of apoptosis and cell cycle regulatory gene expressions . However, no improvement of cell cycle perturbation induced by 2,2-azobisdihydrochloride was reported in intestinal epithelial cells IPEC-1 treated with blueberry anthocyanins . To summarize, blueberry extracts and phenolic fractions demonstrated protective effects against oxidative stress, which were mainly explained through reduction of ROS production and protection against DNA damage induced during oxidation. Additional studies comparing cell models and/or blueberry fractions using similar experimental parameters are necessary to demonstrate the effects of the treatment on antioxidant enzymes, and fully understand the antioxidant contribution of blueberry phytochemicals versus their metabolic by-products.

There is also a need to evaluate the potential effects of blueberry volatiles in this regard.Atherosclerosis, a chronic inflammatory disease of the arterial wall , is characterized by the buildup of plaques in arteries and is the most frequent underlying condition for the development of cardiovascular diseases . Human umbilical vein endothelial cells and human microvascular vein endothelial cells provide a model to study normal as well as oxidation and inflammation-related dysfunctions. Studies on the effect of blueberry compounds in endothelial cell models are detailed in Table 3. Risk factors including smoking, aging, hypercholesterolemia, and hyperglycemia promote the retention of lipids, particularly LDL prone to oxidation in the vascular wall, causing the activation of inflammatory processes . The treatment of endothelial cells exposed to oxidative stress triggers with blueberry anthocyanins demonstrated protective effects toward ROS secretion and lipid peroxidation . A similar observation was reported with cells treated with blueberry exosome-like nanoparticles ,an extracellular messenger vesicle presents in plants that contains proteins, lipids, mRNA, and microRNA . In addition to reducing ROS production, blueberry ELN also regulated gene expression involved in endothelial activation and leukocyte recruitment [MAPK1 and intercellular adhesion molecule ] and inflammation . The antioxidant effect of blueberry extract on endothelial cells is likely due to the activity of several phytochemicals, but the extent to which other compounds contribute to the effect remains unclear, particularly due to the low number of studies focusing on nonphenolic compounds. The secretion of chemokines and adhesion molecules by the endothelium is primarily regulated by TNF-α and Creactive protein , and leads to monocyte recruitment . After infiltration, monocytes differentiate into macrophages and phagocytose LDL . Macrophages that accumulate lipids eventually turn into foam cells, becoming surrounded by smooth-muscle cells and a collagen matrix, ultimately resulting in plaque formation . Blueberry anthocyanins reduced the adhesion of THP-1 monocytes to HUVEC endothelial cells with a better efficacy than the phenolic acid fraction derived from the same extract . The action of blueberry anthocyanins was further investigated and the individual compounds malvidin and cyanidin 3-glucoside, protocatechuic, and gallic acid reduced THP-1 adhesion . Blueberry extracts also decreased platelet- and endothelial-derived microvesicles through the inhibition of P2X7 transcription and Akt phosphorylation, both contributing to the release of extracellular vesicles associated with monocyte interaction with endothelial cells . Su et al. observed that blueberry extracts led to down regulation of noncoding miR-21, miR-146a, and miR125b, miRs typically increased in macrophages involved in plaque formation . In cardiovascular disease, endothelial cell migration and angiogenesis are reduced, leading to structural and functional alterations of the endothelium . Akt is a major signaling pathway in angiogenesis, regulating cell survival, cell cycle, and migration . Treatment with blueberry polyphenols increased angiogenesis in endothelial cells through the upregulation of the Akt pathway . However, abnormal angiogenesis promoted by vascular endothelial growth factor was counterbalanced by blueberry extract treatment through the inhibition of ERK and Akt phosphorylation . In addition, blueberry polyphenol extract did not modulate polyphospholipase C expression and phosphorylation, involved in angiogenesis, in HUVEC cells following induction with VEGF or LPS .

As the US/ Brazilian admixture weight is much less than the European admixture weight, this was likely due to a migration event from the Americas into Irish populations. The other out-of-US admixture event, from the Western United States to South Korea , was seen when m ¼ 6, 8, and 10. F3 statistics all have significantly negative values, and the F4 statistics and are significantly positive, supporting a Western US/South Korea admixture. However, using nine migration edges Treemix reported the reverse direction; as F3 and F4 statistics cannot easily infer directionality, more heavily sampling of the Asian populations or alternate methods may be needed to determine whether flow is occurring in both directions.To determine if invasive populations have experienced loss in genetic diversity, we used the software ANGSD to estimate average pairwise nucleotide diversity in 20 kb increments across the 20 largest contigs of genome for each population. Invasive populations can sometimes exhibit reduced levels of diversity early on in their history due to a founder effect , whereas ancestral populations tend to have the greatest amount of diversity as they have had many generations to accumulate mutations. A Welch one-way test found a significant difference in mean pairwise nucleotide diversity between clusters. We then used pairwise Games-Howell tests and found each cluster to be significantly different , except for the Eastern United States, Brazil, and Italy when compared with each other. As Asia is the ancestral home of D. suzukii, it is no surprise that South Korean wild populations exhibit the highest diversity levels . Similarly, the laboratory populations from Japan and Hawaii have half as much pairwise diversity as the wild South Korean population,drainage pot consistent with a small laboratory population size. The invasive populations display an intermediate level between these extremes. To assess whether invasive populations may have experienced a bottleneck or population shrinkage, we also estimated Tajima’s D in the same genomic intervals.

Extremely positive values can indicate a loss of rare alleles, which can occur during a population shrinkage, whereas extremely negative values can indicate a recent bottleneck followed by rapid expansion . A Welch one-way test again indicated significant differences in mean Tajima’s D between clusters , and pairwise Games-Howell tests found all clusters to betatistically different except for Western US against Brazilian flies. Strains from Hawaii and Japan both had high genome-wide levels of Tajima’s D, indicative of a loss of rare alleles that can occur during a population shrinkage . The remaining populations had neutral values of D, except for Ireland’s relatively high value. Based on this, we conclude there are no strong signals for a recent bottleneck, although the high genome-wide D value for Ireland suggests a recent population shrinkage. As our Irish samples were collected in 2016 only 1 year after its discovery in Ireland, we could be observing the founder’s effect in action .Based on population allele frequencies, we have shown that D. suzukii exhibit population structure based on region and invasion history. In the New World populations, we find that Eastern and Western US samples appear to be distinct populations. While this could be the result of continuous population variation from East through Central to the West coast, it is more likely the case that the two populations experience little gene flow due to strong geographical barriers such as the Sierra Nevada or Rocky Mountain ranges, and the fact that key target fruit crops such as cherries,raspberries, blueberries, and strawberries are primarily grown in states that we sampled . Any genetic exchange between these regions would likely be the result of human activity, such as could be the case with samples collected from Alma Research Farm, Bacon County, Georgia clustering with the Western US populations. As other nearby collections failed to share this signal, the Alma research population could represent a recent and isolated migration event.

Otherwise, we see little evidence of migration events or admixture between the Eastern and Western United States, which is somewhat surprising as the country’s supply of fresh blueberries, cherries, and caneberries are concentrated in a few states and shipped across the country . However, recent changes to cultural management such as more frequent harvesting and post-harvest chilling may be responsible for disrupting the D. suzukii lifecycle and limiting cross-country transport . While we were able to detect population structure between eastern and western locations in the United States, we were surprised to discover a lack of structure on a finer scale, either based on latitude or simple geographical distance, given the large number of loci analyzed. In a similar study using 3484 SNPs in 246 Hawaiian D. suzukii samples, researchers were able to identify three distinct populations roughly seperated by islands . The fact that D. suzukii has been present in Hawaii since 1980, in addition to the isolation by island, are likely the strongest factors in providing enough genetic drift to create such differentiation. As the continental US D. suzukii have only been present since 2008, it may be too early for finer structure to have developed. Alternatively, continual dispersion and transportation of D. suzukii around the United States may be hindering the development of more local structure. Several studies have reported a low probability of D. suzukii surviving when exposed to freezing temperatures, based on cold survival assays of wild-caught specimens , suggesting that flies collected in cold-winter regions such as Washington, Michigan, Maine, and New York could be annual migrants to the area from nearby warmer locations. The lack of north-south population structure supports the hypothesis that flies are regularly re-migrating into colder climates after the harsh winters have ended. Alternatively, flies could be tolerating winters by surviving inside human structures , or by having evolved resistance to freezing temperatures . Studies using D. suzukii collected from different locations have reported different levels of rapid cold-hardening response, suggesting that there could be regional selection present .

If populations in northern regions undergo strong seasonal fluctuations in allele frequencies, such as has been demonstrated in wild D. melanogaster populations collected in Pennsylvania , by only sampling sites in the summer we may be missing signals of population differentiation between the north and south. Likely, some combination of these factors is responsible for the success of D. suzukii in these regions, and further studies will be needed to identify the causes. North-south clines in specific traits such as diapause and circadian rhythms have been previously identified in drosophilids and could be at play here as well . Further analyses using methods such as those recently used to detect SNPs correlated with invasive success could be applied to this dataset to find signals of selection. Fst values between populations from the United States, Brazil, and South Korea were low and agree with previously published Fst estimates based on Pool-Seq data; Olazcuaga et al. 2020 observed that Fst between US, European, Asian, and Brazilian populations varied between 8.86 and 9.02%. However, we were surprised to see that our Italian and Irish samples had much higher values of Fst compared with the other populations, and even to each other. This discrepancy could be due to the small sample sizes we had from Europe; in this scenario, pooling larger number of samples can improve power to estimate Fst, and we instead rely on comparing the relative Fst values between populations for our analysis. High Fst values between our Japanese and Hawaiian populations were expected, however, as these have likely experienced strong drift during their time in captivity. In general, we find that our treemix and migration results largely coincide with the proposed invasion pathway inferred from microsatellites , as well as a recent preprint that re-analyzed invasion pathways with pooled sequencing data . We see that European and US/Brazilian populations form two distinct clades,large pot with drainage emphasizing these regions were invaded by two independent migrations from Asia. Hawaii is the first population to diverge in the Americas, followed by the Western United States, then the Eastern United States and Brazil. Additionally, in the Western United States, we detected a strong signal of admixture from Hawaii, which could be due to multiple or ongoing migration events. We also detected signals of admixture from the Eastern United States/Brazil to Ireland, which matches the predicted initial invasion pathway and suggests multiple migration events. Unique to our analysis, we recover support for admixture of Western US samples in Asia, suggesting that migrations could be ongoing in both directions. Invasive species transport is strongly associated with international trade of live plants and plant products , and indeed agricultural export data supports the possibility of this migration as Japan receives almost 15% of all US blueberry exports, and Oregon recently became the first state to begin shipping blueberries to South Korea in 2012 . It should be noted that while Treemix infers direction of migration, the model can occasionally infer the incorrect direction, particularly when populations are closely related without an available out group .

In conjunction with evidence of this widespread ongoing migration, we observed nucleotide diversity levels of all invasive populations to be only moderately below that of the wild South Korean population, a trend also observed in Fraimout et al. . Typically, recent invasion events are characterized by reduced diversity relative to the ancestral populations due to founder or bottleneck effects . However, successive invasion events can provide relief from any initial bottlenecks by providing increased genetic diversity. This has been observed to occur in multiple animal studies and could lead to increased ability to adapt and evolve to new climates. Correspondingly, in our analysis, we did not find populations with broadly low values of Tajima’s D, suggesting little bottleneck effect. As measures to reduce impacts of invasive species are often hindered by repeated migrations , it will be important to enforce that fruits being exported and imported internationally are free of live D. suzukii as required by the US Department of Agriculture, even though this species is already internationally established.We anticipate that the genomic data provided here will prove useful in many fields of biology beyond the scope of this study. Knowledge of genetic variation and alternate alleles present within a species can be informative for the design of probes and micro RNAs , such as for the purpose of creating gene drives to control invasive species. Gene drive mechanisms to eliminate D. suzukii have been experimentally tested on multiple lines to ensure the miRNAs are broadly effective , but a large dataset of wild population sequencing allow researchers to more confidently select target sites that are nonvariable and thus susceptible to Cas9 targeting . Drury et al., demonstrated that minor natural polymorphisms in target sites reduce gene drive effectiveness in flour beetles, and tools have been developed to help researchers design gRNAs accounting for population variation . Similarly, with the recent development of a CRISPR-Cas9 editing and RNAi knockdown protocols for D. suzukii , prior knowledge of allelic variation will allow researchers to design targeting oligonucleotides more precisely to avoid loci with variability. Most recently, our dataset has been used to study sensory receptor evolution in D. suzukii, giving insights into its evolution toward becoming a major agricultural pest . Other future uses of this trove of genomic data could involve insecticide resistance studies or the development of diagnostic assays for rapid detection in the field.Since domestication efforts began in the early 1900s , higbush blueberry has rapidly become a high-value fruit crop worldwide. Higbush blueberry, compared to hundreds of closely related blueberry species in the Ericaceae, is widely cultivated due to its adaptation to temperate climates, excellent fruit quality, yield, and composition of phytonutrients. As a result for the demand for fresh blueberries as a ”super fruit”, high bush blueberry production has increased 600% during the past three decades and steadily grown to a multi-billion dollar industry. In addition to its short domestication history, high bush blueberry is unique in being one of only three major commercially valuable fruit crops, accompanied by cranberry and the garden strawberry, with wild progenitor species native to North America. Blueberries have a single epidermal layer that expresses a rich profile of anthocyanins during ripening that, in combination with epicuticular wax, generates its characteristic ”powdery blue” color.

From the perspective of crop pollination services provision, this effect is important since the pollination service can decrease not only due to lack of neighboring natural areas but also nearby flowering crop area. The vast nutritional benefits of a diet containing a wide variety of plants have long been known. However, benefits distinct from simple nutrition, such as phytochemicals have recently become clear. Diets rich in a plethora of phytochemicals can promote a healthy and diverse gut microbiota, reduce intestinal and systemic inflammation, and decrease the risk of colorectal cancer and type 2 diabetes mellitus. Some of these benefits can be observed around the world. Many parts of India have historically low colon cancer incidence rates. The Indian subcontinent has been continuously settled for millennia. Ancient cities in the Indus valley have been dated to the third and fourth millennia BC and some sites are even older. Archaeological evidence of grain cultivation, including several varieties of barley and wheat, has been found in excavations dated to the sixth millennium BC. Wheat is still a staple crop in northern India, and many other grains, including barley, were commonly cultivated and eaten until the 1950s, when wheat and white rice became dominant. Although the country has many diverse cultures, some customs remain common and conventional throughout the nation. One such tradition is the form of main meals where a large round platter, the thali, holds rice or bread and several smaller bowls, or katori, which hold a separate condiment or curry to be eaten with the rice or bread at the diner’s preference. Typical dishes include, but are not limited to, dal , yogurt ,vertical indoor hydroponic system and assorted spices and vegetables. The development of agriculture early in its history has allowed India to develop rich traditions around food.

These traditions have been deeply influenced by Ayurveda, the ancient Indian system of medicine. In Ayurvedic practice, food is a source of nourishment and medicine, used to both prevent and treat illness. Maintaining a proper balance of Ayurvedic elements through diet is considered an effective way to live a healthy lifestyle. According to the Ayurvedic principles, each meal should contain a balance of the six major flavors. This calls for the many small portions of a thali meal which also easily incorporate variety. A variety of flavors in a meal often indicates the presence of many classes of bio-active compounds . Although these substances may not be macronutrients, vitamins, or minerals, they still impact human health. Polyphenols are perhaps the largest class of bio-active compounds, containing sub-classes such as flavonoids, isoflavones, stilbenes, lignans, and tannins. As a flavonoid subgroup, anthocyanins are included in this class. Anthocyanins are of interest in the food industry as nontoxic and water-soluble pigments, as most are colored red, purple, or blue, and many display antioxidant and anti-inflammatory activity. A class of phytochemicals called polyphenols is also found in virtually all plant foods, though their quantity may be reduced by preparation methods. Rich sources of anthocyanins include deeply colored fruits and vegetables, such as blueberries, eggplants, and certain carrot and potato cultivars. Given that many phytochemicals exert anti-inflammatory activity via promoting gut bacterial diversity, there is a growing interest in a food-based approach to countering the growing epidemic of inflammation-promoted chronic diseases such as colon cancer.We have learned that no discussion of diet is complete without consideration of the intestinal microbiota. Trillions of bacteria, distributed throughout the gastrointestinal tract from mouth to anus, facilitate digestion and intestinal homeostasis. Structural factors greatly impact the overall makeup of each community.

For example, low pH prohibits many pathogenic bacteria from colonizing the stomach and the upper small intestine. The depths of the large intestine, on the other hand, is an ideal habitat for many anaerobes. The gut microbiota is a dynamic community, composed of living organisms that can alter in response to diet, disease, and other environmental pressures. Changes in the intestinal microbiota were first correlated with illness in 1681 when Anton van Leeuwenhoek recorded that the microbial composition of his diarrhea differed from normal fecal samples. Since then, the intestinal microbiome has been closely studied to show how it can be implicated in a variety of conditions ranging from obesity to colon cancer. A great deal of investigation into microbiota has been accomplished in the last decade. Many of these observed changes result in an overall loss of bacterial diversity in the microbiota, indicating that species diversity is associated with health. However, the opposite may be true for cause-consequence relations, but not enough research has been brought to light. High-throughput technologies have driven advances in identifying the trillions of microbes and the metabolic functions that live in the colon. This led to a critical insight that gut plays as dynamic of a role in metabolism as the liver. The proximity of these microbes to the intestinal mucosa and gut lymphoid tissue explains the critical role they play in health and disease. Indeed, dysbiosis plays a significant role in the development of inflammatory bowel disease, obesity, and colon cancer. Emerging evidence suggests that diet can directly influence the content and composition of gut microbiota. Thus, understanding the complex interactions between diet, gut microbiota, and the host are crucial in prevention and treatment of chronic diseases that plague our society. Studies in murine models have shown rapid changes in the gut bacteria of mice being switched quickly from a standard diet to a high-calorie diet back to a standard diet.

In humans, surveys show that diets high in fiber correlate with higher microbial diversity and reduced populations of Enterobacteriaceae, including Escherichia and Shigella species. Marked differences are also seen during consumption of animal- vs. plant-based diets. While nutrients in the diet will affect intestinal microbes, other substances present in food may also have an effect. For example, most anthocyanins are not absorbed into the bloodstream in the small intestine, and so they stay in the gastrointestinal tract until they reach the colon. There, they can affect the colonic microbiota in multiple ways. Firstly, anthocyanins have antioxidant activity that can reduce inflammation-induced oxidative stress on the gut bacteria. Secondly, anthocyanins are a potential carbon source, which bacteria can metabolize, resulting in increased growth of certain microbes. Lastly, bacterial metabolism of anthocyanins produces a variety of metabolite byproducts, some of which have antimicrobial effects on enteric pathogen species including Escherichia coli.Chronic intestinal inflammation is a hallmark of certain bowel disorders, such as ulcerative colitis and Crohn’s disease, which are two major forms of inflammatory bowel diseases , and IBD is also considered a risk factor for colorectal cancer. In the latter, inflammation is generally low-grade but persists over a long period of time. Diet composition can promote or suppress chronic inflammation. Low-fiber high-calorie diets, which are typical in Western countries, may directly promote inflammation, or as already discussed, indirectly promote this through dysbiosis. Indeed, some dietary patterns associated with chronic inflammation are also linked to the reduction of total microbial diversity and imbalances in intestinal microbial groups. Furthermore, some bacteria, including E. coli, can flourish during low-grade inflammation, where thinning of the intestinal mucus layer occurs and allows for more direct interaction between the host’s cells and the intestinal bacteria. This condition can cause a feedback loop in which contact between bacteria and epithelial cells leads to dysregulation of mucosal immune response. This contact can lead to a bacterial biofilm, formed when bacteria attach themselves to the surfaces of the aqueous environment in the gut and begin to secrete substances that allow them to affix onto the epithelium. The interaction between bacteria and epithelial cells elevates inflammation,vertical farming tower for sale leading to increased thinning of the mucus and direct host-bacteria interaction. The thali approach, however, combats this cycle in two different ways: by suppressing bacterial growth with anti-microbial phytochemicals , and by reducing the opportunity for inflammation to occur. One molecular pathway involved in such a cycle involves interleukin 6 . This cytokine is normally expressed during acute inflammatory responses, and among other effects, upregulates the transcription factor STAT3. In the nucleus, STAT3 promotes cell proliferation and differentiation as well as upregulating anti-apoptosis genes. When IL6 is chronically elevated, it can lead to an apoptosis-resistant, constantly expanding T-cell population in the intestinal mucosa.

These cells can further contribute to chronic inflammation. Just as a certain diet may promote chronic inflammation, a change in diet can help to restore health. Various bio-active compounds, including anthocyanins, have demonstrated antioxidant activity, reducing local amounts of reactive oxygen species. Low levels of reactive oxygen species can lower the expression of some inflammatory genes, including IL6, and relieve the stresses on both the intestinal microbiota and epithelial cells caused by chronic inflammation. In a study of pigs, we found that supplementing a high-calorie diet with purple potatoes that contains anthocyanins led to a six-fold reduction in levels of interleukin-6 compared to high-fat diet control. Colorectal cancer killed nearly 774,000 people worldwide in 2015, and nearly an estimated 50,630 deaths in 2018 in America making it the third leading cause of cancer-related deaths in the United States in women and second in men. Virtually all cases of CRC are considered to result from an interplay of exogenous and endogenous factors with respect to the variable contribution from each factor. Some non-modifiable risk factors include old age and family history of CRC. Other risk factors, however, are associated with lifestyle or behaviors and thus can be changed. These modifiable risk factors include smoking, obesity, low physical activity, deficiency of dietary fiber, deficiency of vitamin D, deficiency of folate, high intake of red and processed meat, and alcohol consumption. Some of these risk factors, however, are closely related. For example, inadequate fiber intake and excessive fat intake are dietary risk factors which tend to lead to a lack of exercise which ultimately may contribute to obesity, particularly in combination. In the US, 40 percent of adults are obese, and so the risk factors discussed are common mainly due to the modern Western lifestyle. Therefore, it is no surprise that nearly half of the CRC cases arise in the developed nations. The Western diet in its current form contains more risk factors than the calorie and fat content. Foods that contain heterocyclic amines , polycyclic aromatic hydrocarbons , and emulsifiers can also contribute to carcinogenesis. HCA and PAH are produced in meats when they are fried or grilled over an open flame. These substances have been proved to damage the DNA of colonocytes and potentially promote risk of colon cancer. Emulsifiers are used in foods like ice cream to ensure an even distribution of fat molecules. Recent evidence suggests, however, that emulsifiers promote intestinal inflammation, creating an environment that favors colon carcinogenesis in mice. Some of these risk factors, however, are closely related. For example, inadequate fiber intake and excessive fat intake are dietary risk factors. These tend to lead to a lack of exercise, which ultimately contributes to obesity. In the US, 40 percent of adults are obese, and so the risk factors discussed are common mainly due to the modern Western lifestyle. Therefore, it is no surprise that nearly half of CRC cases arise in developed nations. However, colon cancer has a long development period . This gives ample time for lifestyle changes to take place, including diet-based intervention. Chronic inflammation, a condition that is promoted by dietary risk factors also contributes to the development of cancer, even in humans. Patients with inflammatory bowel disease have a significantly increased risk of developing CRC, while long-term aspirin treatment is associated with a significantly decreased risk of CRC. For example, the IL6/STAT pathway discussed earlier is also implicated in cancer formation. Over expression of IL6 leads to excess STAT3 transcription, causing unwanted cell proliferation not only in T cells but also in the intestinal epithelium. Another inflammatory cytokine of note is TNF α. While the intestinal bacteria can promote inflammation, they may also affect the likelihood of CRC more directly. Once the intestinal mucus layer is thinned, and direct bacterial-epithelial cell interactions occur, certain bacterial strains promote tumor development. E. coli strains bearing the pks island are of particular interest. This genetic locus codes for the secondary metabolite colibactin, along with the enzymes necessary for its production.

Comparing estimates from columns and suggests that the inclusion of time invariant parcel characteristics, such as parcel size and distance to the coast, as well as time-varying lagged crop choice and lagged recycled water deliveries is important.Our empirical approach is deliberate in conditioning on an array of factors that are likely correlated with both crop choice and salinity. The inclusion of the annual time trend and water prices in column provides an opportunity to test if our estimates of WTP are robust to their inclusion. The stability of our estimates between columns and lends credibility to our identifying assumption that, conditional on observables, salinity is uncorrelated with unobservables that may impact crop choice. A look at the marginal effects reveals how crop shares in the region change due to salinity. Using the estimates from column of Table 3.3, we hold the control variables constant at their average levels and show the predicted share of parcels in each crop type under a constant basin-wide TDS level of 2000 mg/L in Table 2.3. This is depicted relative to the average share of crops by type in the sample period. We see that given this increase in TDS of almost 1,360 mg/L, fallow ground would increase from 10.6% of parcels to 12.3% of parcels, holding all other variables at their averages. Likewise, vegetables and strawberries would increase slightly by 1.3 and 1.7 percentage points, respectively, and caneberries would decline by 4.5 percentage points. An increase in vegetable crops relative to fallowed land due to a change in salinity, holding all else constant, is intuitive due to their insensitivity to salt relative to the other regional crops, as shown in Figure 3.4. Interestingly,round plastic pots shares of strawberries also increase and the greatest declines are observed in caneberries, despite strawberries being relatively more salt sensitive. This may reflect the relative value per-unit of these crops or the fact that strawberries are often times rotated with vegetable crops such as broccoli, lettuce, and cauliflower for pest and soil management.

We next use these estimates to deduce growers’ willingness to pay for a reduction in groundwater salinity. We focus on crops whose estimates in Table 3.3 were significant at the 95% confidence level or greater, namely, vegetables, strawberries, and caneberries. The willingness to pay estimates for a reduction in groundwater salinity of 10 mg/L are reported in Table 4. While these willingness-to-pay estimates are wide-ranging, the high dollar values indicate that growers highly value water with low salinity levels. These WTP estimates are on the same order of magnitude as the expected revenue losses from a drop from 100% to 90% yield capacity as shown in Figure 3.4. To put these magnitudes into perspective, row cropland in Monterey and Santa Cruz Counties in 2021 ranged in value from $28,500 to $75,000 per acre, representing some of the most expensive cropland in the state. Contrast this to the range of values observed in 2021 for well-dependent cropland in Fresno county which ranged from $10,000 to $16,000 per acre . To assess the robustness of our results, we test the sensitivity of our results to two modeling choices. First, we take a closer look at our measure of salinity, which can be measured in different ways. We chose to focus on TDS in our main estimation, since it is widely used in the agronomic literature and is a measure of general salinity. This allows us to look at results that may be applicable across multiple types of salinity problems . One concern may be that growers actually respond to an alternative salinity metric when faced specifically with seawater intrusion. Chloride is a measure of salinity that specifically captures seawater intrusion, rather than salinity from other sources, such as soil, rock, or other natural materials. Table 2.5 reports marginal effects based on the estimation of our preferred specification from the last column of Table 3.3, except we replace the salinity variable with chloride measurements. On average, chloride levels are 15% of TDS values, so an increase in chlorides to 300 mg/L is similar to a shift in TDS to 2,000 mg/L. As shown, results are largely the same across these two highly correlated measures of salinity.

Larger marginal effects are estimated for vegetable row crops and caneberries when using chlorides, which may be due to the fact that the spatial distribution of chloride concentrations is different than that of TDS. Finally, we take into account the possibility that other water resources may be available to a subset of growers in the Pajaro Valley. Farmers located near the coast experience some of the highest salinity levels relative to the rest of the basin, and simultaneously impose the greatest externality on others when they pump groundwater. PV Water recognizes this, and in collaboration with the growers in the basin and the City of Watsonville, set up the Delivered Water Zone and a distribution system to deliver recycled water and other alternative supplies to the growers most impacted by seawater intrusion. The distribution system serves roughly 15%, or 5,000 of the 30,000 acres farmed in the Valley. The total quantity delivered has slowly increased from 667 AF in 2005 to 4,203 AF by 2016. This is a small fraction of irrigation water used within the DWZ, but it is likely still relevant for farm-level decisions. It is plausible that growers inside the DWZ have different projections of their future access to high quality water and are less responsive to groundwater salinity, compared to growers without access to delivered recycled water. In addition, anecdotal evidence from conversations with growers in the Valley suggests that growers inside the DWZ who had been unable to plant strawberries before they started receiving deliveries are now able to plant the salt-sensitive crop once again. While we conditioned explicitly on recycled water deliveries to farmers inside the DWZ in our initial estimation, we perform a robustness check by removing all parcels within the DWZ, to focus solely on the effects of salinity on crop choice when there are no other water sources available. The fraction of parcels planted in various crop categories differs for this subset so marginal effects in this case need to be compared to a different baseline. Marginal effects from the estimation of salinity impacts on this sub-sample are shown in Table 2.6.

Results are very similar in magnitude and significance to those reported in Table 2.3, suggesting that the existence of the DWZ is not biasing our estimation of the relationship between salinity and crop choice. Finally, we ask the question of what would happen to crop choices and to consumer welfare under a scenario in which the quality of groundwater deteriorates significantly across the basin. We simulate and compute the utility-maximizing crop choices for each parcel in each year under a high TDS scenario and plot the distribution. To do this, we keep the estimated marginal utilities for the attributes of crops, parcels, and climate variables the same as in the panel mixed logit model displayed in column of Table 3.3. For each parcel, we estimate the probability of choosing each crop type and use these to predict each parcel’s baseline crop choice. Then,hydroponic bucket we recalculate the probabilities of each crop being grown for each parcel after altering the vector of TDS values to reflect a higher salinity scenario. Ideally, we would simulate the change in TDS predicted by a climate change model of sea-level rise. This exercise is challenged by the fact that model predictions of sea-level rise, while necessary, are insufficient for deploying our model of crop choice. To use climate model output in our simulation, we would need to map sea levels to the salinity concentration in the groundwater wells on each parcel throughout the Pajaro Valley. Doing this would require the use of a hydrologic model of the groundwater basin, which is beyond the scope of this paper. Further, seawater intrusion is highly influenced by demand for groundwater resources, so the decomposition of changes in salinity to either sea-level rise or to groundwater overdraft is challenging. Climate change is predicted to cause higher temperatures and more variable precipitation, which may lead to increasing demand for groundwater, in addition to a rise in sea levels . Instead, we opt to model a realistic increase in TDS by looking at how much groundwater salinity has increased in the basin over our sample period. The average spring TDS during our sample period is 644 mg/L. From 1990-2020, four years had an average TDS greater than double this value, with an average increase of 10% annually. For a relatively straightforward simulation, we increase the current-period TDS by 100%, to see how crop choice would evolve with this plausible shift in salinity. All other variables, including weather, remain stable for this analysis, which allows us to focus on how salinity specifically impacts cropchoice distributions. The estimated change in the distribution of crop choices is plotted in Figure 2.8. The graph plots the difference between the original model estimates of crop choice and the simulated estimates of crop choice under an increase in TDS conditions of 100%. Caneberries experience the largest shift in parcels planted under the 100% increase, which coincides with their sensitivity to salinity, as well as their relatively lower profitability when compared to strawberries, another salt-sensitive crop. Vegetables experience the largest increase in the probability of being planted, as they are the least salt-sensitive. Fraction of land left idled also increases substantially under the high TDS scenario.Seawater intrusion, which occurs when saline water from the ocean enters a freshwater aquifer, can manifest from two primary drivers: groundwater extraction and sea-level rise. Pumping groundwater faster than the natural rate of recharge can move seawater to freshwater zones, and sea-level rise alters where saltwater sits relative to freshwater in the aquifer .

Salinity is a major concern for coastal agricultural production that is dependent on groundwater for its water supply , but it can also have significant impacts on inland irrigated agriculture as salts accumulate in the soil over time. Increased salinity levels in agricultural water lead to declines in agricultural productivity, and farmers are left with few mitigation strategies. In this paper, we empirically evaluate the likelihood that farmers switch crops in response to changing groundwater salinity, with an application to the Pajaro Valley, a coastal region in California. Unique spatial panel data on groundwater quality and land use spanning 11 years lends itself to a panel mixed logit model of crop choice. This revealed preference approach allows us to estimate the marginal willingness-to-pay for improvements in irrigation water salinity. We find evidence that growers are more likely to shift away from crops that are saltsensitive, such as strawberries and caneberries, relative to fallow ground, when facing an increase in groundwater salinity. The marginal WTP to pay for a 10 mg/L reduction in TDS varies by crop, and ranges from $1,613 for strawberry growers to $16,369 for caneberry growers. Our simulation of a 100% increase in TDS across the basin speaks to potential land use changes in the basin if salinity trends continue. We estimate that a change in TDS of this magnitude, which could realistically occur in a future defined by sea-level rise and continued groundwater overdraft, would result in a welfare reduction of $140 million. While our WTP and marginal damages estimates are restricted to an agricultural region defined by the jurisdiction of a single water management agency, most groundwater management decisions and investments are made at this scale. The paucity of robust, geospatial groundwater quality data that can be paired with accurate planting information precludes us from deriving estimates in other regions. While salt sensitivity is crop specific, which will drive differences in the WTP across regions, this methodology is generalizable and can be applied elsewhere to determine the benefits of reducing groundwater salinity. Salinity is becoming an increasingly common issue across the United States and the globe as sea levels rise and groundwater aquifers become more stressed under climate change. Estimating marginal damages from changing salinity can provide new context for the cost of climate change and the cost of groundwater overdraft, both of which are broadly important for groundwater management.The stability of water resources for agricultural production has always been an important topic, but the scale and urgency of the issue has dramatically increased in recent decades.

The principle is that the features of samples belonging to the same category are close to each other, while the features of samples belonging to different categories are far from each other. The earliest representative work is Siamese Network, which is trained with positive or negative sample pairs . Vinyals et al. proposed the Matching Networks, and they borrowed the concept “seq2seq+attention” to train an end-to-end nearest neighbor classifier. Snell et al. proposed Prototypical Network, which learns to match the proto center of class in semantic space through few samples. Sung et al. proposed Relation Network, which concatenates the feature vectors of the support samples and the query samples to discover the relationship of classes. Li et al. proposed CoveMNet based on the covariance presentation and covariance metric of the consistency of distribution. The network extracts the second order statistic information of each category by an embedding local covariance to measure the consistency of the query samples with the novel classes. Chen et al. proposed Meta-Baseline method, which achieves good performance on some FSL benchmarks. The accuracy achieves at 83.74% with 5-way, 5-shot task of Tiered-ImageNet, and 90.95% with 1-way, 5-shot task of Mini-ImageNet. Recently, FSL has started to be used in research on plant disease identification. Argüeso et al. used Siamese Network on the dataset Plant Village . Jadon proposed SSM-Net that uses the Siamese framework and combines two features from a Conv and a VGG16. Zhong et al. proposed a novel generative model for zero-shot and few-shot recognition of citrus aurantium L. diseases by using conditional adversarial auto-encoders. Afifi et al. compared Triplet network, Baseline, Baseline++,strawberry gutter system and DAML on PV and coffee leaf datasets. The results show that the Baseline has the best performance. Li and Chao proposed a semi-supervised FSL method and tested it with PV.

Nuthalapati and Tunga introduced transformer into plant disease recognition. Chen et al. used meta-learning on Miniplant-disease dataset and PV. Li and Yang used Matching Network and tested cross-domain performance by mixing pest data. These methods have been tried from various perspective and have made important progresses. Nevertheless, FSL still has two common challenging issues: limited features extracted from few samples are less representative for a class ; the generalization requirements are very high and various. In this work, we tackle the two issues by using multi-scale feature fusion and improving training strategies. CNN is widely used in image-based deep learning methods. In a CNN architecture, the local features with more details and small perceptive fields are extracted from low-level layers, while the global features with rich semantic information and large perceptive fields are extracted from high-level layers . MSFF is the technology using multi-scale features which are extracted from different layers of CNN . In object detection and semantic segmentation, many excellent networks are proposed by using MSFF, such as Feature Pyramid Network , Unet , Fully Convolutional Network etc. MSFF is also used in image restoration, image dehazing and image super resolution etc. . These methods fuse features by using dense connection, feature concatenation or weighted element-wise summation . In common, the mentioned methods have encoder-decoder framework. The multi-scale features extracted from encoder are reused in decoder to enhance feature representation. However, in conventional classification task, MSFF is seldom used because the network does not have decoder. Generally, only the top semantic features are fed into classifier, but other scale features are abandoned. But in fact, the high-level features and the low-level features are not subordination relationship. The local features including rich fine-grained features can be an effective compensation to formulate a richer feature representation of sample . In the data-limitation condition, it requires to extract as many features as possible from a limited amount of data.

Therefore, in this work, we propose to leverage the MSFF to enhance feature representation. Multi-scale features can be fused in different ways. In our work, we use cascaded multi-scale feature fusion . The channels of feature maps increase after feature fusion. But it does not mean that all channels are the same significance. The contribution of each channel is different. Some channels should be emphasized and some should be suppressed. Attention can help to focus on the meaningful channels. Attention mechanism plays important role in human perception to selectively focus on salient parts in order to capture visual structure better . It has been leaded into some areas of machine learning such as computer vision, natural language processing etc. and has significance to improve performance . It not only tells where to focus, but also improves the representation of interests. Recently, some light-weight attention modules have been proposed. Wang et al. proposed Residual Attention Network that uses encoder-decoder style attention module. Hu et al. introduced a compact module to exploit the inter-channel relationship, which was named as Squeeze-and excitation module. Woo et al. proposed Convolutional Block Attention Module that includes channel attention and spatial attention. These light-weight attention modules can be easily embedded into deep learning networks as plug-ins. In this work, we use the CA to weight the accumulated channels obtained from CMSFF. As the definition of FSL, it is asked to generalize to novel categories or novel domains. Generalizing to new categories within the same domain of training is defined as intra-domain classification, while generalizing to novel domain is defined as cross-domain classification. Long-tail distribution of data is common in plant disease datasets. To identify the part of categories with few samples, the model can be trained with the part of diseases that have more samples.

This generalization happens in the same domain. Cross-domain happens when a set of categories with few shots is required to be identified but does not belong to any dataset. Cross-domain adaption happens between different datasets, which is more difficult than intra-domain adaption. However, researchers found that it is frequently encountered situation and inescapable for boosting FSL to practical application. Guo et al. established a new broader study of cross-domain few-shot learning benchmark and pointed out that all meta-learning methods underperform in relation to simple fine-tuning methods, which indicates that the difficulty of the cross-domain issue. Adler et al. proposed a method of representation fusion by an ensemble of Hebbian learners acting on different layers of a deep neural network, which is from feature representation perspective. Li W.-H. et al. proposed a task-specific adapters for cross-domain problem from the perspective of network architecture. Qi et al. proposed a meta-based adversarial training framework for this problem, which is also from the perspective of network architecture. As we know, there is no research that has been done from a training strategy perspective. These efforts are the kind of general explorations of using general benchmarks and rarely discuss specific domains. In fact, different domain has its own characteristics and resources to utilize when crossing domains. Hence, in this work, we propose a set of training strategies to match various cases of generalization using the available data resources. The contributions of this work are summarized as: we propose a Meta-Baseline based FSL approach merging with CMSFF and CA for plant disease recognition; we propose a group of training strategies to meet different generalization requirements; through extensive comparative experiments and ablation experiments,hydroponic fodder system we validate the superiority of our method and analyze various factors of FSL. Comparing with the existing related works under the same data conditions, our method has achieved at the best accuracy.In this research, three public datasets are used in our experiments. Mini-ImageNet is a subset of the ImageNet, which includes 100 classes and 600 images per class. We select 64 classes in our experiments. The second is PV released in 2015 by Pennsylvania State University. It is the most frequently used and comprehensive dataset in academic research up to now in plant disease recognition. Totally, it includes 50,403 images which crosses over 14 crop species and covers 38 classes, as shown in Table 1. Because the number of samples in PV is unbalanced, we use the data after augmentation and select 1,000 images per class to keep balance. The third is the dataset of apple foliar disease , which was published in FGVC8 Plant Pathology 2021 Competition. All images of AFD were taken in wild with complicated backgrounds, as shown in Figure 1A. Like classical classification structure, our framework contains two components: an encoder and a classifier, which is illustrated in Figure 2A.

The encoder noted as fθ is a CNN-based network merging with CMSFF and CA. It is trained in two stages: base-training and meta-learning. In base-training, the network contains fθ and base-training classifier, which is trained with image-wise data. The goal in this stage is to learn the general features as prior knowledge. Some large-scale general datasets with more classes and diverse data, such as ImageNet, Mini-ImageNet etc. are good choices for learning prior knowledge. The classifier can be linear classifier, fully connected layer, SVM, or other classifiers. The cross entropy loss is calculated to update the parameters of fθ during back propagation. After base-training is completed, the classifier is removed and the trained model is delivered to the meta learning stage. In meta-learning, fθ is initialized by the trained model from base-training. Meta-learning is a concept of learning to learn. So, the purpose is not to learn the knowledge of the training classes, but to learn how to differentiate between classes. Aiming at the objective, the classifier in meta-learning is replaced by a distance measurement module. The classification result is decided by the distances from the support samples to the query sample. Meta-learning is a task-driven paradigm where training data is formulated as N-way, K-shot tasks. Based on a simple machine learning principle: test and training conditions must match , the data of Cnovel is also formatted into tasks in test. After embedding, the 2D color image has been a high dimensional vector in semantic space. The distance of query sample to the class centroid is calculated by a distance metric. Distance metric uses distance function which provides a relationship metric between each element in the dataset. In many machine learning algorithms, distance metric is used to know the input data pattern in order to make any data-based decision. The most common used measures to calculate the distance between two vectors are cosine similarity, dot product and Euclidean distance. Cosine similarity is a measure of similarity between two non-zero vectors of an inner product space. It is measured by the cosine of the angle between two vectors and determines whether two vectors are pointing in roughly the same direction. It is the same as the inner product after normalization . In Euclidean geometry, the dot product of the Cartesian coordinates of two vectors is widely used. It is often called as inner product or projection product of Euclidean space. The length of projection represents the distance of two vectors. In mathematics, the Euclidean distance between two high-dimensional vectors is the square root of the sum of the squares of the distances in each dimension. Basically, the structure of MSFF includes two categories: parallel multi-scale feature fusion and cascaded multi-scale feature fusion . The two fusion methods are illustrated in Figure 2B. The PMSFF concatenates the features from different layers of CNN simultaneously. The different resolutions of feature maps are uniformed before concatenation. Comparatively, the CMSFF fuses the different resolution feature maps step by step. Taking Resnet12 as backbone network, four convolutional blocks are linked. A group of feature maps of double times of channels and half resolution is generated after each block forwarding. In the backward fusion, small size feature maps are two times up-sampled and concatenated with the feature maps of previous block. After a series of up-sampling and concatenation, all channels are fused together to be the fused full-scale feature, noted as F. The CMSFF is used in this work. The domain of training is noted as source domain , and the domain of test is noted as target domain . Data from different domains can be used in the three stages: base-training, meta-learning, and test. It is special that there are two training stages of our method, and the datasets used in the two stages could be different. We just consider the domain of meta-learning stage as SD. When SD is the same as TD, it is intra-domain adaption, otherwise, it is cross-domain adaption. In order to mimic different adaption situations, we design different data configurations.

If, in contrast, gibbons would react competitively as other great ape species did in previous social dilemmas, we would expect them to try to maximize their food rewards by hesitating to act and by taking advantage of their passive role—placing themselves in front of the release mechanism. In that sense, we would expect passive partners to benefit from their position and obtain more rewards than the actors. Furthermore, we would also expect gibbons to be more likely to act in direct food test trials given that they could easily obtain at least one direct reward from their actions.Therefore, actors were still able to obtain the majority of the five released rewards in both conditions. Furthermore, actors obtained the extra rewards in 87% of the direct food test trials in which they acted. In line with this finding, Fig. 2 shows the percentage of trials in which individuals release food against the number of rewards that each individual obtained in indirect and direct food test trials. Interestingly, in only one dyad the more active individual obtained less benefits than the passive partner in both conditions. We also found significant effects of our control variables age and length of dyad suggesting that younger individuals obtain more food and that dyads who have been longer together distributed the five rewards more equally. Next, we evaluated whether passive gibbons acted strategically by placing themselves in front of the ramp at the moment the actor released the five food rewards and whether they would take advantage of their position in direct food test trials compared to indirect food test trials given that the actor gibbon would spend some time retrieving the food baited inside the handle.We also explored whether gibbons would take an advantageous position after the food had been released.

For that we measured whether the passive individual was in front of the ramp by the time the actor arrived at the location where the food had been released. After releasing the food,hydroponic nft the actor moved to the food location in 237 of those 287 trials . Passive individuals were in front of the ramp by the time the actor arrived in 76 occasions . We found no differences between conditions . We found that actors did not approach the released food in 50 trials in which they released it. A majority of those trials were direct food test trials . This makes sense since actors spent some time obtaining the food reward placed inside the handle. Nevertheless, in a great majority of these trials the actors ended up obtaining the food reward from the handle before the passive individual finished her last reward. Interestingly though, this behavior predominantly occurred in three of the six dyads. Furthermore, we only found one case in which the actor showed an intention to approach the partner by getting closer to him.Te results of the study suggest that dyads of gibbons managed to solve a competitive food task where one dyad member had the opportunity to pull and activate a release mechanism containing five potential food rewards for both partners. When gibbons had the opportunity to obtain an extra reward from their actions , they almost always acted, avoiding mutual defection. In contrast, in an indirect food test condition where gibbons could not obtain the extra rewards from their pulling efforts, their likelihood to pull and release potential food rewards dropped significantly in comparison to the direct food test condition. In our opinion, two primary reasons could explain this pattern of results. First, it is possible that gibbons were more motivated to pull when they could directly benefit from the extra reward inside the handle. Similarly, gibbons would have significantly pulled more often in the indirect food test condition compared to the no food control because they could still obtain some rewards. Clearly, gibbons showed that they did not just act for the sake of pulling the rope. Most likely, their actions were motivated by the prospect of obtaining rewards, especially when those were easier to access. While this reason is very plausible, it does not necessarily account for why gibbons did not pull for 90 s in almost 40% of the indirect food test trials.

This is especially surprising if we consider that actors benefitted more than passive partners in this condition. In other words, gibbons did not seem to interpret the situation as beneficial for actors. If that were the case, we would have expected gibbons to pull more often in indirect food test trials. Thus, the second possible explanation for our results is that gibbons interpreted the situation as a conflict of interest and hesitated to pull to avoid losing rewards in favor of the passive partner. This interpretation would be in line with previous findings in chimpanzees, bonobos and common marmosets. Thus, given the two non-mutually exclusive explanations, it remains unclear whether gibbons defected in indirect food test trials due to a reduced motivation to act because they could not access the extra reward attached to the handle or because they wanted to avoid the possibility of losing rewards to their partner. So far, we have mainly discussed gibbons’ decisions whether to pull or not. The next question concerns whether gibbons strategized when they took a passive role. In other words, did they try to maximize their own rewards when their partners pulled? The main source of potential conflict between participants lied on the possibility that passive individuals could position themselves in front of the release mechanism during direct and indirect food test trials. In direct food test trials, this could be particularly beneficial for passive partners given that actors could lose some valuable seconds trying to obtain the extra food reward attached to the handle. However, we found that actors actually obtained most of the rewards in both conditions, with a special advantage over passive partners during indirect food test trials. In fact, in only one dyad of gibbons the passive individual obtained more rewards than the actor in both test conditions. Furthermore, passive individuals rarely took advantage of the situation and they did not distinguish between conditions. That is, during direct food test trials passive partners did not benefit from the time that the actors spent trying to obtain the reward located inside the handle. In that sense, gibbons did not interpret the situation as a social dilemma in which they could benefit more than their partner.

Yet, gibbons also did not solve this task cooperatively. For that to be the case, dyad members would have needed to benefit more or less equally on both conditions and they would have not hesitated to manipulate the handle in indirect food trials. It is also very unlikely that gibbons’ decisions were driven by proactive prosocial motivations such as releasing food rewards to favor their dyad members given that actors benefited the most from their own actions. One possible explanation to understand why actors obtained more rewards than passive partners is that both individuals approached the handle during direct food test trials to obtain the reward, although only one individual pulled the handle. This occurred in 27.6% of the direct food test trials in which an individual pulled the handle. This possibility could partially explain why passive gibbons rarely position themselves in front of the release mechanism during direct food test trials, but it cannot explain why in indirect food test trials they did not take advantage of their passive role. In fact, in indirect food test trials passive partners approached the handle in 10% of trials. However, there are numerous reasons to suggest that a dominance component cannot fully explain our pattern of results. First,hydroponic channel only three of 12 individuals released rewards in less than 20% of the direct and indirect food test trials. Te result suggests that although they did not solve the task cooperatively, in half of the dyads both individuals exchanged roles relatively often. Furthermore, our results are also in line with literature suggesting that there is no clear dominance of one sex over the other and that gibbons engage in food sharing in both captive and natural settings. Importantly, conflict avoidance does not seem to be relevant here either. Cofeeding events occurred three times as often than displacements events, suggesting that individuals were usually tolerant with each other, as it has been observed in other populations. Relatedly, gibbons never hoarded the blueberries. They ate them as soon as they got them. Furthermore, these tolerance may be mediated by the length of time that dyads had spent together. In our study, the length of dyad predicted how equally gibbons divided the five food rewards. A third alternative explanation is that once a gibbon decided to manipulate the handle, the other one totally disengaged from the task, as if acknowledging a sort of property claim. This could explain why passive partners did not take an advantageous position in front of the release mechanism and why, as a consequence, actors did not face a social dilemma in many trials. After all, actors benefit more than passive partners despite the costs to pull the rope, understood as the possibility to lose rewards due to the distance they had to cover and the time lost to return to the location where the food was released. Nevertheless, this is unlikely because passive individuals still obtained a significant fraction of the food rewards .

All these previous arguments cannot fully explain why passive partners rarely took advantage of their position, especially given how successful this strategy was: passive partners obtained almost 75% of rewards when they positioned themselves in front of the release mechanism by the time the actor manipulated the handle. We thus propose that passive gibbons did not always take advantage of their partner actions because of the combined processes of motivation from the side of the actor and a general high level of social tolerance towards inequities. Tat is, individuals that were more motivated to obtain food and more attentive were also more likely to take the actors’ role in our task. Trough participation, they could become more aware of the situation as a whole and react faster to obtain the rewards despite the potential costs of pulling the rope. This gave them an advantage over their passive partners, whom at the same time tolerated actors obtaining the majority of rewards . Importantly, tolerance towards reward inequities also came from the perspective of the actors. Indeed we found that in fly trials individuals from five of the six dyads seemed to adopt a prosocial attitude towards their passive partners by letting them access all the released rewards. Future studies should improve different aspects of our setup to continue exploring gibbons’ decision-making strategies when individuals’ interests collide. Te main weakness of our design is that we were not able to separate dyads of gibbons before the experimental sessions. In that sense we could not train them with the different task contingencies as it is usually the case in this type of settings but see. It is thus possible that some individuals were more skillful than others, and that might have affected our results. Nevertheless, all individuals approached the apparatus and obtained rewards and only one never pulled from the handle during the course of the study. Moreover, despite the fact that gibbons distinguished between conditions with food and the no food control, their latencies to act did not differ between the indirect food test trials and the no food control trials. This could be interpreted as strategic behavior in the indirect food test trials if the gibbons were waiting for their partners to act. It is possible that with longer trials we would have found a significant difference between gibbons’ latencies in indirect food test trials and no food control trials. In that sense, future changes in the trial time or the food rewards can better assess whether gibbons strategize to solve conflicts of interest. Relatedly, it is possible that gibbons were more motivated to act during direct food test trials compared to indirect food test trials because there were more rewards in play . It has been found that at least great apes are able to distinguish between these two amounts when they are presented at the same time.