Given the previous epochs from 1 to 8, has values for their F1 Score and Accuracy. It shows that there is possible room to improve the model with more fine-tuning and possibly an early stop in training to not have the model over-train to get the result of 1.0 for F1 Score and Accuracy. Another possible reason for the result could be the large imbalance of images between classification labels and that the Plant Village data set is considered to be a small data set. These types of results are good but not realistic for model prediction power. Even though these values are incredibly high, the training and validation loss is still fairly low and slowly converging to 0. This means that the model is learning over time, which is a good sign and shows room for improvement. A possible future improvement for this project would be to find another data set with more specific plant disease information to train the model on. Efforts will be made to look for data that includes more plant pests. That variation would be beneficial because the data set for this project mainly contains crop disease images. The disease Spider Mite, is labeled as a disease in this data set but in reality, is not a disease. It is the only classification label that has pest-inflected crop images in this data set. Having more data on crop pests would be beneficial because crop pests also cause a significant amount of crop loss and damage as well. Technical improvements for this project include developing a stronger data augmentation technique. Instead of using the set transform method which artificially augments the data set,garden grow bags using another package that can actually create the separate images and add them to the data set instead would be interesting to see how it would perform. More Hyper-parameter fine-tuning could be done such as exploring the learning rate and adding an optimizer. More Epochs should be tested in order to see how the model will perform over a greater period of time.

Fewer epochs will also be tested to see how early-stopping the model from training will perform. Another idea is to explore more the Training-Validation-Testing splits chosen for the data. Exploring the performance between different splits could show how to better improve the classification model. To achieve our expected agricultural need of feeding 10 billion people by 2050, we must prioritize minimizing crop loss wherever possible. More research is needed to help develop more tools to assist crop growers with preventing crop loss. The study “Mobile phone use is associated with higher smallholder agricultural productivity in Tanzania, East Africa” by Amy Quandt et al. looks into the relationship crop growers have with their cell phones as agricultural tools to help increase crop yields. “A key result is the positive association between phone use for agricultural activities and self-reported agricultural yields”. Cell phones are increasing accessibility to technological tools that help with agriculture. These technologies for assisting with crop loss will not only be utilized by commercial crop growers or the average hobbyist and enthusiast as well. Whether crop growers use a ViT image classification model or a convolutional neural network image classification model, or another type of machine learning architecture is used, more research is needed to help develop tools to assist crop growers worldwide in eradicating crop loss everywhere! The original Specialty Coffee Asscn. of America Coffee Taster’s Flavor Wheel was developed in 1995 by Ted Lingle, before many advances and methods in sensory science had been developed . To revise this longstanding industry tool, sensory science and statistical methods were applied as novel flavor wheel construction techniques. Even today, across food and beverage industries, very few flavor wheels exist that were created using a scientific approach and a sensory lexicon. A lexicon is a list of vocabulary developed using sensory descriptive analysis methods used to describe a product, along with descriptions of each attribute and reference preparation instructions .

Some notable existing flavor wheels have been created using sensory lexicons, for products such as beer, wine, tea, spices, and even drinking water, but the flavor wheel construction methods differed from those used in the current study Suffet and others 1999; Gawel and others 2000; Koch and others 2012; Lawless and others 2012. Lawless and others used similar statistical techniques to those used in this study to develop the McCormick Spice Flavor Wheel; however, the data used were simply a subset of descriptive analysis data gathered from lexicon development, with no sorting task. In the development of a tea flavor wheel, Koch and others used all descriptive analysis data to perform principal component analysis to determine the positioning in the flavor wheel, but no clustering techniques or sorting exercises were utilized. Gawel and others did use a sorting task, as in this study, for mouthfeel attributes in wine, but slightly different clustering statistical techniques were used, and only 9 experts participated in the sorting exercise. Prior to this project, SCAA and World Coffee Research worked with sensory scientists, industry representatives, and trained panels of judges at the Sensory Analysis Center at Kansas State Univ. and Texas A&M Univ. to develop a lexicon of about 110 attributes to describe flavor , texture/mouthfeel, and amplitude . The WCR Sensory Lexicon was then sent to UC Davis to be sorted into categories and levels to be converted into an updated Coffee Taster’s Flavor Wheel. The words in a flavor wheel serve to standardize training and aid in education and discussion. The original Coffee Taster’s Flavor Wheel has served as a communication tool about coffee products among all components of the industry, including tasters, plants, retailers, exporters and importers, producers, baristas, and consumers. The new Coffee Taster’s Flavor Wheel will serve as an improved communication tool, as it is an organized visualization of the WCR Sensory Lexicon . This tool is the 1st step toward enabling the coffee industry to identify and characterize specific flavor changes and relate these changes to specific variables in the coffee process, which brings us one step closer to understanding which factors drive coffee flavor.Although this type of scientific conversion from lexicon to flavor wheel was unprecedented, existing sensory and statistical methods were also applied for the purposes of this study.

A rapid sensory profiling method sans tasting, called single free sorting, was utilized to determine the similarities and dissimilarities among the 99 coffee flavor attributes. Once the data from the individual sorting tasks were collected and summarized, 2 multivariate statistical techniques were applied. First, to determine the major categories, subcategories, and levels, agglomerative hierarchical clustering was used. Conjointly, to determine the arrangement of these categories and subcategories in the wheel structure, multidimensional scaling was used. AHC and MDS are both techniques used in sensory science to observe and visualize the similarities between different products, consumers, or attributes . In this way, existing sensory and statistical methods were adapted to create a novel method for constructing a flavor wheel from a defined lexicon.Twenty-nine trained descriptive analysis panelists were contacted and recruited from other descriptive studies already in progress at UC Davis. These panelists were not required to be trained specifically on coffee, but they were required to be regular coffee drinkers, had all participated in descriptive analysis on products with complex flavors, and had worked with and been exposed to most of the flavor attributes in the WCR Sensory Lexicon. Panelists were not further trained for this experiment,tomato grow bags because group discussions may have allowed the more opinionated panelists to influence the decisions of the quieter panelists. For this experiment, it was decided to simply allow panelists to draw on their individual experiences and subsequently compile and average all the data, rather than holding group discussions and coming to a group consensus. Recruitment, screening, and scheduling were done via email. Once accepted into the study, participants were sent written instructions to perform the sorting task on the web app remotely from their personal computers. The entire process was online and remote. In order to accurately reflect the coffee industry needs, create an additional set of data, and add more statistical power, 43 coffee industry experts recruited by SCAA performed the same online procedure as the UC Davis panelists. The industry panelists came from all areas of the coffee industry and they all had experience as coffee tasters, but not all of them had experience in sensory descriptive tests.Before the sorting task began, the WCR Sensory Lexicon was reduced to 99 flavor attributes, removing all attributes not exclusively referring to flavors. Specifically, the attribute “astringent” and all attributes in the Texture/Mouthfeel and Amplitude sections were removed. The word sort procedure was originally done in a Steinberg study , to be used as a tool for semantic analysis, particularly regarding connotations. This sorting method has since been adapted to food samples for sensory analysis .

Traditionally, panelists are asked to sort food products or other samples into as many clusters or groups as they choose, in a way that makes sense to them . In free multiple sorting, a rapid sensory descriptive method, panelists repeat this procedure until they feel they have exhausted the sorting possibilities, and then they are asked to provide descriptions for each group of samples . In a study comparing single sorting to multiple sorting, Rosenberg and Kim found that multiple sorting was superior in representing all possible dimensions of categorization of the data. Additionally, one drawback to using single sorting is that the individual data need to be summed together in order to analyze it, so individual data are lost . In this experiment, instead of sorting food samples themselves, panelists were asked to sort the attributes into categories and subcategories without tasting samples and therefore based on their experience and expectations of these flavor descriptors. Thus, this sorting exercise was similar to the original word sort procedure performed by Steinberg in 1967. Sorting the words themselves was appropriate in this case, due to the ultimate goal of using the Coffee Taster’s Flavor Wheel as a tool for coffee industry professionals. Since there was no tasting, fatigue, adaptation, and carryover effects did not bias the data . Additionally, as there were 99 attributes, to avoid fatigue, instead of repeating the procedure multiple times, the panelists each only sorted the lexicon once. A user-friendly web interface was created using AngularJS to allow for simple, efficient sorting of the 99 flavor attributes. This helped to minimize the clutter of index cards and catalyze the data collection process, because data could be stored immediately in Firebase , a free database and web application hosting service. The website had a welcome page and the participants would log in and be greeted with brief instructions and a “begin” button. The users would then see further instructions and the list of attributes, each with Table 3–RV-coefficients from multiple factor analysis comparing UC Davis and coffee industry participants. Industry UCD MFA Industry 1 0.414 0.832 UCD 0.414 1 0.850 MFA 0.832 0.850 1 a question mark to the far right with a scroll-over pop-up with the WCR definition of that attribute. If a user was unclear about the meaning of one of the words of the lexicon, he/she could scroll over the information bubble to access the definition. The participant was able to click and drag the attributes into categories and subcategories, for as many hierarchical levels as they deemed necessary. Once the user felt the attributes were adequately sorted into categories and subcategories, they would press “submit” and the results were immediately stored in the Firebase database.The methods of AHC and MDS were used to represent attribute–attribute relations instead of product–attribute relations, because there were no coffee samples, only attributes. To organize the raw data, a program was written in Ruby to translate the sorting data into matrices that could be used for analysis. For both of these methods, 1st, 2 binary matrices were created for each participant , one for “sibling–sibling” relationships, in which the attributes appeared in the same subcategory, and one for “parent–child” relationships, in which one attribute appeared in a subcategory under another attribute.

In summary, DP completely prevented cancellous bone loss caused by irradiation over this short duration study . Our studies demonstrated that DP diet supplementation was equally effective at preventing the skeletal responses to both low-LET gamma radiation, at a dose equivalent to a single fraction of radiotherapy, or combined proton and HZE ions, simulating space radiation. Therefore DP or its components may provide effective interventions for loss of structural integrity caused by radiotherapy or unavoidable exposure to space radiation incurred over long duration spaceflight.Animals. Male C57BL/6J mice experiments at 16 weeks of age were randomized by weight, individually housed, and assigned to groups . Food and water were made available ad libitum and mice were housed on a 12 hours light/dark cycle. Body weights and food consumption were measured throughout the experiments to monitor animal health . The NASA Ames Research Center and the Brookhaven National Laboratory Institutional Animal Care and Use Committee approved all procedures, and studies were conducted in accordance to the IACUC health and ethical standards. Diets. Diet compositions are shown in Fig. 7. The control diets included the following: Control Diet 1 was LabDiet 5001; Control Diet 2 was purified AIN93G and was used as a control for the AOX-supplemented diet of A. Kennedy and colleagues. Control Diet 3 was AIN93M and served as the control for the DP-supplemented diet. The custom antioxidant diet , was prepared by a commercial vendor based on a previously reported diet composition,plastic flower pots with the base AIN93G diet supplemented with five antioxidants: ascorbic acid , N-acetyl cysteine , L-selenomethionine , dihydrolipoic acid , and vitamin E . All antioxidants were obtained from Sigma .

The DP diet was composed of 25% by weight powdered dried plum and was prepared by Teklad as reported by Halloran et al.40. Analysis of custom diets. The candidate interventions were selected in part on the basis of their antioxidant properties. Antioxidant capacity of the custom diets was measured using a Total Antioxidant Capacity measurement assay. In this assay, levels of Trolox equivalents are positively correlated with antioxidant content. DP and DHLA diets had significantly higher antioxidant capacities compared to their respective controls. Specifically, Control diet 1 contained 0.05mM Trolox equivalent per mg of protein. Control diets 2 and 3, CD2 ; and CD3 had lower TAC compared to CD1, 56% and 41% respectively. Both the antioxidant cocktail and dried DP diets had 84% and 74% increased TAC compared to CD1, and their respective controls at 323% and 196% TAC. The AOX and DP diets had comparable TAC’s . Feeding and injection protocols. Mice were separated into groups and fed various diets or injected with DHLA , Ibuprofen . Mice were pre-fed 7 days , 17 days or 21 days with the diets , AOX or DP prior to total body irradiation . The differences in pre-feeding periods were based on previous published findings showing effective prevention of radio damage by AOX diet or bone loss prevention by DP. Feeding with the corresponding diets was continued until euthanasia. For the injection protocols, DHLA or Ibuprofen was delivered via subcutaneous injection twice a day, starting one day prior to TBI as previously reported. In all experiments, mice were irradiated at 16 weeks of age and tissues harvested 1 day later for the gene expression analysis, and 11 days later for the microCT analysis .Radiation exposure. Conscious mice were exposed at 16 weeks of age to 2 Gy Gamma or with 1 Gy of protons and 56Fe ions delivered sequentially to simulate space radiation. The sequential ion exposure was comprised of an initial exposure to 25cGy of 1 H , then 50cGy of 56Fe , and, finally, 25cGy of 1 H; for a total dose of 1Gy, and was performed at the NASA Space Radiation Laboratory at Brookhaven National Laboratory , NY. This exposure regimen was designed to simulate space radiation combining both low-LET and high-LET particles.

Controls were handled identically to the irradiated animals with the exception of exposure to the radiation source, and are referred to as ‘sham-irradiated’. Gene expression. Flushed bone marrow cells from the femora and tibiae were pelleted and lysed in RLT buffer with 1% beta-mercaptoethanol and stored at −80C. Total RNA was extracted using QIAshredder, and RNeasy mini kit . For each sample, RNA was treated with RNase-free DNase Set . RNA quantity was determined using a spectrophotometer and quality confirmed by 2100 Bioanalyzer . Equal amounts of RNA were reversed transcribed, followed by qPCR using GoTaq® RT-qPCR System . Taqman gene expression assays were used : nuclear factor, erythroid 2-like 2 , receptor activator of nuclear factor kappa-B ligand , osteoprotegerin , tumor necrosis factor alpha and monocyte chemotactic protein-1 . The relative gene expression was quantified using the comparative threshold cycle method with normalization to expression levels of glyceraldehyde 3-phosphate dehydrogenase . The reactions were performed in a 7300 RT-PCR System as described previously. Microcomputed tomography . Tibiae were dissected, cut distal to the TFJ to allow PFA infiltration and fixed for 24 hours at 4 °C, followed by storage in 70% Ethanol. The bones were transferred to phosphate-buffered saline and then the proximal metaphysis scanned and analyzed as previously described with a 6.7 μm/voxel resolution using a SkyScan 1174 microCT scanner . For cancellous bone, a 1.0mm thick region located 0.24mm distal to the proximal growth plate of the tibia was selected and semi-autonomously contoured to include cancellous tissue. To assess cancellous bone loss, the bone volume to total volume fraction , trabecular thickness , trabecular number , and trabecular separation were calculated and reported following conventional guidelines. To measure possible changes in cortical features that contribute to whole bone mechanical properties, bones were scanned at 14.6μm/voxel resolution starting at midshaft 2mm proximal to the tibia–fibula junction over a 0.3mm height. Parameters reported include cortical bone cross-sectional area , bone periosteal perimeter , cortical thickness and mean polar moment of inertia .

Tissue mineral density was calculated using the linear attenuation coefficient and calibrated phantoms for diaphyseal cortical bone. Statistics A one-way or two-way analysis of variance was performed as indicated in the legends, with treatment and irradiation as main effects. Where the main effect P< 0.05 by 1-factor ANOVA, or interaction effects by 2-factor ANOVA, differences between groups were analyzed by Dunnett’s post-hoc test comparing experimental groups to the non-irradiated controls, or all pairs Tukey-Kramer . All data are presented as mean and standard deviations.To be labeled as a fruit juice, the US Food and Drug Administration mandates that a product be 100% fruit juice. For juices reconstituted from concentrate, the label must state that the product is reconstituted from concentrate. Any beverage that is less than 100% fruit juice must list the percentage of the product that is fruit juice, and the beverage must include a descriptive term, such as “drink,” “beverage,”or “cocktail.” In general, juice drinks contain between 10% and 99% juice and added sweeteners, flavors, and sometimes fortifiers, such as vitamin C or calcium. These ingredients must be listed on the label according to Food and Drug Administration regulations.Water is the predominant component of fruit juice. Carbohydrates, including sucrose, fructose, glucose, and sorbitol,plastic garden container are the next most prevalent nutrients in juice. The carbohydrate concentration varies from 11 g % to >16 g % . Human milk and standard infant formulas have a carbohydrate concentration of 7 g %. Juice contains a small amount of protein and minerals. Some juices have naturally occurring high contents of potassium, vitamin A, and vitamin C. In addition, some juices and juice drinks are fortified with vitamin C. Juices fortified with calcium have approximately the same calcium content as milk but lack some other nutrients present in milk, such as magnesium and a substantial amount of protein. Many such calcium-fortified juices also are fortified with vitamin D. The vitamin C and flavonoids in juice may have beneficial long-term health effects, such as decreasing the risk of cancer and heart disease.‍ Drinks that contain ascorbic acid consumed simultaneously with food can increase iron absorption by twofold,which may be important for children who consume diets with low iron bio-availability. Juice contains no fat or cholesterol, and unless the pulp is included, it contains no fiber. The fluoride concentration of juice and juice drinks varies. One study found that fluoride ion concentrations in juice ranged from 0.02 to 2.8 ppm.‍The fluoride content of concentrated juice varies with the fluoride content of the water used to reconstitute the juice. Some manufacturers specifically produce juice for infants. These juices do not contain sulfites or added sugars and are more expensive than regular fruit juice. Other forms of fruit juices are frequently consumed. Up to one third of adolescents consume sport drinks, and approximately 10% to 15% consume energy drinks.Pediatricians should inquire about the use of these products as they assess the nutritional intake of their patients.Juices from many fruit contain flavonoids , which can decrease the activity of several enzymes and transport proteins important in drug disposition.‍

Although the ingestion of grapefruit juice has been shown to reduce the activity of intestinal cytochrome P450 3A4 and produce potential drug-nutrient interactions of drugs that are CYP3A4 substrates , recent evidence suggests that grapefruit juice can also inhibit organic acid transporter activity.In addition to grapefruit juice, flavonoids present in oranges and apples have also been shown to reduce the activity of the organic acid transporter OATP2B1.Although the grapefruit juice–CYP3A4 substrate interaction and the potential for producing significant nutrient-drug interactions is the most well characterized, it should be noted that, in addition to inhibiting CYP3A4 activity, cranberry, pomegranate, and blueberry juice can inhibit the activity of CYP2C a cytochrome P450 isoform that catalyzes the bio-transformation of therapeutic drugs such as ibuprofen, flurbiprofen, warfarin, phenytoin, fluvastatin, and amitriptyline. The clinical significance of any of the aforementioned juice-drug interactions is extremely difficult to predict on the basis of a history of coingestion. Substantial variability in the duration and magnitude of resultant interactions is a function of multiple factors, including the following: constitutive expression of the effected enzyme or transport protein, significant genetic polymorphism in the enzyme or transporter, the relative flavonoid composition and potency among different juices, and the amount of juice ingested and its duration of ingestion .In evaluating the potential juice-drug interactions, the coadministration of fruit juice and a drug for which metabolism or transport could be affected by a flavonoid should not be considered immediately as a contraindication for treatment. The amount and type of juice being ingested,9specific information characterizing a given interaction, and whether the drug being taken has a low or high therapeutic index must be considered in the evaluation of a potential interaction. Consultation between the physician and pharmacist can be beneficial in considering the potential clinical significance of a juice-drug interaction.The 4 major sugars in juice are sucrose, glucose, fructose, and sorbitol. Sucrose is a disaccharide that is hydrolyzed into 2 component monosaccharides, glucose and fructose, by sucrase present in the small bowel epithelium. Glucose is then absorbed rapidly via an active-carrier–mediated process in the brush border of the small bowel. Fructose is absorbed by a facilitated transport mechanism via a carrier but not against a concentration gradient. In addition, fructose may be absorbed by a disaccharidase-related transport system, because the absorption of fructose is more efficient in the presence of glucose, with maximal absorption occurring when fructose and glucose are present in equimolar concentrations.‍Clinical studies have shown this process, with more apparent malabsorption when fructose concentration exceeds that of glucose than when the 2 sugars are present in equal concentrations .‍However, when provided in appropriate amounts , these different juices are absorbed equally as well.Sorbitol, found in small amounts in pears, apples, cherries, apricots, and plums and in sugar-free foods and some liquid medications, is absorbed via passive diffusion at slow rates, resulting in much of the ingested sorbitol being unabsorbed.Carbohydrate that is not absorbed in the small intestine is fermented by bacteria in the colon. This bacterial fermentation results in the production of hydrogen, carbon dioxide, methane, and the shortchain fatty acids acetic, propionic, and butyric. Some of these gases and fatty acids are reabsorbed through the colonic epithelium, and in this way, a portion of the malabsorbed carbohydrate can be scavenged.‍Nonabsorbed carbohydrate presents an osmotic load to the gastrointestinal tract, which causes diarrhea.‍ 19

After treated leaf exposure to intense UV light for 120 min, high levels of mite repellency with the spinetoram treatment dropped in persistence from 10 d to 3 d. Mite mortality after treated leaf exposure to UV light was reduced to control levels on abamectin treated leaves by the time of the day 1 bioassay . Because mites trapped in the felt were excluded, percent mite mortality on spinetoram versus spinetoram-UV treated leaves must be interpreted carefully in Fig. 4-7. Based on data from Fig. 4-3 , Fig. 4-8 depicts a more accurate assessment of the results when mites were placed on UV treated spinetoram leaves because it combines the mortality and repellency . There was no effect of the leaf side treated or leaf side the mites were placed on for both treatments and therefore, data were pooled and the new response variable for each treatment became ‘mites deposited on treated side’ versus ‘mites deposited on untreated side’. There was no significant variation observed between the three leaf replicates on any bioassay date and thus, replicate data were pooled. Based upon repeated measures analysis, each response variable showed significant impacts by day , time and location . With spinetoram treatment, there were more mites alive on the untreated side versus the treated side of the leaf on days 1, 3, 7 and 10 . However, on day 14, there was no difference between the numbers of mites on the treated versus the untreated side of the leaf for any of the observation times. The mites in the control treatment were distributed similarly across both sides of the leaf on all days and times . With spinetoram treatment, mite mortality was different from the control on both the treated and untreated sides of the leaves. On the spinetoram-treated side of the leaf,flower bucket mite mortality by day was significantly different from the control treatment for days one through 10 but on day 14 mite mortality was no longer different .

The same pattern was observed for the untreated side of the spinetoram leaves, i.e. mites were dying at higher levels versus control leaves on both the untreated and treated sides of the leaf. In the control treatment, mite mortality was not different between the water treated and untreated sides of the leaf . Mite repellency on the spinetoram treated and untreated sides of the leaf were different than seen on control leaves . On the spinetoram treated side, mite repellency by day was different from the control for days one and three as well as day 7 and day 10 but not for day 14 . Mite repellency on the spinetoram treated side of the leaf by day for each level of time was not different from the control for times 20 min through 10 hours , but was different for each observation interval from 24 hrs through 5 days . On the spinetoram untreated side of the leaf, mite repellency by day was different from the control for days 1, 3, and 7 as well as day 10 but not for day 14 . Mite repellency on the spinetoram treated side of the leaf by day for each level of time was not different from the control for times 20 min through 10 hours , but was different for observation intervals of 24 hrs through 5 days . In our assessment of the four pesticides currently recommended for avocado thrips management , we found that all four products had some negative effects on E. hibisci. Mite exposure to abamectin resulted in relatively high mortality within the first two weeks of the bioassay and dropped sharply; presumably as translaminar movement of the material took place and the ultraviolet light rays broke down surface residues . Fenpropathrin treatment showed the longest and highest amount of activity. Spinetoram was the only material to which the mites exhibited strong repellency and when mites were bioassayed in the Munger cells with spinetoram, mortality was high and consistent with the pattern observed with the repellency over the first two weeks of the bioassays. Mites exposed to sabadilla, a chemical commonly thought to have little non-target effect , showed higher mortality and longer persistence than expected. However, this could be due to the mites feeding on the pesticide-laced sugar on the leaf surface, as sabadilla is formulated with sugar .

Data clearly showed that exposing the treated, field-weathered leaves to UV light increased the survival of the mites on both abamectin and spinetoram-treated leaves. Mite mortality to the UV-treated abamectin leaves was no different than with control leaves on day one of the bioassay , indicating that surface residual activity had been eliminated. With spinetoram treatment, mite repellency and mortality were reduced from 14 d to 10 d. The chief differences in spinetoram from its analog spinosad are: 1) the addition of the 3’-O-ethyl group, which improves potency by altering nicotinic function in the insect nervous system and 2) hydrogenation of the 5,6 double bond, which improves photostability of the molecule and thereby increases residual control . Our data show that these modifications increased the longevity of the material on the leaf surface but with intense UV exposure, that activity was broken down to some degree. The bioassays evaluating mite detection of spinetoram on the leaf surface clearly showed more mites alive on the untreated side of the leaf than the treated side, indicating that the mites were able to detect the material and move away from it. There were fewer mites drowning in the wet felt in the spinetoram detection bioassay on day one than seen in the initial field trial bioassay on day one, indicating that the pesticide free leaf surface provided some sort of refuge for the mites. Spinetoram exposure at days one and three ultimately resulted in some mite mortality or mites drowned in the wet felt, but there were fewer overall mites dying and drowning on both sides of the leaf . Mite repellency was different from the control for both treated and untreated sides of the leaf, but on each subsequent bioassay date, the level of significance dropped until on day 14, there was no statistical separation. Our data suggest that because fewer mites were repelled in the spinetoram detection trial on bioassay days 7 and 10 and because of the pesticide free side of the leaf, more mites were alive, i.e. fewer picked up a toxic dose or drowned. It remains difficult with our bioassay system to precisely separate whether or not mites received a toxic dose when repellency levels were high.

Our studies were conducted with a conservative dilution rate of 2,843 L of water per ha while the majority of California avocados groves are grown on steep hillsides and utilize helicopter application using 468-935 L of applied water per ha. On these hillside groves, speed sprayers cannot be used and relatively few growers use drag hoses because of the high cost of labor in California. Application by helicopter may not provide complete coverage and many of the interior portions of the avocado tree remain untreated. With consideration of the following factors: helicopter application resulting in uneven distribution of pesticide on hillside avocado groves, the conservative dilution rate used in our trial, our containment of mites on the pesticide treated arenas and providing a pesticide treated/ untreated leaf area, our data suggests that in a field setting, mites may not pick up a toxic dose of spinetoram. Those mites that do not pick up a toxic dose will likely be repelled by the spinetoram and this may result in reduced E. hibisci mortality. Growers should be aware of the data presented herein when deciding upon a pesticide rotation management plan, which reduces avocado thrips resistance evolution. Each of the four recommended products have different features with respect to the efficacy of thrips control,square flower bucket concurrent control of avocado mite pests, and persistence of impacts on predaceous mites and other natural enemies . Citrus thrips, Scirtothrips citri , is a significant insect pest of citrus and mango fruits and has been recognized as a major pest of California citrus since the 1890s . In the USA, citrus thrips are known from Arizona, California, Texas and somewhat recently, possibly Florida , whereas in Mexico they are reported only from northern Mexico . Based on its past distribution, several authors have reported that citrus thrips is native to southwestern North America and northwestern Mexico . Citrus thrips is primarily a pest of citrus in California, particularly in the San Joaquin and Coachella valleys. They can have a broad host range, including, but not limited to, alfalfa, rose, grape, laurel, cotton, date, fir, lucerne and various grasses, pecans, and other ornamentals. Citrus thrips have been collected from over 55 different plant species . Their native host plant is hypothesized to be Quercus or more likely Malosmalaurina Abrams which was likely one of citrus thrips more common native host plants in southern California and northwestern Mexico prior to the introduction of citrus. In the SJV of California, S. citri has recently broadened its known host range and become a significant pest of high-bush blueberries . Scirtothrips citri was not known in Florida until 1986 where it was first detected in grape surveys . A collaborator was aware that in Florida, S. citri is not often collected from or abundant in several crops it is notorious for attacking in other regions of the Americas , but it is the most common thrips species he has collected from native vegetation and weeds. Species identifications from slide-mounted specimens can be unreliable or inconsistent and alternative or additional methods of identification may be necessary. Morphological identification suggests that S. citri is present in California, Arizona and Florida, but given that it is not a pest on several crops one might expect in Florida, further investigation is necessary to determine if S. citri is actually a cryptic species complex. The development of molecular genetic techniques , predominantly analysis of mitochondrial DNA , has significantly contributed to an understanding of natural genetic diversity and speciation . Genetic markers offer additional methods of species determination and delineation, especially when coupled with morphological identifications .

These approaches are especially useful in groups that demonstrate a mixture of diverse ecological traits coupled with a conserved morphology. Given the distribution of S. citri in major citrus growing regions of North America and the level of its pest status in those regions, re-evaluation of morphological and molecular identifications was deemed necessary. The goals of this work were to investigate the haplotypic variation among S. citri populations based on phylogenetic analysis of the mitochondrial and ribosomal DNA, and to identify possible cryptic species complexes within the Scirtothrips attacking citrus. The collection records for all specimens used in this study are listed in Table 1. Specimens were collected from various parts of California, Arizona, Texas, Florida , Mexico, Nicaragua and Turkey. Specimens from Turkey were included in this analysis as it is an under-represented area of the world and at the time of collection from citrus, the collector believed the specimens to be citrus thrips. Specimens were collected into 95% ethanol by beating the live thrips onto a white piece of paper, touching a clean 5/0 Princeton paint brush into the ethanol filled collection vial, touching the ethanol imbibed paint brush tip to the live insect so that the insect stuck to the paint brush tip and then depositing it passively into the collection vial. After collection, all specimens were stored at -20°C until analysis. Some of the collections contained Frankliniella occidentalis and Neohydatothrips burungae but these collected groups were not included in our analysis. Thrips were removed from ethanol and allowed to air dry on filter paper for 2 min. Total DNA was isolated using an EDNA HiSpEx Tissue Kit , following the manufacturer’s protocol. This method is non-destructive, allowing slide mounting and morphological examination of the specimen after extraction. After DNA extraction, two separate gene regions were amplified using PCR: the conserved 28S-D2 domain of the large rRNA subunit and the cytochrome c subunit I of mitochondrial DNA . A ~553-bp section of the 28S-D2 domain was amplified in 25-µl reactions containing 2 µl of DNA template , 2.5 × PCR buffer , 1.0 µl of MgCl2, 5 µM dUTP, 0.5 µM each of the primers CF and CR , 2 µl of bovine serum albumin  and 0.2 µl of Taq polymerase .

A personal communication from a collaborator in Florida supplied the idea to investigate the differences seen in citrus thrips in Florida andCalifornia. In Florida, citrus thrips are the most abundantly collected thrips on weeds but is not an agricultural pest in citrus, blueberries and mangos. However, in California citrus thrips is a pest of many agricultural crops especially the three listed crops. Thus, it seems prudent to determine if there are genetic differences between citrus thrips populations within North American citrus growing regions. Citrus thrips is primarily a pest of citrus in California particularly in the San Joaquin and Coachella valleys. They can have a broad host range, including, but not limited to, alfalfa, rose, grape, laurel, cotton, date, fir, Lucerne and various grasses, pecans and other ornamentals. Citrus thrips have been collected from over 55 different plant species . Their native host plant is hypothesized to be Quercusor more likely Malosma laurina . Scirtothrips citri has broadened its known host range and become a significant pest of a relatively new crop to California, blueberries . Thrips feeding on blueberry during the middle and late portions of the season cause distorted, discolored, and stunted flush growth and poor development of fruiting wood for the subsequent crop . Thrips pressure of this magnitude, coupled with repeated pesticide applications of the few effective and registered pesticides, poses a concern regarding pesticide resistance management. Currently, there are no integrated pest management plans available for control of citrus thrips in blueberry. This is primarily due to the recent nature of this crop-pest association. Historically, low-bush varieties of blueberries could only be grown in regions too cold for citrus production. However, the development of heat-tolerant high-bush varieties, which has enabled the development of a blueberry industry in the San Joaquin Valley , has also caused blueberries to be grown in a region where citrus and citrus thrips flourish. This issue is relevant not only to the blueberry industry,black plastic plant pots bulk but also for the 108,665 hectares of California citrus , which has experienced repeated documented cases of pesticide resistance in citrus thrips populations .

It is also important to note that not all varieties of high-bush blueberries are fed on equally by citrus thrips; i.e. there is a distinct varietal preference for some hybrids with similar parentage . Female avocado thrips lay eggs hidden inside the underside of leaves, in young fruit and stems . The first instar is white to pale yellow while the second instar is larger, more robust, and bright yellow . Avocado thrips larvae are typically found along major veins on the underside of younger leaves and anywhere on the surface of young fruit . Although some pupation occurs on the tree in cracks and in crevices, about threefourths of avocado thrips second instars drop from trees to pupate in the upper layer of dry, un-decomposed leaf litter . Propupae and pupae are rarely seen and they do not feed and move little unless disturbed. Adults are 0.7 mm long and have the typical fringed-tipped wings. Adults are orange-yellow with distinct, thin, brown bands between segments of their abdomen and three small red dots on top of the head . Adult avocado thrips resemble citrus thrips to the untrained eye and to an even lesser degree, western flower thrips, which occur on, but do not damage, avocado and citrus. Avocado thrips develop well under cool, humid temperatures . Populations typically begin increasing in late winter and spring, when avocado thrips feed on young leaves and fruit. Population abundance peaks in late spring and early summer, when most fruit are young and after the growth flush when hardening of leaves induces thrips to move from foliage to feed on young fruit. Populations are suppressed by warm, dry conditions, but this weather usually occurs later in the season, when most fruit are larger and no longer susceptible to damage by thrips. Scirtothrips perseae can have 6 or more generations a year. Egg to adult development occurs in about 20 to 30 days when temperatures average 18 to 24°C . Hoddle reported avocado thrips developmental biology and created a developmental degree-day model listing a developmental threshold of 6.9°C, which to our knowledge is the lowest threshold for any insect species. Monitoring temperatures and using degree-day calculations can predict actual development time.

Foliar feeding is usually unimportant, except when very high populations cause premature leaf drop .Avocado thrips adults can feed on over 11 plant species, however, larvae have only been found on avocados in the field in California suggesting that S. perseae has a restricted host range . Although it has little effect on tree health, avocado thrips feed directly on immature fruit , and obvious feeding scars cause severe downgrading or culling damaged fruit . Moreover, severe scarring when fruit are young can slow and stunt fruit growth. As fruit grow, early feeding by avocado thrips becomes apparent as scabby or leathery brown scars that expand across the skin and is sometimes referred to as “alligator skin” . Avocado thrips damage is affected by practices that increase or decrease the abundance of succulent foliage during set and growth of young fruit. Thrips move to young fruit when leaves harden after the growth flush has finished and the most damage occurs when fruit are 5.1 to 15.2 mm long . Although Hass fruit are susceptible to feeding until they reach about 51 mm in length, thrips feeding rarely causes scars on fruit larger than about 19.1 mm. This scarring on young fruit may not become obvious until fruit enlarge. In severe cases, all fruit on a tree can have their entire fruit surface scarred by avocado thrips, causing some packinghouses to sell such fruit with the box marked “papacado.” The California Avocado Commission estimated a $50 million dollar crop lost in the 2006 due to avocado thrips scarring and the costs of control . Sticky card and beating tray sampling are research methods used for these two insects but are rarely used by growers or pest control advisors . Both PCAs and researchers monitor citrus thrips by counting the percent of fruit infested with immature thrips and the number of immature thrips per fruit is also indicative of the severity of the infestation.

Thresholds in use in the San Joaquin Valley are 20% of Valencia oranges or 10% of navel oranges infested with immature thrips until the fruit reaches 20 mm in diameter or more. Thresholds are halved if Euseius tularensis levels are less than 0.2 per leaf . Avocado thripsare monitored by counting the number of immature thrips per leaf prior to fruit set or the number of thrips per fruit. No firm economic threshold has yet been developed for avocado thrips but PCAs typically treat at 3-5 immature thrips per leaf prior to bloom in San Diego County due to restrictions on use of abamectin during bloom. The major documented citrus thrips predator is the phytoseiid mite, E. tularensis ,procona system although Jones and Morse questioned the importance of this predator. Avocado thrips are frequently preyed upon by Franklinothrips orizabensis Johansen and Chrysoperla carnea and is parasitized by the larval parasitoid Ceranisus menes . Franklinothrips vespiformis , black hunter thrips , and several banded-wing thrips also feed on avocado thrips . In many years, natural enemies are unable to suppress avocado and citrus thrips populations below economic thresholds and chemical control is needed to reduce fruit scarring. By the time damage is noticed on ripening fruit, the thrips that caused the injury are often absent from the fruit. A variety of pesticides are registered for thrips control in different cropping systems . After a number of years of use, pesticides like dimethoate , formetante hydrochloride , cyfluthrin , and fenpropathrin resulted in failures in citrus thrips control in some regions, along with an increase in resistance confirmed with both laboratory and field bioassays. Also, these materials are detrimental to natural enemies such as Aphytis melinus DeBach and other biological control agents important to citruspest control. Since it was registered in 1998, spinosad has been the main material used for control of citrus thrips and a related and more effective material, spinetoram , was registered late in 2007 and will soon replace spinosad once MRL issues are resolved with export countries. Resistance to sabadilla has been shown with avocado thrips and a similar pattern of resistance development with abamectin is of concern due to the persistence of this material in leaf tissue. To date, citrus thrips resistance to spinosad has not been documented but there is concern that resistance to it or spinetoram may appear soon. With a limited number of pesticides available for control and the frequency of resistance shown by thrips such as citrus thrips, it is wise to monitor population levels carefully, limit treatments to population levels of concern, and time treatments optimally . Appropriate cultural practices and conservation of natural enemies should be practiced in concert with the use of pesticides only on an as-needed basis. Thus, the search continues for effective biological and chemical controls useful in citrus and avocado thrips management. For both species of thrips, some pupation occurs on the tree in cracks and in crevices, however, about three-fourths of avocado thrips drop as late second instars from trees to pupate in the upper layer of dry leaf litter . Propupae and pupae are rarely seen, move only if disturbed, and do not feed.

This phenomenon of dropping down to the leaf-litter or soil surface for pupation may create the ideal interface for control using the entomopathogenic fungi B. bassiana. Adding coarse organic mulch beneath trees and maintaining a mulch layer may reduce survival of thrips that drop from trees to pupate below the tree, especially in avocados, because this is common practice by many growers as a method of Phytophthora management. The effectiveness of mulching to control thrips is uncertain and labor costs of adding mulch may not be justified solely for thrips control. However, applying coarse organic material such as composted yard waste beneath trees may help control weeds, and thrips reduction might be an additional benefit, particularly for blueberries. The deep mulch layer that is standard practice with blueberry culture in the San Joaquin Valley may also provide an ideal habitat for B. bassiana. It is possible that as citrus thrips are adapted to and evolved in a hot, dry climate, they may be more susceptible to B. bassiana, whereas avocado thrips has adapted to and evolved in a wet and cool climate and may be less susceptible to or even tolerant to B. bassiana. There is increasing pressure in the United States to move away from broadspectrum insecticides and focus on alternative methods of control, e.g., geneticallymodified crop plants expressing Bt toxins, use of entomopathogens, biorational insecticides. Implementation of such methods on avocado and citrus are difficult due to the relatively primitive methods available for thrips sampling, which are labor intensive and rely on experienced and intuitive pest control advisors. The goal of the workdescribed here is to examine alternatives to traditional insecticides such as Bt proteins and entomopathogenic fungi to control avocado and citrus thrips, with the ultimate target of utilizing entomopathogens to aid in field control, evaluate the insecticides registered for avocado thrips management on the native predaceous mite Euseius hibisci, assess citrus thrips oviposition on blueberry varieties, and determine whether citrus thrips is actually a complex of species. Citrus thrips, Scirtothrips citri , is a plant-feeding pest most widely recognized for the damage it causes to citrus and mango fruits and has been recognized as a major pest of California citrus since the 1890s . Recently, its known host range has broadened and they have become a significant pest of a relatively new crop planted in the San Joaquin Valley of California, high bush blueberries . Citrus thrips feed on blueberry foliage during the middle and late portions of the season causing distorted, discolored, and stunted flush growth and poor development of fruiting wood required to obtain the subsequent crop . High numbers of thrips on blueberries , coupled with repeated pesticide applications of the few effective and registered pesticides, poses a concern regarding pesticide resistance management .

A more recent anonymous Internet-based American survey indicated that 46% of dog owners and 38% of cat owners had fed RMBDs to their pets . Additionally, sales of RMBD have increased annually by as much as 15% in recent years . Over the past decade, this feeding practice has continued to increase, and market locations have expanded to include grocery stores, mass merchandisers, pet specialty stores, and veterinary clinics . A 2019 Italian-based survey shed light on dog owners’ motivations for adopting this feeding method . About 80% of respondents reported that they abandoned feeding commercial diets due to distrust in the clarity of ingredients commercial prescription veterinary diet, veterinarians may acquiesce to such requests. However, the reliability of RMBD for this purpose has not been evaluated. The primary aim of this study was to use PCR to test commercially available RMBD for the presence of DNA of animal origin other than that declared on the labels. A secondary objective was to determine the consistency of DNA presence between different batches of the same diets. The hypothesis was that the diets would contain unlisted protein ingredients, and that these unlisted proteins would vary between batches. To the authors’ knowledge, no previous studies have examined these issues. Nine commercial canine and feline RMBD were selected for analysis. All diets were marketed as balanced for complete feeding. The selected diets included a variety of commonly available North American RMBD, some formulated with novel animal source proteins , or limited ingredients , or grain-free diets which may be potentially selected for use as an elimination diet. The diets evaluated were not specifically marketed for feeding as elimination diets, but contained ingredients which may be considered by pet owners for this feeding purpose. Two lot numbers of RMBD representing separately prepared batches of each diet were selected for analysis in order to assess for consistency of any ingredient contamination between the 2 batches. One canine and one feline veterinary prescription extensively hydrolyzed poultry feather-based diet were used as negative controls. Nine species-specific qPCR assays were designed to detect beef, chicken, duck, turkey, salmon, sheep, rabbit, kangaroo, and pig DNA .

Sequences for each species were found in the National Institute of Biotechnology Information database. Two primers and an internal hydrolysis probe , 3 end, quencher dye NFQMGB were designed using Primer Express Software for all species,30 planter pot with the exception of chicken which used a locked nucleic acid probe . A Basic Local Alignment Search Tool of the amplicons confirmed unique species detection. To ensure these assays did not cross-react with DNA of other species, a crossreactivity evaluation was performed by running all assays with control DNA from each species . A housekeeping gene, eukaryotic 18S assay , was run with each sample to confirm successful DNA extraction. All assays were validated for efficiency and sensitivity by running 10-fold standard curves in triplicate from serial dilutions of control DNA. Each assay was 90% to 100% efficient and sensitive enough to detect as few as 10 copies of the target gene. Of the 9 species of animal DNA tested, 8 species, including pork, chicken, duck, rabbit, lamb, beef, salmon, and turkey, were detected in at least 1 sample of the canine and feline RMBD tested. Only kangaroo DNA was not detected in any of the RMBD. The 2 extensively hydrolyzed poultry feather-protein based diets contained either trace amounts of chicken DNA or no detectable DNA . In the canine RMBD, DNA of 1 or more animal species not indicated on the label was identified in 9 out of 9 diets, in either 1 or both of the tested batches . Of the 18 batches tested, 89% tested positive for unlisted animal-source DNA. An average of 4.4 unlisted proteins was detected in each diet. A total of 2 batches were found to contain DNA consistent with the stated label ingredients. The diet with the greatest number of unlisted proteins was a single batch , labeled as containing turkey and sardine. It contained a total of 6 unlisted proteins . The unlisted DNA most frequently detected was lamb . Discrepancy in the unlisted DNA between batches was noted in 78% of batches. In the feline RMBD, DNA of 1 or more animal species not indicated on the label was identified in 7 of 9 diets, in either 1 or both of the tested batches . Of the 18 batches tested, 61% were positive for unlisted animal-source DNA. An average of 2.6 unlisted proteins was detected in each diet. A total of 7 batches were found to contain DNA consistent with the stated label ingredients. The diet with the highest number of unlisted proteins was a single batch , labeled as containing chicken and salmon. It contained 5 unlisted proteins .

The unlisted DNA most frequently detected was turkey . Discrepancy between batches was noted in 56% of batches. All of the canine and feline RMBD included in the analysis were found to contain the proteins listed on their labels. Contamination of one or both batches in all canine RMBD and most of the feline RMBD tested was detected in this study, which supports the hypothesis that cross-contamination would be found in many RMBD. Numerous independent studies have also demonstrated significant discrepancies between label claims and actual contents of dry or canned over-the-counter commercial diets, including those marketed for the management of CAFR . While this finding may have been expected in RMBD due to the prevalence of unlisted DNA detected in other such studies, diet purity could theoretically have been improved in RMBD as they are purported to undergo less processing before distribution, allowing less opportunity for protein contamination. An additional finding of this study was that unlisted animal source proteins varied among batches in most batches tested, including both canine and feline RMBD that were analyzed. Discrepancy among batches has not been previously studied for comparison, but these results showed that differences in unlisted ingredients were common in RMBD. Due to cost limitations restricting the analysis to only 2 batches of each RMBD, a statistically significant batch contamination rate could not be determined. However, the finding of discrepancy among batches represents yet another variable which could impact interpretation of an ED trial in a patient fed a commercially prepared RMBD. While no particular manufacturer’s diets were found to be more likely to contain unlisted proteins, brand F, the producer of feline diets 7 to 9, had the least number of contaminants, as well as the most consistent agreement between each batch. It is possible that this finding is due to the nature of the processing practices of this particular manufacturer, the production of smaller batch sizes to minimize opportunity for contamination, or more limited sourcing of ingredients to restrict the potential for supplier cross-contamination. Overall, the number of animal protein ingredients included in each diet was not a predictor of the number of unlisted proteins isolated in the analysis. Even diets restricted to single proteins were as likely to contain 1 or more sources of unlisted animal DNA as those with multiple animal proteins and batch contamination was unpredictable.

Previous studies have shown that in rare cases,plastic growers pots ingredients listed on product packaging were found to be missing from the analysis . Our study showed that no animal DNA was missing from that declared on the packaging of any RMBD included in the analysis. Due to the target DNA of the qPCR assay, the study was unable to validate the presence of sardine or goose to confirm the inclusion of these ingredients. This was again due to cost limitations precluding the addition of these proteins in the analysis. Some diets also contained animal fat sources such as salmon oil, cod oil, or sardine oil. Through purification processes, fish oils undergo refinement to remove proteins from the oil to render them free of proteins . While cod and sardine were not included in the analysis, our study did evaluate for salmon DNA. Both canine diets 1 and 3 contained salmon oil and tested negative for salmon DNA. Feline diet 5 contained salmon oil, but also contained salmon meat, and tested positive for salmon DNA as would be expected. If extrapolating from the finding that salmon DNA was not found in the diets containing salmon oil, it may be expected that the other diets containing fish sources of oil did not contain cod or sardine DNA as potential allergens. In general, plant- and animal-based oils are not considered allergenic when highly purified . Of additional note was the finding that no diet contained the DNA of kangaroo. Since kangaroo meat is not used by any of the manufacturers in their RMBD, this finding serves as an additional negative control for this study to validate that no DNA of kangaroo origin was detected in the analysis, as would be expected. Analysis of the 2 extensively hydrolyzed poultry featherbased diets revealed no detection of unlisted animal DNA. This is consistent with previous reports that contaminants are detected less commonly and in lower numbers in hydrolyzed diets . The extensive hydrolysis of poultry feather proteins into component amino acids or very short oligopeptides is intended to avoid inducing IgE-mediated mast cell activation that can occur with proteins 10 kDa in size or greater . Extensive hydrolysis to reduce poultry allergenicity has been validated in both serum IgE and feeding trials to show the clinical benefits for CAFR . These negative control diets were selected because of the rigorous quality control methods undertaken by the manufacturer to ensure cross-contamination does not occur before market release . While the canine diet did test positive for chicken DNA, the manufacturer does list the feathers of chicken, turkey, and duck as their sourced raw materials . The target gene of the analysis for chicken DNA, transforming growth factor beta 3, is a protein expressed in chicken feathers . Additionally, the manufacturer is aware that cross-contamination needs to be avoided in a therapeutic diet and has developed and clinically validated calibration curves to prevent contamination . These calibration curves correspond to a known DNA level that was clinically tolerated based on Global Skin Scores in feeding trials in order to set a tolerance level for ancillary proteins known as the NPPI , which is strictly monitored in each diet prior to allowing market release . Based on the manufacturer’s quality control data, 72.3% of these extensively hydrolyzed diets contain DNA below the limit of detection , and 25.7% may have DNA above the LOD but below a safety threshold of 1.2 g/g . However, no diet released to market will exceed the established cut-offs of the NPPI based on the pre-established calibration curves . Therefore, trace copies of chicken DNA may be expected on PCR in some of the diets released to market, as was found in our study. The DNA in the feline extensively hydrolyzed diet in this study was below the LOD, and no animal DNA was detected in the assay. Based on the sensitivity of qPCR, it can be argued that these assays, being sensitive enough to detect as few as 10 copies of the target gene, are of greater sensitivity than that required to detect clinically meaningful contamination that would trigger CAFR. There is no established maximum tolerable level of a contaminating protein that may elicit a pruritic reaction in a food sensitized pet. In humans, soy protein concentration as low as 10 ppm may evoke a reaction in a soy-sensitized individual . Additionally, dose distribution has been demonstrated to vary between different food allergens in sensitized humans, showing that a tolerance range may exist for different food antigens themselves . The additional concern for CAFR pets is that, as opposed to most humans, pets are often fed a specific commercial diet with daily regularity, increasing their risk of chronic re-exposure to a food antigen contained therein. As a result, even small amounts of unknown allergens may lead to a cumulative reaction in a CAFR-affected pet and skew the clinical impression of their response to a particular ED. These reactions may even be sporadic if there is significant variation of the protein constituents of the diet between batches. The need to validate food allergic threshold distributions in canine and feline CAFR is an important area for future research.

The IHR and intermediate types together were considered to define the “recombinant” group of X. fastidiosa subsp. multiplex isolates . Most were observed more than once, and 5 were found in two different U.S. states or districts . The analysis of Nunney et al. was focused on the evolution and host range ofX. fastidiosa subsp. multiplex. For this purpose, it was necessary to identify and exclude isolates whose recent evolution was influenced by inter sub-specific recombination. As such, once the 23 non-IHR STswere identified, there was no further analysis of the remaining recombinant group STs. In particular, no evidence was presented for classifying some alleles as atypical of X. fastidiosa subsp. multiplex beyond the observation that they were never found in the non-IHR group . Nunney et al. did observe one intriguing pattern when they compared their results to those of Parker et al. . Of the 143 isolates, 13 were also used in the study by Parker et al. , in which typing was based on a different set of 9 loci. Unexpectedly, these 13 isolates maintained the same grouping with the IHR and non-IHR types corresponding, respectively, to the clade A and clade B groupings . This highly statistically significant concordance strongly suggested that IHR is not distributed randomly across all X. fastidiosa subsp. multiplex isolates but instead is restricted to a small subset, while the remainder is little influenced by IHR. However, Parker et al. failed to find evidence of inter sub-specific recombination within any of the X. fastidiosa subsp. multiplex isolates, despite applying a series of 9 tests designed to detect recombination contained within the RDP4 program and the PHI program . This result presented a strong argument against our hypothesis that clade A members cluster because they are recombinant types carrying alleles derived from IHR . Here we reexamined the sequence data obtained in their study by using the more sensitive introgression test to determine if their tests missed evidence of IHR and, if so, whether it was confined to clade A.

In particular,plastic planters bulk what could be concluded about the origin of the group given the observation from 2 independent studies that the members appear to form a well-defined cluster of genotypes? Third, we used the sequence data to examine the hypothesis that the introgressed DNA was from X. fastidiosa subsp. fastidiosa, the subspecies that causes Pierce’s disease. X. fastidiosa subsp. fastidiosa is native to Central America, and all known isolates in the United States and northern Mexico can be traced back to a single introduced genotype . IHR would be of limited interest if it simply randomized the genetic differences among the subspecies but had a minimal effect on pathogenesis. For this reason, we were particularly interested in documenting any possible invasion of new plant hosts associated with IHR. The hypothesis is that IHR creates a range of novel genotypes that are far more variable than can arise from a lineage diversifying through point mutations, and this diversity facilitates adaptive evolution of a kind not possible for a clonal lineage. This kind of probabilistic evolutionary hypothesis can rarely be directly proven based on an individual case; however, it makes predictions that, if generally supported, would cause the hypothesis to be accepted. In the case of X. fastidiosa, compelling evidence supporting the hypothesis would be the invasion of a new native host plant that is uniquely associated with IHR. Our data support this hypothesis: in X. fastidiosa subsp. multiplex, IHR is indeed associated with the invasion of at least 2 new native plant hosts, blueberry and blackberry.To investigate inter sub-specific homologous recombination , we analyzed 31 isolates previously identified as IHR-type and 2 isolates previously identified as intermediate-type X. fastidiosa subsp. multiplex , based on sequence of the 7 housekeeping loci used in the MLST scheme defined by Yuan et al. plus a region of the pilUgene. Together, these 33 isolates made up the recombinant group. Details regarding the isolation and typing of the 33 isolates were provided by Nunney et al. , and a summary of salient features is provided in Table S1 in the supplemental material in that article. All sequences used have previously been published and are available both in GenBank and the MLST website . To detect IHR, we employed a modified version of the introgression test developed by Nunney et al. .

In its original form, the test compares a set of target sequences, some of which may have been involved in IHR, to a set of potential donor sequences. Each variable site is classified as F, a fixed difference between the target sequences and the donor sequences, or P, a polymorphic site within the target sequences where at least one variant base is shared with the donor set. A significant shift in the ratio of F to P marks a recombination break point. In the modified version of the test, the targeted introgression test, the target sequence is known a prioriand is compared to two references, the donor group, D , and the ancestral group, A . The minimum number of nucleotide differences between the target and the two references defines a ratio of D to A equivalent to the ratio of F to P and can be tested in the same way . In some cases, there is no break point because the whole locus appears to be an introgressed sequence . Although the signal of introgression across the entire sequenced region may be clear, it is valuable to have a statistical test that documents the strength of the signal. In this case, the null expectation is the ratio that reflects the pairwise differences between the donor and ancestral group versus the pairwise differences within the ancestral group . We used this ratio to define the expectation of the D/A ratio for a chi-square test of complete introgression. Gene diversity and distance trees were calculated using MEGA5 , and the maximum parsimony tree was created using the PARS program in Phylip . Distance trees and the maximum parsimony tree were used rather than other methods, given the known occurrence of inter sub-specific recombination in the data. Clonal Frame was used to provide an independent estimate of the relative importance of recombination versus mutation in the recombinant group.Analysis of the recombinant group ofX. fastidiosa subsp. multiplex showed three important results. First, inter sub-specific recombination was shown to have occurred in 50% of 8 loci scattered throughout the genome that were chosen independently of the data . Second, it was shown that the donor of the introgressed sequence was X. fastidiosa subsp. fastidiosa, a subspecies introduced from Central America into the United States as a single strain .

However,collection pot the introgressed sequence at two of the loci did not come from any of the X. fastidiosa subsp. fastidiosa genotypes that have been found in the United States. This result suggests that another introduction of X. fastidiosa subsp. fastidiosa must have occurred, an introduction that resulted in successful IHR, after which the donor genotype seems to have disappeared. This involvement of an unexpected X. fastidiosa subsp. fastidiosa strain supports the hypothesis that the members of the recombinant group share a single ancestral IHR event. Third, the hypothesis that IHR has facilitated a shift to new hosts is strongly supported by the example of blueberry, where 10 isolates have been typed and potentially supported by the example of blackberry . A link between the shift to a novel plant host and homologous recombination has not been previously identified. Of course, the direct causation of this link can never be proved without knowledge of the genetic changes driving this shift. It can always be argued that the link is fortuitous and that one or more point mutations in the nonrecombined X. fastidiosa subsp. multiplex genome are causal in the host shift. Arguing against this possibility are 2 additional pieces of information. First, both blueberry and blackberry are native to the United States, so if only a simple genetic change was required to infect these species, why did the native nonrecombinant X. fastidiosa subsp. multiplex apparently never acquire these changes? Second, a similar but even more extensive mixing of the genomes of X. fastidiosa subspp. fastidiosa and multiplex is found in the only form of X. fastidiosa that infects another U.S. native plant, mulberry . Furthermore, in other bacterial species, it has been demonstrated that recombination can drive rapid evolution, both in the laboratory and, in the case of Helicobacter pylori, in mice . Similarly, McCarthy et al. concluded that lineages of Campylobacter jejuni in chickens versus cattle and sheep were able to shift host type, because rapid adaptation was facilitated by recombination with the resident host population. In the study by Nunney et al. , it was shown that the recombinant genotypes formed a well-defined group , demonstrating that inter sub-specific homologous recombination was not randomly distributed across the X. fastidiosa subsp. multiplex isolates. This work was based on a survey of 143X. fastidiosa subsp. multiplex isolates using just 8 loci. There were 33 isolates that showed some evidence of IHR in at least 1 locus: all but 2 showed statistically significant evidence in at least 2 loci, while the remaining 110 showed no such evidence . The generality of this discrete group of recombinant forms was supported by our analysis presented here of the sequence data from 9 more loci sequenced by Parker et al. . These loci divided isolates into 2 groups that appeared to correspond to the recombinant and non-IHR groups, respectively , even though Parker et al. found no evidence of IHR. Upon reanalysis, we found statistically significant IHR in 6 of the 9 loci in the clade A data but no evidence of IHR in the clade B data. Clade A included 6 isolates that we had typed in the present study, and each of these showed evidence of IHR in 4 or 5 of the additional 9 loci. Thus, in two independent samplings that together examined 17 loci, there was clear evidence of substantial genome wide IHR in the recombinant group isolates, amounting to 50% of the genes showing IHR across the MLST locis plus the pilU locus .

The average was higher when based on the loci sequenced by Parker et al. ; however, this was probably biased upwards by the manner in which the loci were chosen . None of the IHR events in 6 of the 9 loci identified using the targeted introgression test, or in the case of complete introgression, a chi-square test, were detected by Parker et al. using PHI and the 9 tests implemented in RDP . This failure of the standard tests of recombination to detect IHR was previously noted by Nunney et al. , motivating the development of their introgression test. We examined the hypothesis that the recombinant group STs were derived from a single IHR event involving a X. fastidiosa subsp. multiplex recipient and an X. fastidiosa subsp. fastidiosa donor. The distribution of allelic differences among the recombinant STs was consistent with them all being derived from a single initial event, but a small number of other inter sub-specific and intrasubspecific recombination events would also be needed . More importantly, the genotypes seen in the recombinant group can be accounted for entirely, or very nearly so, based on a single X. fastidiosa subsp. fastidiosa donor genotype. For example, the substantial variation in cysGcan all be accounted for by an ancestral introgression of X. fastidiosa subsp. fastidiosa allele 12 followed by subsequent intrasubspecific recombination of X. fastidiosa subsp. multiplex sequence to form the other two alleles . In contrast, variation at pilU could be accounted for by a second donor contributing the X. fastidiosa subsp. fastidiosa pilU9 allele, but it could also have arisen by a single mutation in pilU1 unique to the recombinant group. A possible single X. fastidiosa subsp. multiplex recipient genotype was also identified . This genotype is consistent with a known ST: setting cysG to allele 3 makes the recipient identical to ST45, which was sampled from the states of California, Kentucky, and Texas . Elsewhere, we consider a slightly different hypothesis regarding the origin of the recombinant group in which the donor and recipient subspecies are reversed—i.e., that it was derived from a single IHR event, but involving an X. fastidiosa subsp. multiplex donor and an X. fastidiosa subsp. fastidiosa recipient; however, apart from the role reversal, the conclusions are unaltered .

Further compounding these labor-utilization issues, growers must offer a higher piecerate when productivity is low in order to retain their labor force and increased variability in available yield for harvest makes it more difficult for managers to allocate labor appropriately. The market for raspberry pickers is highly competitive. Workers who believe they can earn more money elsewhere, because less fruit is damaged, may leave during a harvest or not return for a subsequent harvest. The potential resulting labor shortage in fields with significant SWD damage could further exacerbate fruit losses due to SWD as unharvested fruit become overripe and act as a SWD breeding ground. Further, agricultural labor costs are also rising over time as the supply of labor from Mexico is shrinking due to improving economic conditions. It is difficult to observe these increased labor costs directly, but it is clear that they are not negligible. In 2015, a tray of 12 six ounce clam shells of conventional raspberries sold at an average price of $15.98 per tray based on Salinas-Watsonville and Oxnard district shipping point prices. According to a 2012 UC Davis study of raspberry production costs and returns, production costs were estimated to be $10 per tray of raspberries. Labor costs accounted for approximately half of these production costs, and the study did not report any SWD-targeting activities. The piece-rate alone averaged $4 per tray in a season.If one were to assume, conservatively, that these additional labor costs associated with managing SWD increased total labor costs by as little as 2% and 4% for conventional and organic raspberry producers, respectively, then these activities would account for a 1% and 2% increase in total production costs. Thus, a 1% increase is production costs would reduce a conventional raspberry grower’s profit margin by approximately 1.67%.

If a similar cost structure is assumed for organic raspberry producers,blueberry containers then one would expect approximately a 3.34% reduction in profit margin resulting from the additional labor costs associated with managing SWD. Labor costs are assumed to increase by a greater percentage for organic producers because they are more reliant on labor-intensive SWD control methods.We examined revenue losses and management costs associated with this invasive pest. Using a combination of field trial data and expert observations, we calculated that SWD has accounted for approximately $39.8 million in revenue losses, equivalent to 2.19% of realized revenues, for the California raspberry industry between 2009 and 2014. Conventional producers accounted for $36.4 million of these losses, equivalent to 2.07% of their realized revenues. Organic producers accounted for $3.43 million of these losses, equivalent to 5.74% of their realized revenues. SWD management activities have also significantly increased production costs for raspberry growers. We calculated that the cost of chemical purchases increased annual per hectare production costs for conventional and organic producers by $1,161.28 and $2,933.01, respectively. We also calculated that the cost of labor-intensive SWD management activities decreased conventional and organic raspberry producers’ profits by 1.67% and 3.34%, respectively. Even though the industry has managed to adapt to the pest, these revenue losses and management costs have significantly reduced the profitability of the commercial production of fresh raspberries. Looking into the future, it is unclear whether SWD will remain a threat to California’s raspberry producers. On one hand, the primary biological reason that SWD has become such an economically damaging pest in both North America and Europe following its invasion is the absence of an effective natural enemy. In Asia, where SWD originates, the presence of effective natural enemies greatly reduces damages associated with the pest. Thus, the introduction of an effective biological control agent could dramatically reduce these estimated losses in the future. On the other hand, California’s raspberry producers rely heavily on chemical management options to reduce yield losses associated with SWD infestations.

If SWD populations were to develop significant resistance to these chemicals over time or restrictions were placed on their use, then these estimated losses could increase dramatically. sitive to N fixation, moss accumulation, organic layer depth, soil drainage, and fire severity. Finally, there are several comprehensive studies of post-fire succession in Central and Eastern Canada , but the trees in these sites inhabit different soil drainage and temperature regimes than their Alaskan relatives, potentially resulting in different rates of ecosystem C dynamics . The goals of this study were to describe the changes in community structure and above ground net primary productivity and biomass that occur over post-fire succession in the upland black spruce forests of Interior Alaska. We present measurements that span two different time scales: recovery 1–4 years after fire and recovery over the entire successional cycle. For the former, we followed vegetation recovery for 4 years after the 1999 Donnelly Flats fire near Delta Junction, Alaska. We used a chronosequence approach for the latter by selecting two sequences of sites in the region that varied primarily in time since fire: a mesic sequence on moderately well-drained soil with permafrost and a dry sequence located on well-drained soils without permafrost . These sequences represent transitions in environmental factors that might occur with climate warming, including loss of permafrost and subsequent increases in soil drainage .This study was conducted in the Donnelly Flats area located near Delta Junction in Interior Alaska, in seven upland sites that were previously dominated by black spruce . All sites were located within a 100-km2 area on gently sloped alluvial flats that range from moderately well-drained soils dominated by permafrost to well-drained soils where permafrost was largely absent. Soil drainage was based on depth to water table and hydraulic conductivity . Our study include three sites on well-drained soils that burned in stand-killing wildfires in 1999, 1987, and approximately 1921 , hereafter the dry chronosequence, and four sites on moderately well-drained soils that burned in 1999, 1994, 1956, and approximately 1886 , hereafter the mesic chronosequence.

Time since last fire was determined by historical record in the younger sites and by tree ring analyses in the older sites. Some or all of these sites have been used to assess the effects of fire on soil C storage and emissions , soil chemistry , hydrogen fluxes , fungal community composition and dynamics , seasonal CO2 and 18O–CO2 fluxes and energy exchange . Within each chronosequence, sites were chosen to have similar state factors other than time . Approximately 65% of precipitation fell during June, July, and August. Potential biota: Although all stands were currently or historically dominated by black spruce and were in a close enough proximity that they belong to the same regional pool of potentially colonizing organisms, the under story vegetation and ground cover varied with soil drainage and stand age . The oldest dry stand was a lichen woodland , with ground cover dominance split between feather moss and lichens. Vaccinium uliginosum and V. vitis-idaea were the most abundant under story species, with deciduous shrubs and trees, forbs and graminoids present but at low abundance. Many of the same species resprouted or recruited after fire in the 1999 dry site and dominated the understory in the 1987 dry site. Species characteristic of well-drained ecosystems that were present in all dry chronosequence sites and absent from the mesic sites were the grass Festuca altaica and the evergreen shrub Arctostaphylos uva-ursi. These species were present, however,best indoor plant pots on trails and roadsides around the mesic sites. The oldest mesic stand had continuous feathermoss ground cover and a high abundance of Vaccinium spp. Feathermoss occupied almost the entire ground surface in the 1956 and 1886 mesic sites. In the 1994 mesic site it persisted in patches that appeared to have escaped burning. Vascular nomenclature follows Hulte´n and non-vascular nomenclature follows Vitt and others . Relief: Sites in both chronosequences were within a 100- km2 area with little variation in slope or topography . Parent material: Soils along both chronosequences were mainly derived from the Donnelly moraine and wind blown loess and have been described in detail elsewhere . Differences in drainage between the chronosequences are thought to be related to differences in water table depth and texture . Although great care was taken to control state factors within and between chronosequences, it was difficult to fully constrain the effects of past fires on productivity or biomass pools. In the 1999, 1994, and 1987 sites, fires were stand replacing . In the 1957 mesic site, the relatively small range of tree sizes suggests a single cohort of black spruce. In the mature 1886 mesic and 1921 dry sites where tree sizes are quite variable, however, the number of trees sampled for age was not large enough to determine whether stands are comprised of a single cohort . At the landscape-scale, the severity and frequency of fire are likely to be related to soil drainage . At the site level, however, stochastic factors such as weather conditions, time since last fire, and neighboring vegetation can also affect fire severity.

Post-fire vegetation recovery is similarly affected by stochastic processes such as timing of fire in relation to both vegetative and reproductive phenology, proximity of seed source, and/or the effects of past and present climate conditions on demographic processes. Finally, we caution the reader to keep in mind at all times that this is an observational study; we depend on the assumptions of the chronosequence approach to make inferences about time.We used a combination of inventory and allometric methods to estimate above ground live tree biomass and production in the sites with trees greater than 1.37 m in height, including the 1987 and 1921 dry sites, and the 1956 and 1886 mesic sites. Sixteen 100 m2 plots were established in the dry sites in four blocks with greater than 100 m between blocks, and six 100 m2 plots were established at greater than 100 m from each other in the 120- year-old mesic site . The diameter at breast height was measured on all trees in these plots. In the 1956 mesic site, tree density and DBH were estimated with a modified point-centerquarter method . When applied in the same site , these methods produced statistically indistinguishable estimates of tree density . Site-specific allometric equations were developed for black spruce in the 1921 dry site and in the 1956 and 1886 mesic sites. An aspen equation was developed for the 1987 dry site; it was also used to estimate aspen biomass in the 1956 mesic site, where aspen comprised 26% of the total basal area. In each site, 10–13 trees were selected in a semi-random manner, where initial selection was stratified to span 90% of the stand DBH range as determined by the inventories described above. All trees were harvested in August 2001. Diameter at breast height, basal diameter at moss level, and height were measured. Each tree was felled at ground level, returned to the lab and separated into dead material, stem, coarse old branches , fine old branches , cones, dead branches, old leaves, and the current year‘s leaves and stems. Aspen were separated into dead material, stem, old branches, and the current year‘s branches and leaves. These components were weighed wet and chopped into small pieces. Sub-samples were weighed, dried at 60 C until they reached a constant mass and reweighed to determine dry weight ratio. For each site, the best-fit linear equation relating the square of DBH to each biomass pool 2 except for old leaves, which was best fit by ln DBH. In all cases, DBH2 or lnDBH was a better predictor of biomass than was a DBHb . Data were log transformed if necessary to meet the assumptions of linear regression. All allometry regression analyses were carried out with Systat version 10.2 . Allometric equations were combined with plot-level inventory data to estimate biomass on a per unit area basis. Approximately 10% of the trees greater than 1.37 m in height at each site were smaller than the minimum DBH included in our equations and for these trees, we used regression equations forced through the origin . To estimate annual diameter increment increase, we analyzed tree ring width on a subset of allometry trees from each site with a microscope and micrometer.

Additional pre-registered experiments showed that subjects’ querying behavior was no more optimal – or less similaritydriven – in our active learning task than a traditional semantic search task , and no more optimal or less similarity driven when directly told to query more optimally by querying dissimilar items , suggesting that memory based active learning is at the mercy of extremely stubborn memory constraints, which are difficult to alleviate by task instructions. A final experiment showed that subjects can distinguish between the more and less optimal query sets, suggesting that subjects understand what optimality entails, but that memory constraints make the spontaneous generation of optimal queries from memory difficult. Our results stand in stark contrast with the large body of work that finds optimal search in active learning. The theory that people acquire information optimally has been very successful in explaining human inquiry in several domains. However, most prior studies use fairly simple, artificial stimuli, and do not require subjects to generate queries from memory. We thus suggest that the scope of the optimality hypothesis in explaining human active learning may be more limited than previously thought. Indeed, we suspect that any setting in which subjects must formulate sequences of queries in natural language will probably be constrained by memory processes, particularly the similarity-driven associative memory search. Although associative memory processes curtail optimal active learning, that does not mean that people’s memory processes are inherently flawed. Rather, memory serves multiple cognitive functions and the associative biases documented in this paper may reflect optimal trade offs between diverging task demands. Indeed, many researchers have argued that association or similarity-driven memory search is part of an optimal system for semantic memory retrieval . Related work has shown that associative memory processes implicated in judgment and decision biases are adaptive in that they often lead to accurate inference and generalization with minimal cognitive cost . Regulating these processes in active learning tasks may be too effortful,blueberries in pots and people may be optimally trading off performance with the cognitive cost required to succeed in our task .

This theory predicts that even though we were unable to reduce semantic congruence and increase optimal search through coaching, performance may improve with higher incentives or practice. Testing these predictions is an important topic for future work. Other future directions include the refinement of our memory and learning models. For example, subjects in our study learned about novel target properties. Yet they came into the experiments with idiosyncratic knowledge about food items or animals. Thus, it is likely they held different prior belief about the novel target properties. Since prior belief is not the focus of this paper, we assumed all subjects held the same prior belief in the experiments. In future work, the shape of prior belief can be set as free parameters and the same framework can be used to derive the prior representation of target properties in a given domain. Individual differences in this regard can be revealed. The Bayesian learning model also assumes that subjects maintain a distribution of belief over multiple hypotheses . However, other research suggests that in a closely related – and not even as complex – active category learning setting, subjects maintain a single hypothesis at a time . Previous research also reveals other simple heuristics, such as the split-half heuristic and the likelihood difference heuristic , in active learning tasks. It is possible that such heuristics play a role in the query search in our active learning tasks and, therefore, can be considered in the modeling of algorithmic processes in future research. Our work contributes to the emerging body of research that offers researchers a naturalistic search domain to study active learning. Additionally, our computational models integrate insights from several fields, and are able to jointly describe both algorithmic memory search processes as well as the optimality or suboptimality of these search processes for active learning. In this way, our paper presents a powerful new research paradigm for naturalistic active learning. There has been an increasing interest in porting computational cognitive models beyond abstract lab stimuli, to attempt to describe everyday cognition. This has been driven by the availability of new machine learning models that offer quantitative representations for natural entities , as well as the growing demand from policy makers and practitioners for theory-driven behavioral and cognitive insights.

Our research is part of this trend, and we look forward to future work that applies established algorithmic and rational theories of cognition to rich stimuli sets to better understand human cognition and behavior in the wild. The slowdown in unauthorized Mexico–U.S. migration has set off a race in U.S. agriculture between rising imports, more machines, and foreign guest workers. Trade policy, including North American Free Trade Agreement re-negotiations, and immigration policy, including more enforcement and new or revised guest worker programs, will determine the winner. Fewer and larger farms that depend on hired workers produce most U.S. fruits, vegetables, and horticultural crops such as nursery plants. The number of farms in the United States is stable at about 2 million, but the largest 10% of all farms account for three fourths of U.S. farm sales. In fresh vegetables, the largest 10 producers account for more than half of the lettuce, broccoli and carrots produced. Americans do not dream of growing up to be farm workers. About 70% of the hired workers on U.S. crop farms were born in Mexico, and 70% of these Mexican born workers are unauthorized, so half of crop workers are working illegally. California has a higher share of unauthorized workers because more of its workers were born in Mexico, 90% versus less than 70% in other states. Crop workers are aging and settling. Most have families that include children born in the United States, and few are migrants who follow the crop harvests from south to north. Unauthorized newcomers, who are primarily Mexican-born workers in the United States less than a year, have been the flexible fresh blood of the farm workforce, willing to move to fill vacant jobs. Their share of crop workers peaked at a quarter in 2000, but today such newcomers represent just 1% of crop workers. Farmers are responding to the end of large-scale Mexico–United States migration and California’s rising minimum wage with four strategies: satisfy current workers to retain them, stretch them with mechanical aids that increase their productivity, substitute machines for workers, and supplement current workers with H-2A guest workers. Seasonal farm work is generally a decade-long job rather than a lifetime career. Training first-level supervisors to reduce favoritism and harassment, paying bonuses to workers who stay through the season, and offering other benefits helps to satisfy current workers and keep them in farm work longer.

Stretching farm workers involves management changes and mechanical aids that increase productivity. Most fresh fruits and vegetables are over 90% water, and workers spend much of their time carrying harvested produce down ladders to bins or to the end of rows to receive credit for their work. Dwarf trees mean fewer ladders and faster picking, reducing the need to fill 50- to 60-pound bags of apples and oranges from tall ladders. Slow-moving conveyor belts that travel ahead of workers in the fields reduce the need to carry harvested produce, increasing worker productivity and making jobs more attractive to older workers and women. Substitution is replacing workers with machines. There are machines available to handle most tasks done by farm workers, but human hands are gentler than mechanical fingers on fragile fresh fruits and vegetables, so that a higher share of hand-harvested produce can be sent to consumers. Machines have other disadvantages as well. They are fixed costs, meaning that farmers must pay for, say, a $200,000 harvesting machine whether there are apples to pick or not, while workers are variable costs who are not paid if storms or disease destroy the apple crop. Nonetheless, rising minimum wages, fewer flexible newcomers,square plant pots and advances in mechanization have encouraged many farmers to experiment with machines, prompting manufacturers to develop and market labor-saving machines that are doing more planting and pruning and are improving rapidly to harvest blueberries, peaches and leaf lettuces. The fourth option is to recruit guest workers under the federal H-2A program, which admits an unlimited number of foreign farm workers to fill seasonal jobs. Receiving permission to hire H-2A guest workers requires farmers to try and fail to recruit U.S.-born workers, provide free housing, and pay an Adverse Effect Wage Rate , which is $13.18 an hour in California in 2018. The number of U.S. farm jobs certified to be filled by H-2A workers tripled over the past decade to 200,000 in fiscal year 2017 and may surpass the peak number of Braceros by 2025 . The number of jobs certified to be filled by H-2A workers in California tripled in 5 years, from 3,000 in 2012 to 15,000 in 2017, and appears poised to continue increasing. Half of the fresh fruit and a quarter of the fresh vegetables available to Americans are imported, and imports of everything from avocados to raspberries are rising. Mexico is the major source of fresh fruit and vegetable imports, supplying half of the imported fresh fruit and three-fourths of the imported fresh vegetables. Many of the fruits and vegetables imported from Mexico are produced on farms that involve partnerships between U.S. and Mexican growers and shippers, with U.S. partners providing capital and technology and marketing Mexican-grown produce. Satisfying and stretching current workers are shorter term strategies to increase the productivity of an aging farm workforce. Substituting machines, hiring guest workers, and increasing imports are longer term strategies to supply fresh fruits and vegetables to Americans.

Policy will help to determine the winner of the race in the fields between machines, migrants and imports. Technologies that could replace farm workers are improving rapidly and decreasing in cost, potentially putting agriculture on the cusp of another wave of labor-saving mechanization. Farmers have long sought new or revised guest worker programs that eliminate requirements to try to recruit U.S.-born workers, provide housing, and pay the super minimum AEWR wage. The House Judiciary Committee approved a bill in November 2017 that includes these farmer wishes, but it has drawn opposition from advocates for removing worker protections and from some farmers for capping the number of guest worker visas at 450,000 a year. If the new H-2C program included in the Agricultural Guest worker Act is enacted, the influx of farm guest workers would likely accelerate, which may reduce support for the engineers and scientists developing machines to replace farm workers. The United States has an overall agricultural trade surplus, but a deficit in agricultural trade with Mexico reflecting ever-more Mexican avocado, tomato and berry imports. The Trump Administration aims to reduce the trade deficit with Mexico in NAFTA renegotiations, perhaps by imposing tariffs or other restrictions on Mexican imports. This could slow the integration of the North American produce industry, which has evolved to provide year-round supplies of fresh fruits and vegetables to Americans. Agriculture has been at farm labor crossroads many times, asking who will pick the crops after the exclusion of the Chinese in the 1880s and the termination of the Bracero program in the 1960s. Today’s race in the fields will determine whether Americans will consume more imported produce or whether fruits and vegetables will continue to be grown in the United States and picked by machines or guest workers. Lowbush “wild” blueberries are considered a nutrient-rich healthy food, due in large part to their exceptional phenolic content and antioxidant activity. Lowbush blueberries are particularly rich in anthocyanins and the anthocyanin profile is complex compared with other fruits. They contain five of the six anthocyanidins commonly found in nature , which can have three different sugar moieties attached as well as acyl groups such as acetyl-, malonyl-, or coumaryl- also attached to the sugar moieties. Blueberries are also rich in proanthocyanidins, chlorogenic acid, and flavonols. Diets rich in blueberries or their polyphenolic-rich extracts have been associated with lower cardiovascular risk, weight gain and metabolic syndrome, and neurological diseases . In addition, studies involving blueberries have identified polyphenolic-derived phenolic acids that improve cell differentiation and proliferation of osteoblasts in vitro and promote bone growth and limit bone loss in rodents. These health-promoting effects are due to a myriad of mechanisms associated with blueberry polyphenolics, including prevention of oxidative stress and inflammation, and vaso- and lipid modulation.

Given the strong linkages between the agriculture sector and the other sectors of the economy, it is important to not only estimate the direct effects of pest damage but also the multiplier effects, because damage to crops by birds and rodents reduces the output of the agriculture sector and all other linked sectors. In general, the economic effects of a change in producer costs are usually broken down into three different categories: direct, indirect, and induced effects. The direct effect of a lower yield can be measured by the revenue lost that the grower would have earned from sale of that acre and the increase cost of pest control. For example, the direct effect of bird damage to an almond orchard would be the value of the damaged and eaten nuts and the farmer’s control costs. However, the revenue of individual growers supports other industries in the economy. Growers create jobs for shop owners, restaurant staff, police, fire, etc., which must also be measured when examining the total economic effect. These additional non-direct or multiplier effects are called secondary economic impacts and are composed of indirect and induced effects. Several studies exist that use IO models to estimate the total impact of California agriculture to the state economy , but no study exists using this model to analyze specifically the total impact of bird and rodent damage to these crops. This paper details the initial determination of the counties and crops that will be used in an IO model to estimate the total economic impact of a group of pests, birds and rodents, on California agriculture. The results of this study is a list of counties that will represent a segment of California’s agricultural production that has a high value and concentration of crops that are susceptible to bird and rodent damage. Ultimately, in subsequent phases of this study, IO modeling will determine the loss of employment and revenue to the regional economy created by birds and rodents.

Identification and accurate measurement of bird and rodent damage to crops has progressed; however, pest arrival, density,growing raspberries in containers and potential and real damage to crops is still an uncertain event at the farm level. Additionally, pesticide use and productivity varies across time and space . To more effectively limit pest dam- age, increased use of Integrated Pest Management tools in California agriculture suggest that California’s pesticide use levels for most crops are low relative to the rest of the United States . There are several important outcomes that emerge from this research on the economic impact of bird and rodent damage to California crops. A useful way to quantify the economic effects, which are likely to occur within the region as a result of change in agriculture expenditures resulting from increased costs and decreased yield due to bird and rodent damage, is through IO modeling. Many governments, agricultural associations, and others benefit from IO modeling but face limited budgets. The methodology presented in this paper is useful for the narrowing of an economic analysis, so that the regions or counties chosen for the analysis provide the most pertinent and valuable results for the stakeholder. Additionally, the results of this economic research can be used at the state level to advocate, in revenue and jobs lost terms, for additional and more effective pest control options. Fluvial suspended sediment fluxes from developed watersheds in semi-arid environments are influenced by natural and human induced changes to the land surface that interact with extremely variable climatic regimes. Environmental monitoring and sedimentary records indicate that fluvial sediment flux dynamics often exhibit temporal dependence over event to interdecadal time scales, particularly in arid to semi-arid climates . However, attributing changes in sediment regimes to a discrete cause is often complicated by the overprinting of many external drivers and internal dynamics that affect watershed scale sediment production and transport, which tend to obscure the effects of individual forcing factors . Furthermore, factors affecting watershed-scale sediment production operate over a wide range of time scales, with even seemingly discrete events generating legacy effects that may last for years or decades .

Semi-arid basins in particular have been found to display persistent dependence on climatically driven antecedent basin conditions, such as storm/flood and wildfire histories . The addition of human influences further complicates sediment flux controls in the highly developed portions of the world that are the most intensively studied . Thus, elucidation of temporal dependence in the suspended sediment dynamics of a highly developed, semi-arid basin is a forensic exercise of implicating and eliminating a host of potential controls. For this reason, when discrete controls on sediment dynamics are discovered in a given watershed it is often the result of scenarios where proportionally large areal disturbances have dominated the sediment response of relatively small watersheds. In this way, wildfire , urbanization , and agriculture have been found to exert significant control on fluvial sediment flux. However, understanding the fluvial sediment dynamics of most systems over inter-decadal time scales requires the disentanglement of multiple controls, particularly at larger spatial scales.The most important external driver controlling inter-decadal scale sediment flux is regional climate, which interacts with internal factors such as geological substrate and topography to influence internal processes such as geomorphic evolution, soil development, vegetation assemblages, and fire frequency . The interaction of vegetation, topography and interannual to decadal scale climatic expression also largely determines wildfire regimes . Sediment flux generally rises after wildfire due to increases in the erodibility of hillslope surfaces through the removal of vegetation and litter layers, destabilization of soil aggregates by organic matter combustion, and increases in soil mantle slides or overland flow due to the development of subsurface and surface soil hydrophobicity, respectively . In systems experiencing dry seasons, such as much of the Western U.S., this results in down-slopedry-ravel transport through gravity alone . Soil heating can also cause hydrophobicity increases in the soil surface that, along with decreases in interception and evapotranspiration, cause increases in surface runoff during the wet season . Increased surface runoff further exacerbates erosion from the destabilized hillslope. Indeed, the timing of high-intensity precipitation plays a large role in post-fire sediment flux augmentation .

Large storms produce precipitation intensities and volumes sufficient to traverse runoff regimes, from sheet flow, to rill and gully erosion, and mass wasting, which can very effectively erode wildfire destabilized hillslopes . With increasing elapsed time between wildfire and high intensity precipitation events, hillslopes generally re-vegetate, re-stabilize, and yield less sediment for a given precipitation magnitude , although decadal scale legacies of individual fires have been reported . Humans have caused pre-historic to historic increases in global sediment flux due largely to agriculture and deforestation . This phenomenon has generally been followed by a rapid decrease in sediment flux during the 20th century, primarily from river impoundment, and to a lesser degree changes in agricultural practices and afforestation . Changes in agricultural practices over the last century have in many cases led to decreases in off-field sediment transport with the implementation of soil conservation practices, including changes to less erosive irrigation techniques . Flow regulation causes declines in basin scale sediment yield by trapping sediment in reservoirs and altering the natural flow regime, particularly through reduction of peak flood discharge magnitudes . After an initial spike during construction, urbanization can also lead to sediment load decreases with the increase in the cover of impervious surfaces . Conversely, extensive urbanization can act to increase sediment yield by altering basin scale precipitation – discharge characteristics ; for example shortening the time to peak flow,large plastic pots for plants decreasing total flow duration, increasing peak magnitude, and increasing total runoff volume .Due to the difficulty and expense of collecting samples, fluvial suspended sediment flux is usually estimated on the basis of infrequent sediment monitoring coupled with more frequent or even continuous discharge monitoring . The most common technique is to compute sediment concentration -discharge rating curves using log-linear regression or non-parametric localized regression methods such as LOESS . Anthropogenic disturbances and wildfire will alter CSS–Q relationships if they result in disproportionate changes in the magnitude and/or timing of the supply of sediment or water relative to one another . Thus, changes in sediment flux and CSS-Q relationships examined in relation to agriculture and wildfire activity over time can provide insight into these important controls onsediment dynamics in highly agricultural, semi-arid basins.

Determination of the dominance of a factor potentially controlling sediment production over other factors can be approached through the comparison of the temporal trends of control metrics with the metric describing sediment production. Correlation between control factors and sediment production metrics can then be analyzed and interpreted in light of the expected effects of a given control .The objective of this study was to examine how contemporary wildfire activity and land use change affected discharge normalized sediment delivery from highly agricultural, semi-arid mountainous watersheds in the context of additional hydrologic and climatic controls. The fundamental approach was to examine changes in suspended sediment – discharge relationships over time in light of temporal trends in wildfire and agricultural activities. Conversely, changes to less erosive agricultural technologies, such as increasing the proportional utilization of drip irrigation, would be expected to result in decreasing sediment production. Departure of sediment production trends from those expected on the basis of changes in a given control factor would be considered as evidence that the factor was not a dominant control on sediment production. Correlation of sediment production metrics with wildfire activities were then used to determine if wildfire disturbance also acted as a short term control on sediment production. Wildfire activity was expected to correlate positively with sediment production. Departure from this expected correlation between sediment production and wildfire would also indicate that wildfire was not a dominant control.The Salinas River drains 11,605 km2 of the Central Coast Ranges of California from a maximum relief of ~ 1,900 m with a mean discharge of 11.6 m3 /s from the lowest gauge in the basin for the periods of 1931- 2011 . The regional climate is dry-summer subtropical — most annual precipitation falls as rain originating from winter storms, the largest of which often occur during strong El Niño years . For this region ‘water years’ begin on 1 October of the previous calendar year and end on 30 September of the calendar year. A strong precipitation gradient extends from the wetter SW to drier NE region of the watershed due to predominant S-SW impingement of storms and orographical forcing . Geologic substrate is primarily Mesozoic sedimentary rock . The Salinas River valley consists of three lateral geomorphic zones – a riverbed, a bottomland, and flanking terraces, with one such terrace containing the major alluvial plain on the valley floor that is populated and used today. The bottomland is a broad bench situated lower than the surrounding plain and separated from it by well-defined side slopes. Though historically there was a well-defined, small, forested channel localized in the bottomland , today the channel is primarily a broad, destabilized active zone that is intermittently well-defined in space and time as either a meandering thread or braided channel. The modern channel is lightly vegetated, with the abundance depending on the duration of interannual dry periods between floods, as these times allow pioneer grasses and willow shrubs to emerge though not necessarily persist. The Salinas valley has been influenced by humans and animals throughout its recorded history and likely thousands of years before the arrival of Europeans. Pre-historically, the Ohlone natives of the region used fire to maintain an open terrain on the main valley floor and to promote their food supply, whereas the hills and mountains around the valley were forested and home to large predators . The moist bottomlands were well vegetated with cottonwoods, sycamores, live oaks, willows, and some pines and white oaks . Archival records and drawings from the Spanish and Mexican era indicate that the bottomlands were deforested in support of the development of the rancho economy prior to American conquest. Further, beaver were likely abundant in the river and important in its morphology and sediment dynamics, yet are now demonstrated to have been extirpated from the landscape as part of the maritime California fur trade during the Spanish and Mexican era . Meanwhile, the higher plains adjacent to the bottomlands were grazed by some millions of free-ranging cattle during this era , until the devastating drought of 1861-1865 ended California’s cattle-based economy.

Due to the fact that only a very small number of microbes can be reliably cultured for further study towards using them as legume crop inoculants, we focused on the PGPB that the plant specifically selects within its root nodules with the goal of finding “helpers” for the nitrogen-fixing rhizobia in supporting plant growth. Soil collections were made in 2017 and 2019 from the farm of the Botswana University of Agricultural and Natural Resources in Notwane from underneath an indigenous Tephrosia purpurea plant . Environmental DNA was isolated from both samples in 2019, at the same time trap experiments were performed, to provide insight into the diversity of the soil microbial community. It should be noted that there was a two-year gap between collecting the 2017 sample and its analysis in contrast to the 2019 sample that was analyzed almost immediately after collection. Because the methodology for DNA extraction was the same, we hypothesized that differences in the percentages of the phyla might occur from changes brought about by storage conditions, or time elapsed. In both the 2017 and 2019 samples, the major phyla were Proteobacteria, Firmicutes, and Actinobacteria. The percentage of Actinobacteria in the 2019 soil was almost twice that of the 2017-collected soil . These results are in line with those obtained by other authors. The bacterial genera responsible for the induction of N2-fixing nodules in legumes belong to the phylum Proteobacteria and are therefore part of the dominant group. The phyla Actinobacteria and Firmicutes contain several genera of bacteria with PGPB activities that are very well documented. The percentages of Gemmatimonadetes, Acidobacteria, and Planctomycetes also varied between the 2017- and 2019-analyzed samples . Whether or not these differences are due to the delay between collection and analysis or other factors such as changes in the surrounding environment such as water content is not known. Nevertheless,plastic pots for planting the data demonstrated that the dominant microbes from the eDNA analysis were Proteobacteria, Firmicutes, and Actinobacteria, all of which are more likely to be cultured and serve as inoculants than the other bacteria listed.

Soil isolates are often considered as sources of inoculants for crops in agriculture, particularly rhizobia and other plant growth-promoting bacteria , but the nodule isolates may be a more specific inoculant for because they are found within nitrogen-fixing nodules. Evidence based on coinoculation experiments with rhizobia also indicates that soil-isolated as well as nodule-associated bacteria may be important for improving plant growth via plant nutrition. Although a large number of soil isolates have been tested for their ability to produce siderophores, solubilize phosphate, fix nitrogen, or perform other plant-growth promoting functions, to our knowledge only a few of them have been actively incorporated into agricultural practices. Due to the sheer numbers of soil isolates potentially available in Botswana soils , we focused our study on microbes housed in legume nodules. Several trap plants, including Vigna unguiculata , Macroptilium atropurpureum , and Tephrosia virginiana, nodulated following inoculation with Botswana soil mixed with an artificial substrate watered with -N medium, but cowpea gave the most consistent results . Bacteria isolated from cowpea nodules included rhizobia , which are known to nodulate cowpea and other legumes . Furthermore, species of Bacillus, including B. safensis and B. pumilus, well known PGPB, were also isolated from cowpea nodules . In addition, several possible opportunistic pathogens including Ochrobactrum anthropi, Burkholderia dolosa, Ralstonia mannitolytica, Staphylococcus pasteuri and others were isolated from cowpea nodules and identified by rrs sequencing. These emerging pathogens, which are often found in plant rhizospheres, were discarded. Non-pathogenic isolates were tested for PGP traits and their ability to grow under salinity stress and at different pH values . A number of isolates exhibited possible PGP activity including phosphate solubilization and siderophore production. Cowpea plants grown in the 2017 Botswana soil sample were harvested after 9 weeks of growth. Control +N plants produced more biomass as measured by dry weight than plants from all other treatments, averaging 1.73 g. The experimental plants were darker green in color than control -N plants and produced more than twice as much biomass, averaging 1.11 g compared to 0.47 g for the -N control.

Cowpea plants grown in the 2019 Botswana soil sample were harvested after 12 weeks of growth because of a lag in growth at the start. Control +N plants were larger, more robust, and darker green than experimental or control -N plants, averaging 0.77 g. Although the experimental plants were not as robust as the +N control plants, a result frequently observed in control plants given super-optimal N, the inoculated cowpeas produced significantly more biomass than the -N controls. All experimental cowpea plants from both soil treatments developed multiple, pink colored root nodules, whereas control -N and control +N plants were devoid of nodules. In both experiments, control -N plants were indistinguishable from control plants grown in soil that was sterilized by auto claving .Because cultivation methods are biased for the reason that very few bacteria are capable of growing on standard bacteriological culture media, we analyzed the cowpea nodule microbiome by isolating eDNA from the nodule tissue and sequenced the eDNA with the goal of obtaining an inventory of the nodule microbial population. We predicted that these analyses would give us insight into the bacteria that were specifically selected by the plant and if they were culturable, they might have potential to be used as commercial inocula. As expected from anatomical studies of determinate nodules such as cowpea, the nodule interior based on eDNA analysis is dominated by Bradyrhizobium spp. . Although DNA sequences from numerous bacterial genera including Microvirga, Rhizobium, Bacillus, Sphingomonas, and others were detected in the nodule microbiome in this study , the exact percentages and diversity of non-rhizobial microbial sequences within the nodule itself are difficult to assess. Nonetheless, several of the genera in the nodule microbiome analysis directly correspond to the nodule isolate genera. The bacterial population of nodules based on sequencing the isolated eDNA differs in terms of representation from the results obtained from isolating microbes from soil. The soil population is dominated by Actinobacteria, Proteobacteria, and Firmicutes . Although a large number of Gram-positive species are detected in the soil microbiome analysis, they are detected at very low levels in the nodule microbiome .

Nevertheless, some genera such as Bacillus as well as actinomycetes, especially Micromonospora, are repeatedly isolated from nitrogen-fixing nodules and also detected in the nodule microbiome analysis. Coupled with the fact that several of these species, when inoculated with rhizobia frequently enhance the symbiosis,drainage for plants in pots this strongly suggests that they have a positive effect on the symbiosis. The difference between the soil and nodule microbial populations in terms of numbers of microbes is reminiscent of the differences in the numbers of bacteria found in the rhizosphere versus the endosphere and between the rhizosphere and rhizoplane communities in other plant systems such as pepper and maize. Whether or not this is a specific selection for a large number of beneficial bacteria to protect the root or leaf surface from pathogen attack as suggested by the camouflage hypothesis or that normally surface bacteria are excluded from internal tissues and only some of the bacteria that enter roots and nodules are “cheaters” is difficult to determine at this time. In contrast, rhizobia are actively selected by the host plant for their symbiotic traits in response to active recognition between the host and its symbiont. Whether a similar recognition system operates between PGPB and plant surfaces is not known. Although the mechanisms used by the non-rhizobial endophytes to enter the root and the nodule frequently involve the secretion of hydrolytic enzymes such as cellulase and pectinase, are these enzymes induced because the bacteria are recognized, and if so, what are the signals to which the endophytes are responding? To our knowledge, the mechanisms underlying how a coinoculation between rhizobia and PGPB triggers plant growth stimulation are not well understood. There is now a large literature examining the impact of climate change on agricultural yields that can be divided into two types of studies. A second category that has been developed more recently looks at statistical relationships between climate or weather and crop yields. The benefits of the former are that it is grounded in a mechanistic, bottom-up understanding of how plants grow. But process-based models are often calibrated to specific field settings which can be data intensive and means the generalizability of results to larger areas is unclear.

Statistical models are typically based on observations of crop growth over large areas in real-world field settings. But the reduced-form relationship between weather variables and yield means the mechanisms driving model results are often unclear and that care should therefore be taken in using results for climate change projections extending beyond the historical record. Despite the fact that both approaches seek to quantify the impacts of climate change on agricultural productivity, there have been relatively few attempts to systematically compare findings. A number of studies have compared process-based and empirical responses for individual crops in individual locations, such as maize and wheat in South Africa or maize in Switzerland . At the global level, Liu et al provide a systematic comparison of the temperature response of wheat yields estimated from regression models, up scaling point estimates from an ensemble of process-based models, and gridded process-based models, generally finding only small differences between the three methods. In this special issue, Lobell and Asseng compare individual published estimates of crop sensitivities to climate impacts from process-based and empirical yield models, finding little difference in the temperature response. Roudier et al , Knox et al , and Knox et al are perhaps most similar to the analysis presented here. These papers present meta-analyses of yield impacts for multiple crops in specific regions and report average differences between process-based and empirical estimates. All papers find that the effect of impact estimation technique is small relative to other sources of variation. Our approach adds to these studies firstly by performing a global analysis and secondly by using a multivariate regression for our meta-analysis, instead of simply splitting the sample of studies. This multivariate approach allows us both to control for potential confounding variables and to estimate continuous response functions that can be globally extrapolated in order to inform an economic analysis. In the agricultural sector, the effect of climate change-induced yield shocks on more policy-relevant variables such as prices, consumption, food-security, and economic welfare will be mediated by the global trade in agricultural commodities and will depend on terms-of-trade effects and the interaction of climate change impacts with existing market distortions . Though several papers have incorporated climate productivity shocks into partial- and general-equilibrium models very few report welfare changes . Understanding the welfare impacts of climate change-induced productivity shocks on agriculture is important both for policy and because the simple integrated assessment models used to calculate the social cost of carbon use damage functions that parameterize changes in economic welfare with temperature. Current agricultural damage functions in these IAMs use studies from the early-to-mid 1990s that are now dated and largely obsolete . This paper contributes to the existing literature in two ways. It is the first systematic, multi-crop, global comparison between empirical and process-based crop models. Although the distinction between these approaches has been widely discussed, this paper quantifies this difference at the global scale and puts it in the context of other uncertainties in future climate change impacts, such as how quickly farmers are able to adapt to climate change. In addition, we advance the literature by examining not just yields but also economic welfare by incorporating estimated yield changes into the Global Trade Analysis Project CGE model, thereby producing results ready to inform IAM damage functions.The basis of the yield-temperature response functions in this paper is a database of studies estimating the climate change impact on yield compiled for the IPCC 5th Assessment Report , also described in a meta-analysis by Challinor et al . This database contains over 1700 point estimates of the impacts of changes in temperature, rainfall, and CO2 concentrations on the yield of 17 different crops compiled from 94 different studies.