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CB has been deemed persistent in the environment but with a low potential for bioaccumulation and toxicity

Root exudation may also be altered after nanomaterial exposure.In addition, adsorption of nanomaterials to bacterial cell surfaces has been reported to disperse nanomaterial agglomerates.Such processes and other soil characteristics could cause temporal variations in CNM behavior within the natural soil environment, including differentially over the course of plant growth. The results of the CNM concentration-dependent agglomeration in aqueous soil extracts qualitatively explained the observed inverse dose–response trends, which deviate from typical sigmoidal dose–response relationships reported for toxicants that dissolve in soil water , but quantitative tests are not possible because of the complex soil characteristics and dynamic processes described above. In this study, with nondissolving but agglomerating CNMs, small amounts of CNMs in moist soil did not agglomerate but rather remained suspended in soil water where they were more bio-available and impactful to soil microbes and plant roots. With larger amounts of CNMs in moist soil, large agglomerates formed, which led to a sharp decrease in their bio-availability and observed impacts . Although the inverse dose–response patterns were mostly shared across CNMs, the relationships were linear for CB and fit a power function for MWCNTs . Differences in agglomeration and possibly differing toxicity mechanisms could explain the differing model fits. Our results demonstrate that not only the mass concentration and primary particle size but also the level of agglomeration may play critical roles in determining CNM effects on plants and their root symbioses in soils. In prior microbial toxicity and hydroponic phytotoxicity studies, it was recognized that nanomaterial effects would increase as nanomaterial size decreases but would decrease as nanomaterials agglomerate. For instance, antimicrobial activity was found to be higher for smaller versus larger graphene oxide sheets,while debundled, short,nft system and dispersed MWCNTs were demonstrated to have relatively higher bacterial cytotoxicity due to enhanced MWCNT–cell contact.Depicted as “nano darts”, individually dispersed single-walled carbon nanotubes were reported to induce more bacterial death than SWCNT aggregates, as dispersed SWCNTs directly damaged bacterial cell membranes.

In hydroponic studies, dispersed MWCNTs were found to have stronger effects on tomato plants than MWCNT agglomerates.Even when comparing among agglomerates, small MWCNT agglomerates exerted stronger impacts to Arabidopsis T87 cells than large agglomerates.Still, the dose–response relationship for unstudied low concentrations, which are, across the herein unstudied range of 0 to 0.1 mg kg−1, is uncertain. It is possible that the whole-plant N2 fixation potential decreased continuously with CB concentration until 0.1 mg kg−1 . Alternatively, there could be a threshold concentration somewhere between 0 and 0.1 mg kg−1, possibly close to the lowest studied dose , above which the inhibition of the whole-plant N2 fixation potential occurred but below which it did not . There is uncertainty in such untested low concentration regimes. Such uncertainty reinforces the challenges in extrapolating toxicological results from studies using only high nanomaterial concentrations to low concentration exposure scenarios, owing to influential effects of nanomaterial physicochemical structuring.We chose multi-walled carbon nanotubes and graphene nanoplatelets as two representative engineered CNMs, with industrial carbon black for comparison. CB has been commercialized for decades in the rubber and pigment manufacturing industries,with annual production of over 10 million metric tons.However, there is evidence that CB may have similar or higher toxic effects on soil bacterial communities and amphipods compared with other CNMs.Therefore, assessing whether CB affects soybean and N2 fixing symbioses and comparing how the effects differ from those of MWCNTs and GNPs are important from an environmental regulatory standpoint. MWCNTs and GNPs were purchased from Cheap Tubes Inc. ; carbon black was purchased from Dorsett & Jackson Inc. . Besides the manufacturer reported properties , CNMs were characterized by transmission electron microscopy , thermogravimetric analysis , and inductively coupled plasma optical emission spectroscopy for material morphology, thermal stability, overall purity, and metal composition, following previously reported methods.The CNMs were used as received without further purification.

Three concentrations of MWCNTs, GNPs, and CB were evaluated in this study. A sequential 10-fold dilution method accompanied by mechanical mixing was used to prepare homogenized soil and CNM mixtures as reported previously.The mixing was performed using a hand-held kitchen mixer, from the low to the high CNM concentration treatments, with the mixer cleaned between different CNMs to avoid contamination. The cleaning procedure followed guidelines recommended by the National Institute for Occupational Safety and Health for cleaning surfaces contaminated with carbon nanotubes.CNM dry powder was weighed and amended directly into soil in concentrations of 0.01, 10, and 100 g kg−1 . Each mixture was blended thoroughly using the mixer for at least 10 min. These CNM–soil stocks were then diluted ten times by the addition of unamended soil and mixing by the mixer similarly as above, resulting in concentrations of 0.001, 1, and 10 g kg−1. The dilution and mixing were repeated again to achieve the final CNM working concentrations of 0.1, 100, and 1000 mg kg−1. The CNM–soil mixtures were stored prior to planting.Bradyrhizobium japonicum USDA 110 was initially streaked from frozen stock glycerol onto solid modified arabinose gluconate medium24 with 1.8% agar in a Petri dish, then cultivated in the dark. Following incubation, several discrete colonies were dispersed into 4 mL of liquid MAG medium. An aliquot was inoculated into a 500 mL glass flask containing 100 mL of liquid MAG medium and incubated in the dark for 5 d until stationary growth phase. Aliquots of the culture were dispensed into centrifuge tubes and centrifuged , and the supernatant was discarded. Cell pellets were resuspended in a 1 M MgSO4 solution to an optical density at 600 nm of 1.0 to serve as the inoculum during seed planting. Soybean seeds were purchased from Park Seed Co. . Seeds were inoculated with B. japonicum following the method of Priester et al.Specifically, seeds were soaked in the B. japonicum inoculum for 10 min and deposited into rehydrated peat-filled seed starter pellets at 1/4-in. depth using forceps. An aliquot of the B. japonicum inoculum was dispensed into the pellet holes over the planted seed; the seed plus additional inoculum were then covered with a thin layer of the peat pellet substrate. The pellets were watered daily and incubated on a heating mat . Each planting pot was comprised of a 3 qt high density polyethylene container with bottom perforations, which was lined with polyethylene WeedBlock fabric at the bottom, and overlain by 400 g of washed gravel to allow water drainage.

A polyethylene bag punched with 40 evenly spaced 5 mm holes was placed over the gravel, and 2.3 kg of soil was weighed into each bag. Perforation of the bags allowed for water drainage, thereby preventing root rot within the soil-filled bags. Overall, there were 10 treatments, including three concentrations for each of CB, MWCNTs, and GNPs, plus a control soil without nanomaterial amendment. There were eight replicate pots per treatment. Ten days after seed sowing, 80 VC stage 59 seedlings were transplanted into potted soils. Prior to transplanting, the outside mesh of the starter pellets was removed carefully to minimally disturb the seedling roots. A central planting hole was formed in the soil, into which B. japonicum inoculum was dispensed. One seedling was inserted into the hole, and another aliquot of B. japonicum inoculum was dispensed onto the surface. Both inoculation steps were deemed necessary for adequate contact between B. japonicum and the soybean roots and thus effective inoculation. The filled transplanting hole was covered by a thin layer of soil, and the potted soil surface covered by a layer of WeedBlock fabric to minimize soil surface crusting and weed growth. A wooden support stake was inserted against the inside wall of each pot for later plant support by tying, as needed. After transplanting, the plants were grown for another 39 d to the R6 stage in the Schuyler Greenhouse at the University of California at Santa Barbara. The greenhouse climate was controlled using VersiSTEP automation under full sunlight. The indoor air temperature ranged from 15 to 34 °C,hydroponic gutter and the indoor photosynthetically active radiation fluctuated between 21 and 930 μmol m−2 s −1 from nighttime to daytime. Soil moisture sensors were inserted to a depth of 13 cm into the soil of seven pots to monitor soil volumetric water content, electrical conductivity, and temperature. Data were recorded at least twice daily using a ProCheck data display . Pots were watered to retain an average soil volumetric water content of 0.25 m3 m−3 .Midori Giant is a determinate soybean variety, which stops vegetative growth soon after flowering initiates.Also, N2 fixation will accelerate when plants initiate pod development. Therefore, plants were harvested at each of two stages: intermediate or final , aimed at capturing CNM effects on plant vegetative growth with early nodule formation, and then reproductive development with highest N2 fixation potential. Three replicate plants from each of the ten treatments were sacrificed at the intermediate harvest , and five replicates were sacrificed at the final harvest , when plants reached stage R6 .At harvest, plants were separated, above ground from below ground, by cutting the stem at the soil surface using a single edge razor blade. The above ground part was further divided into stem, leaves, and pods . Leaves and pods were counted and arranged according to their sizes, then photographed. Total leaf area and pod size were further quantified by analyzing the images using Adobe Photoshop software.Sub-samples of fresh leaves and pods were weighed and then stored for future analyses.

The remaining tissues were transferred to separate paper bags, then weighed before and after drying to determine wet and dry biomass plus gravimetric moisture content. The below ground plant parts were removed from the pot within the polyethylene bag surround. The soil in the bag was gently loosened from around the roots and nodules using a metal Scoopula , while minimizing root system disturbance. The relatively intact below ground parts, including roots and nodules, were rinsed in deionized water thoroughly to remove remaining attached soil, then air-dried. The nodules were carefully excised from the roots using a single edge razor blade and forceps as reported previously.Nodules were counted; sub-samples were weighed and refrigerated for later TEM analysis. The remaining nodules were weighed and then analyzed immediately for N2 fixation potential. Roots were dried and massed as above, to determine gravimetric moisture content and dry biomass. After N2 fixation potential measurements, nodules were also similarly dried and massed. After acquiring dry masses, all dried plant parts were archived for future analyses. Sub-samples of soil from each pot were collected and stored for future analyses. The N2 fixation potentials of root nodules were measured as nitrogenase activity by the acetylene reduction assay, according to standard methods with some modifications.Pure acetylene gas was generated by the reaction of calcium carbide and deionized water in a 1 L Erlenmeyer flask, with C2H2 collected into a 1 L Tedlar bag . Intact nodules that were freshly excised from cleaned plant roots were placed into a 60 mL syringe with a LuerLok Tip and incubated with 10% C2H2 . At 0, 15, 30, 45, and 60 min, 10 mL of the gas sample in the syringe was injected into an SRI 8610C gas chromatograph with a sample loop to measure the C2H2 reduction to ethylene over time. The GC was equipped with a flame ionization detector and a 3 ft × 1/8 in. silica gel packed column. Helium was used as the carrier gas at a pressure of 15 psi . Hydrogen gas and air were supplied for FID combustion at 25 and 250 mL min−1, respectively. The oven temperature was held constant . The C2H4 peak area and retention time were recorded using PeakSimple Chromatography Software . Chemically pure C2H4 gas was diluted by air and measured to establish a C2H4 standard curve . The C2H4 peak area values were converted to C2H4 concentrations against the standard curve and further to moles of C2H4 using the ideal gas law assuming ambient temperature and pressure. For each analysis, the moles of C2H4 produced were plotted over time, and the relationship was evaluated for linearity, then fitted by a linear regression model to calculate the C2H4 production rate. The N2 fixation potential was calculated as the C2H4 production rate normalized to the assayed dry nodule biomass.

Hedgerows may therefore represent a source of bee diversity in the landscape

Of the species only at controls, 80% were represented by a single individual. The species only at hedgerows tended to have more specialized nesting requirements , whereas those only at controls were primarily generalists . Also, although the majority of the species were found at both hedgerows and unrestored controls , species ranging from relatively rare to common were infrequent at controls and more abundant in hedgerows . Interestingly, the three species observed over 100 times, Lasioglossum incompletum, Halictus tripartitus and Halictus ligatus, all small-bodied floral and nesting resource generalists, were at similar abundances in hedgerows and unrestored controls, if not slightly more abundant in controls .Although hedgerows may help counter homogenization of pollinator communities in simplified agricultural landscapes, comparing the spatial heterogeneity they support to that which is observed in natural communities is important in assessing their overall conservation value. In remnant chaparral/oak woodland communities in the same ecoregion and adjacent to our study landscapes , an average of 30% of species were not shared across sites located within 3.5–50 km of each other. The Central Valley, which was once described as ‘one vast, level, even flower-bed’ , has been extensively converted to agriculture, likely limiting the species pool due to local extinctions. Even so, at hedgerows an average of 15 km apart, we found between 36% and 67% of species were not shared between sites, depending on the year. Both the spatial scale and biota of our study and that of are comparable, suggesting that hedgerows are, in fact,grow strawberry in containers restoring spatial heterogeneity to approximately the same range as might occur in adjacent natural systems. In addition, in the disparate landscape of the southwestern United States, a diversity hot spot for bees , 61% of species were not shared across sites within 1–5 km of each other .

Although the species pool is richer in the southwest, the amount of species turnover at hedgerows is not unlike what is observed in that highly heterogeneous region . Thus, across many aspects of biodiversity, hedgerows might provide a valuable measure for conserving biodiversity . Only mature hedgerows in this study supported higher trait and b-diversity when compared to non-restored farm edges. Thus, the processes that lead to a buildup of spatial turnover in pollinator communities are slow and may take considerable time before observably affecting pollinator communities. However, we have recently shown that hedgerow restoration leads to increased rates of colonization and persistence of pollinators in maturing hedgerows and that this effect becomes stronger over time . Further, we found that maturing hedgerows differentially support more specialized species over time . These two temporal studies on the early phases of hedgerow maturation show that hedgerows begin to impact pollinator communities much earlier than 10 years. Combined, these findings suggest a possible mechanism whereby restoration might lead to increases in species turnover; as a hedgerow matures, species with a wider variety of life-history traits are better able to colonize and persist there, thus leading to the accumulation of differences in community composition between sites over time. This then leads to greater spatial heterogeneity in pollinator communities at hedgerows. Conversely, in unrestored areas, the rate of colonization and persistence is lower, particularly for species with more specialized habitat requirements, thereby creating an ecological filter that limits the total diversity and, thus, turnover that is possible. This above-described process can be, in part, deterministic; restored and non-restored farm edges differ fundamentally in which pollinator species are able to colonize and/or persist in them . Thus, pollinators respond to the differences in the plant communities between hedgerows and controls, and the pollinator community at mature hedgerows tracks floral hosts. Interestingly, however, the pollinator communities at hedgerows that were closer to one another were not necessarily more similar than sites that were further apart.

In addition, hedgerows maintain b-diversity in the landscape by supporting unique combinations of species, and we did not find evidence that communities at hedgerows were nested subsets of one another . Because hedgerows are planted, the floral communities the pollinators are tracking will not necessarily be spatially structured like natural communities. In addition, bees are known to be highly spatially and temporally variable and thus, stochastic processes that do not result in spatial structuring are likely operating as communities assemble. In contrast to within hedgerows, the dissimilarity of pollinators at unrestored controls responded positively to geographic distance. Because the conditions at controls are relatively uniform across space, this suggests a role for dispersal limitation in determining pollinator community composition at unrestored controls . In addition, the number of shared species between hedgerows and controls was also positively related to distance , suggesting the communities at controls may be influenced by landscape context such as the presence of nearby hedgerows.Here we focus on the effects of hedgerows on b-diversity, but there are likely other contributions to spatial heterogeneity in our landscape. There are a number of crops that provide floral resources to pollinators in our area, including mass-flowering sunflower, melons, and almonds . Different crops attract different pollinators and thus may affect the spatial heterogeneity of communities. In addition, some crops might also pull resident species from the hedgerows , while others may attract species that may subsequently colonize hedgerows . Differences in adjacent crops between hedgerows and unrestored controls thus may add noise to the underlying signal of b-diversity. However, because hedgerows and controls are matched for crop type, while there may be a contribution of crop type on b-diversity, it should be a random one affecting hedgerows and controls simultaneously. To achieve sustainable food production while protecting biodiversity, we need to grow food in a manner that protects, utilizes, and regenerates ecosystem services, rather than replacing them .

Diversification practices such as installing hedgerows, when replicated across a landscape, may provide a promising mechanism for conserving and restoring ecosystem services and biodiversity in working landscapes while potentially improving pollination and crop yields .Increasing population and consumption have raised concerns about the capability of agriculture in the provision of future food security. Te overarching effects of climate change pose further threats to the sustainability of agricultural systems. Recent estimates suggested that global agricultural production should increase by 70% to meet the food demands of a world populated with ca. 9.1 billion people in 2050. Food security is particularly concerning in developing countries, as production should double to provide sufficient food for their rapidly growing populations. Whether there are enough land and water resources to realize the production growth needed in the future has been the subject of several global-scale assessments. Te increase in crop production can be achieved through extensifcation and/or intensifcation. At the global scale, almost 90% of the gain in production is expected to be derived from improvement in the yield,hydroponic nft channel but in developing countries, land expansion would remain a significant contributor to the production growth. Land suitability evaluations, yield gap analysis, and dynamic crop models have suggested that the sustainable intensification alone or in conjugation with land expansion could fulfil the society’s growing food needs in the future. Although the world as a whole is posited to produce enough food for the projected future population, this envisioned food security holds little promise for individual countries as there exist immense disparities between regions and countries in the availability of land and water resources, and the socio-economic development. Global Agro-Ecological Zone analysis suggests that there are vast acreages of suitable but unused land in the world that can potentially be exploited for crop production; however, these lands are distributed very unevenly across the globe with some regions, such as the Middle East and North Africa , deemed to have very little or no land for expansion. Likewise, globally available fresh water resources exceed current agricultural needs but due to their patchy distribution, an increasing number of countries, particularly in the MENA region, are experiencing severe water scarcity.

Owing to these regional differences, location-specific analyses are necessary to examine if the available land and water resources in each country will suffice the future food requirements of its nation, particularly if the country is still experiencing significant population growth.As a preeminent agricultural country in the MENA region, Iran has long been pursuing an ambitious plan to achieve food self- sufficiency. Iran’s self- sufficiency program for wheat started in 1990, but the low rate of pro-duction increase has never sustainably alleviated the need for grain imports. Currently, Iran’s agriculture supplies about 90% of the domestic food demands but at the cost of consuming 92% of the avail-able freshwater. In rough terms, the net value of agricultural import is equal to 14% of Iran’s cur-rent oil export gross revenue. Located in a dry climatic zone, Iran is currently experiencing unprecedented water shortage problems which adversely, and in some cases irreversibly, affect the country’s economy, ecosystem functions, and lives of many people. Te mean annual precipitation is below 250 mm in about 70% of the country and only 3% of Iran, i.e. 4.7 million ha, receives above 500 mm yr−1 precipitation . The geographical distribution of Iran’s croplands shows that the majority of Iran’s cropping activities take place in the west, northwest, and northern parts of the country where annual precipitation exceeds 250 mm . However, irrigated cropping is practiced in regions with precipitations as low as 200 mm year−1, or even below 100 mm year−1. To support agriculture, irrigated farming has been implemented unbridled, which has devastated the water scarcity problem.The increase in agricultural production has never been able to keep pace with raising demands propelled by a drastic population growth over the past few decades, leading to a negative net international trade of Iran in the agriculture sector with a declining trend in the near past . Although justified on geopolitical merits, Iran’s self-sufficiency agenda has remained an issue of controversy for both agro-ecological and economic reasons. Natural potentials and constraints for crop production need to be assessed to ensure both suitability and productivity of agricultural systems. However, the extents to which the land and water resources of Iran can meet the nation’s future food demand and simultaneously maintain environmental integrity is not well understood. With recent advancement in GIS technology and availability of geospatial soil and climate data, land suitability analysis now can be conducted to gain insight into the capability of land for agricultural activities at both regional and global scales. Land evaluation in Iran has been conducted only at local, small scales and based on the specific requirements of a few number of crops such wheat, rice and faba bean. However, there is no large scale, country-wide analysis quantifying the suitability of Iran’s land for agricultural use. Herein, we systematically evaluated the capacity of Iran’s land for agriculture based on the soil properties, topography, and climate conditions that are widely known for their relevance with agricultural suitability. Our main objectives were to: quantify and map the suitability of Iran’s land resources for cropping, and examine if further increase in production can be achieved through agriculture expansion and/or the redistribution of croplands without expansion. The analyses were carried out using a large number of geospatial datasets at very high spatial resolutions of 850m and 28m . Our results will be useful for estimating Iran’s future food production capacity and hence have profound implications for the country’s food self-sufficiency program and international agricultural trade. Although the focus of this study is Iran, our approach is transferrable to other countries, especially to those in the MENA region that are facing similar As a preeminent agricultural country in the MENA region, Iran has long been pursuing an ambitious plan to achieve food self- sufficiency. Iran’s self- sufficiency program for wheat started in 1990, but the low rate of production increase has never sustainably alleviated the need for grain imports. Currently, Iran’s agriculture supplies about 90% of the domestic food demands but at the cost of consuming 92% of the available freshwater. In rough terms, the net value of agricultural import is equal to 14% of Iran’s current oil export gross revenue. Located in a dry climatic zone, Iran is currently experiencing unprecedented water shortage problems which adversely, and in some cases irreversibly, affect the country’s economy, ecosystem functions, and lives of many people.

The linear model for the Nema Quad system had the steepest slope but not a very strong R-squared value

Even though no significant differences were detected with the ANOVA analysis, linear models were weak at representing the relationship between fruit size and fruit per hectare and all systems using size-controlling root stocks had an R-squared value <0.15 . Continuing the trend from the previous season, in 2019 for June Flame, there were no significant differences in the slope of fruit size vs fruit per hectare relationship for any of the systems . The contrast between the C-6 Quad system and Nema Quad system did have a t.ratio with a greater absolute value than 1.68, however the P.value for the same comparison was still greater than the designated alpha, > 0.05. In this same season the C-6 Quad system had the best fit for the linear model showing a negative correlation between fruit size and fruit per hectare. All other systems fit the model poorly and also did not indicate a clear negative correlation between fruit size and fruit count per hectare . For the August Flame harvest of 2017, data from all systems fit linear models that showed a negative correlation between fruit size and fruit per hectare . Values for the t. ratio between the C-9 Quad and Nema Quad systems were beyond the absolute limit but had a P. value greater than the declared alpha, thus no significant differences were confirmed .For the 2018 harvest of August Flame there were no significant differences in the fruit size vs. fruit per hectare relationships detected among systems . Linear models fit 2018 August Flame data better than other years and showed a clear negative correlation between fruit size and fruit per hectare . In 2019 there was a wide spread of mean fruit sizes per tree in the August Flame data and no significant differences occurred among systems for the relationship between fruit size and fruit per hectare . Although the ANOVA analysis did not indicate differences among systems,hydroponic nft system linear models indicated a weak negative correlation between fruit size and fruit per hectare with all systems having near horizontal models accompanied by Rsquared values <0.1 . Although R-squared values for the linear models representing the relationship between fruit size and fruit per hectare were identical to those for fruit size and fruit per tree , there were differences detected in the contrast analysis for slopes.

Data for the June Flame 2017 and 2018 harvest seasons indicated no significant differences in the relationship for fruit size vs fruit count per tree among any of the systems . In 2019 there was a significant difference in the data for the June Flame cultivar between the C-6 Quad system and the Nema Quad system . In the 2017 harvest data of August Flame there was a significant difference in the fruit size vs. fruit per tree relationship among C-6 V and Nema Quad systems . The difference in 2017 data was visually apparent in the steeper slope indicated in the C-6 V system but that might be a result of the narrow range of fruit loads per tree in that system . No significant differences in the fruit size vs. crop load per tree relationship were detected in the harvest season of 2018, however both, C-6 Quad and C-6 V systems, had t. ratios indicating one may exist, but p-values remained above alpha, therefore a difference was not conclusive . Data for the 2019 harvest of August Flame indicated no significant differences in this relationship between systems, and in fact, the fruit size vs. crop load per tree relationship were most similar among systems in this year compared to other years .A relationship between light interception and yield was most apparent in the June Flame cultivar with the C-6 Quad and C-9 Quad systems which produced data that fit linear models with the highest R-squared values.Data from the C-6 V system had a poor fit with a linear model. Interestingly the systems with data that had a poor fit to the model also had the highest % light interception, often >50% . August Flame cultivars showed a similar pattern for the relationship between amount of light intercepted and yield. Data from the Nema Quad and C-6 V systems had poor fits to the linear models but also had the highest light interception. Data from the C-9 Quad system had a moderate correlation between PAR and yield, fit the model best.

The C-6 Quad system is an apparent outlier, having a value of almost 5 Kg/m2 yield with only about 40% light interception, and a very slight negative correlation between the two parameters . Both of the C-6 V systems with the June and August flame cultivars had trends as shown in previous research, higher density systems were able to intercept a higher proportion of light during earlier years because the trees fill their allotted space more quickly, . The mean fruit size for the June Flame cultivar in 2017 was similar among all systems, most likely a result of consistent thinning resulting in the desired crop loads per tree. In 2018 the mean fruit size for June Flame systems was exceptionally large, especially for an early bearing cultivar. Considering that the C-6 Quad and C-6 V systems had some of the largest fruit sizes provides strong evidence that size-controlling root stocks are not always associated with reductions in fruit size. The C-9 system had poor performance in the trial but, with its success in previous studies and how well systems with the more size controlling root stocks performed in this trial, it is likely not due to the reduced hydraulic conductance associated with size controlling root stocks . June Flame systems in 2019 closely mirrored fruit sizes from the previous season, providing more confidence that any reduction in fruit size compared to the Nema Quad system is unlikely a result of size controlling root stocks. The results from the June Flame cultivar are most promising because there were concerns that the size-controlling root stocks may have the potential to have negative effects on fruit size in early maturing cultivars. With how quickly early bearing cultivars must set and mature fruit during the spring flush growth, there was concern that reduced hydraulic conductance associated with undeveloped xylem would influence fruit size . However, this trial did not provide evidence that early maturing cultivars on the size-controlling root stocks produce smaller sized fruit compared to those on more vigorous root stocks.

With the August Flame cultivar, systems using size-controlling root stocks also were not found to diminish fruit size in this later maturing cultivar. In 2017 all dwarfing systems performed beyond expectations. With fruit sizes reaching almost 300 grams, it is likely that thinning may have been excessive and crop load per tree could have been increased while still reaching above minimum fresh market size requirements. The strong yield for high density plantings of August Flame during the 2017 harvest supports reports of higher density plantings reaching full cropping sooner than low density systems . By 2018 the Nema Quad systems were able to produce fruit of similar size compared to systems with size-controlling root stocks, but fruit were still not the largest. Large fruit sizes indicate that the amount of thinning could, again, have been reduced. In 2019 there was noticeable water stress in the field due to some irrigation problems,nft channel but the magnitude of the problem was not documented. It is likely the water stress was a reason for some of the smaller fruit sizes compared to previous years. Most interesting about the 2019 season was the performance of the C-9 Quad system and how after producing significantly smaller and fewer fruit in both previous seasons, it now had the largest mean fruit size. Overall, systems with size-controlling root stocks performed well and on par compared to the Nema Quad system giving confidence that reduced hydraulic conductance associated with size-controlling root stocks does not necessarily reduce fruit size in either early or late bearing cultivars such as June and August Flame.In addition to fruit size, number of fruits produced was not diminished in systems using size controlling root stocks compared to the Nema Quad system. The 2017 harvest for the June Flame cultivar was the only harvest that the Nema Quad system produced significantly more fruit per hectare than all other systems. These results differ with previous studies where KAC_V plantings reached full cropping at the same time as trees on vigorous root stocks but, systems with size-controlling root stocks pruned to an open-vase lagged behind more vigorous root stocks . By 2018 the C-6 Quad and C-6 V systems produced more fruit per hectare than the Nema Quad system while the C-9 system had a substantially reduced yield compared to all other systems. Fruit count could have been increased had thinning been more consistently managed but since fruit sizes were also similar, results would not likely have changed in terms of differences between systems. 2019 was by far the most productive harvest for June Flame, with strong yields in the C-6 Quad, C-6 V, and Nema Quad systems while the C-9 Quad was less productive. Due to the lack of significant differences among systems there is no evidence that a reduction in either fruit size or fruit count would be expected in an orchard system using size-controlling root stocks compared to a system with more vigorous root stocks, when using appropriate management practices and planting densities adjusted for the reduced tree size.

Results from the 2017 harvest of August Flame were much more aligned with previous studies where systems with high-density plantings reached maximum yield capacity earlier than in low-density systems . It is possible that if the amount of thinning in the C-6 Quad and C-6 V systems had not been as severe, they could have produced significantly more fruit than the Nema Quad system. The C-9 Quad system had the lowest fruit count but, with such a large fruit size, could have potentially produced a fruit count similar to the Nema Quad system if thinning had been done more precisely. In 2018 the fruit count was similar in the C-6 Quad, C-6 V, and Nema Quad systems while the C-9 Quad system had half the crop load as the other systems. Since the most size-controlling root stocks produced yields on par with the Nema Quad system, it is probable that the C-9 Quad system was under some stress that hindered production rather than its reduced fruit count being a result of reduced hydraulic conductance in the root stock. It is likely in 2019 that all systems were under stress. Not only was fruit size significantly smaller than previous years, fruit count per hectare was also fewer than that of even the earlier bearing cultivar for all systems except the C-9 Quad. It is widely accepted that as crop load increases fruit size diminishes . In this study the relationship between crop load and fruit size was similar among systems with high density plantings on size-controlling root stocks and the system with lower planting densities on a vigorous root stock. Results were as expected, as crop load increased fruit size diminished. Although the relationship between fruit size and fruit produced per hectare was not significantly different among systems, appropriate crop load per tree and fruit size was influenced by planting density. The larger crop load that trees in the Nema Quad system could hold while maintaining similar fruit size as trees from other systems with significantly reduced crop load per tree indicate that trees with size-controlling root stocks planted at a higher density may not be able to maintain as large of fruit size with larger crop loads compared to trees with more vigorous root stocks at wider spaced plantings, this concurs with findings from Inglese et al., . Results from this study also demonstrate that an increased number of trees per unit area compensate for the reduced crop load per tree, thus allowing high-density plantings on size controlling root stocks to be a viable option for commercial production, similar findings have been reported by Webster and DeJong et al., .It is well documented that an orchard’s ability to intercept photosynthetically active radiation influences yield and that the two are linearly related up to 50% light interception .