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Various tillage systems have limitations on soil health, such as the degradation of soil structure and organic matter under conventional tillage (CT) systems, as well as short‐term soil compaction in conservation tillage systems. A 3‐year field experiment was established to evaluate the integration of cover crop (CC) and organic amendments (OAs) into CT and strip tillage (ST) systems, and their impact on soil properties and cotton (Gossypium hirsutumL.) productivity. The CC was cereal rye (Secale cereale), and the combined application of animal manure and biochar constituted the OA. In the third year, differences in soil compaction between the CT and ST systems were observed when the measurements were made after tillage. Moreover, integrating CC and OA under the CT and ST systems increased the soil depth to compaction zones. Soil compaction was observed at 27.5‐cm depth under CT, at 30‐cm depth under CT integrated with CC and OA, at 10‐cm depth under ST, and at 15‐cm depth under ST integrated with CC and OA, using 2 MPa as the threshold. In general, the integration of CC and OA tended to increase soil respiration, organic matter, and available nutrients, but the effects were not consistent across years and soil depth. Despite differences in the various soil health properties, the management systems had minimum impact on cotton productivity and fiber quality, indicating the ST was effective in preparing the seedbed. Moreover, the differences in soil properties were not at yield‐limiting levels within 3 years of the study. A 3‐year assessment of integrating cover crops and organic amendments into different tillage systems was made.Differences in soil compaction between the different tillage systems were observed after tillage operation.Integrated systems increased soil depth to compaction zones under the different tillage systems by the third year.Integrated systems effects on soil respiration, organic matter, and nutrients were not consistent over time.The integrated systems had no significant impact on cotton yield and fiber quality in all 3 years.

This study quantifies the effects of wide row spacing on lint yield, yield components, and fiber quality of upland cotton (Gossypium hirsutumL.). An experiment was conducted in Tifton, GA in 2021 and 2022, where cotton was planted in six replications of 91‐, 122‐, 152‐, and 183‐cm row spacings. Following defoliation, 1.8 m was hand harvested from each plot, and boll density plant−1and density ha−1were determined for sympodial and monopodial branches. Additional measurements included fruit and lint yield distribution assessments and intra‐boll yield components including seed cotton weight boll−1, seed index, seed boll−1, lint weight seed−1, seed surface area (SSA), fiber density, and single fiber weight. Lint yield was reduced 20% in the 183‐cm row spacing compared to the 91‐cm row spacing. The 91‐cm rows had the lowest number of sympodial bolls plant−1with 152‐ and 183‐cm rows demonstrating a 24%–28% increase in sympodial bolls plant−1. Sympodial bolls ha−1were reduced 22% in the 183‐cm row spacing compared to the 91‐cm row spacing. There were no differences in bolls ha−1or lint yield ha−1with respect to monopodial growth. There were no differences in seed cotton weight boll−1, seeds boll−1, fiber density, single fiber weight, or turnout. Seed index and SSA were increased in the 183‐cm row spacing. Lint weight seed−1was reduced in the 91‐cm row spacing. Cotton produced in 152‐ and 183‐cm row spacings produces more sympodial bolls plant−1than traditional 91‐cm rows.Sympodial bolls ha−1were reduced in 183‐cm row spacings as compared to 91‐cm row spacings.With a reduction in sympodial bolls ha−1, lint yield is sacrificed in the 183‐cm row spacing.Wide row spacing improved fruit retention but did not affect lint yield.Even with more monopodial bolls plant−1in the wider rows, there are no differences in monopodial bolls ha−1.

Yield improvement in cotton could be accelerated through selection for functional yield drivers such as interception of cumulative photosynthetically active radiation (∑IPAR), radiation use efficiency (RUE), and harvest index (HI). However, information on the extent to which these traits vary in cotton in the southeastern United States is limited. It was hypothesized that functional yield drivers would vary significantly within a diverse cotton collection. This study was conducted in Tifton and Athens, GA, and included a total of 4 site‐years. Lint yield, total biomass production, ∑IPAR, RUE, and HI were all affected by genotype. Biomass was more strongly correlated with RUE than ∑IPAR. Even among the highest yielding genotypes, values for functional yield drivers (biomass and harvest index) differed significantly, indicating that high yields could be achieved by differentially manipulating these underlying traits. However, when considered for all genotypes, only HI exhibited a significant positive correlation with yield. Boll production and intra‐boll yield components were also affected by genotype. When considered across upland genotypes, lint per boll, lint per seed, and lint percent were strongly associated with HI and lint yield, whereas boll mass and seed number per boll were not. We conclude that the genotypes evaluated in the current study achieve high lint production per boll and lint yields by manipulating different yield drivers. However, lint yield was primarily maximized through an increase in HI due to increases in boll production and within‐boll distribution of biomass to fiber, not due to increases in total biomass production or boll size. Lint yield varied significantly across a diverse collection of cotton genotypes.Maximum lint yields were achieved by manipulating different functional yield drivers.Across all upland genotypes, harvest index was most strongly associated with lint yield.Harvest index was most associated with sympodial boll numbers, fiber per boll, and fiber per seed.

Cotton (Gossypium hirsutumL.) lint yield and fiber quality are associated with various yield components. Research efforts addressing intra‐boll yield component contributors to lint production boll−1are limited. Thus, a study was conducted in Tifton, Georgia with the objectives to quantify the contributions of intra‐boll yield components to lint production boll−1and to identify yield components most strongly associated with lint production boll−1in advanced breeding lines of upland cotton. Data collected included intra‐boll yield components and fiber quality parameters. A strong association was observed between lint production boll−1and seedcotton weight boll−1(r= 0.896) compared to lint production boll−1and lint percent (LP, r= 0.574). For breeding lines with maximum lint weight boll−1, the contribution of seedcotton weight and LP ranged from 0.17 to 0.36 g boll−1and 0.22 to 0.24 g boll−1, respectively, suggesting a relatively greater influence of seedcotton weight boll−1on lint weight boll−1. Lint production boll−1can be expressed as the product of seeds per boll, seed surface area, fiber density (FD), and individual fiber weight (IFW). IFW was the greatest contributor to lint production boll−1for seven breeding lines and FD for nine breeding lines. A strong positive association was observed between lint production boll−1and IFW (r= 0.656, p< 0.001); however, no significant association between lint weight boll−1and FD suggesting a relatively greater influence of IFW on lint weight boll−1. Our work provides future direction aimed at improving lint yields through the selection of various yield components. Significant genetic differences exist for all measured parameters except seeds per boll.Seedcotton weight boll‐1has a relatively greater influence on lint weight boll‐1 compared to lint percent.Individual fiber weight has a greater influence on lint weight boll‐1compared to fiber density and seed surface area.

Success stories of wide row cotton production have generated producer interest across the cotton belt. The objective of this study was to quantify the effect of row spacing on (1) cotton growth and development and (2) lint yield and fiber quality in Georgia. The cotton cultivar Deltapine DP 1646 (Bollgard 2, XtendFlex; Bayer Crop Science) was planted in 2021 and 2022 in Tifton, GA, at row spacings of 91 cm, 122 cm, 152 cm, and 183 cm. Although canopy closure was delayed in wider row spacings compared to the 91‐cm spacing, all other crop growth and development trends did not differ among row spacings. Similarly, row spacing had no effect on the incidence of boll rot/hard lock. The 91‐cm row spacing yielded 1734 kg lint ha−1. The 183‐cm row spacing reduced yield by 15% compared with the grower's standard row spacing of 91 cm. Fiber quality parameters did not differ among row spacing treatments. Seed costs can be reduced in all wide row systems evaluated for cotton, and the 122 and 152‐cm row spacings had similar yields to the 91‐cm row spacing. However, Georgia growers produce peanuts (Arachis hypogeaL.) and corn (Zea maysL.), the most common rotational crops for cotton producers, using a 91‐cm row spacing. Consequently, the simplest transition to wide row production would be the 183‐cm spacing, which incurred yield penalties in the current study. Thus, a 91‐cm row spacing is still the most feasible option for Georgia cotton producers. Wide row cotton production has potential benefits for Georgia growers.Planting cotton on 183‐cm row spacings reduces seeding rate 50% from 91‐cm row spacings, with plant populations being reduced 46%.Canopy closure was delayed in wider row spacings compared to the grower standard.All other crop growth and development measurements were similar across four row spacings.Lint yield was reduced 15% in 183‐cm row spacings as compared to 91‐cm row spacings.

Cotton (Gossypium hirsutumL.) management decisions to abet early growth, fruit set, boll maturation, and harvest preparation are often facilitated by prediction of the date when critical developmental stages are reached. In the United States, growing degree days calculated with a base 60°F (DD60s) are commonly used to predict cotton development. Observations suggest development of modern cultivars differs from previously established guidelines. The objectives were to (1) reevaluate DD60s required for an early, mid‐maturing and late maturing cultivar to reach key growth stages across the US Cotton Belt; and (2) determine if predictions of growth stages are strengthened by optimizing base temperature or including an upper threshold by growth stage. During 2018 and 2019, 22 field trials were established in 10 states. Plant growth stages were monitored weekly and air temperature was computed from interpolated surface observations weighted by a physical, geographic model. Observed DD60s to reach growth stages varied slightly by cultivar and region (≤85 DD60s and ≤130 DD60s, respectively). Required DD60s to reach growth stages exceeded most published ranges. Optimization of base temperature and inclusion of an upper threshold by growth stage did not substantially decrease errors in predicting date of growth stage occurrence. The DD55 and DD55 with an upper threshold of 86°F calculations resulted in slightly lower errors in predicting date of growth stage occurrence than the DD60 calculation. Although guidelines should be updated, it is unlikely slight modification in base temperature or upper thresholds will drastically increase the predictive ability over the DD60 calculation. Growing degree days base 60°F (DD60s) to developmental stages are greater than previously published guidelines.Beginning at square, earlier maturing cultivars reach each developmental stage earlier than later cultivars.Optimization of base temperature did not substantially increase predictive power over the DD60 calculation.Inclusion of an upper threshold only slightly increased the predictive power over a standard DD60 calculation.

Optimizing irrigation termination time can save water and preserve lint yield and fiber quality in cotton. Although there is currently an irrigation termination recommendation in Georgia, the ideal time for termination could be influenced by cultivar differences in maturity. The hypotheses of this study were that differential irrigation termination times will affect lint yield, fiber quality, and incidence of hardlock and boll rot, and responses will be dependent on cultivar differences in maturity. In 2021 and 2022, a study was conducted in Camilla, GA, using two cotton cultivars with contrasting maturities under four irrigation termination treatments. Irrigation was terminated at cutout, first open boll, 2 weeks after first open boll, and 4 weeks after first open boll. Measurements included plant growth, cutout date, lint yield, irrigation water use efficiency (IWUE), fiber quality, and incidence of boll diseases. Gas exchange measurements and percent open boll estimates at each irrigation termination time were also conducted. Terminating irrigation at cutout did not significantly affect yield in either year; however, IWUE increased 12.6% relative to current recommendations and 13.2% relative to the latest termination time in the 2022 season. Cultivars differed significantly in cutout date, agronomic maturity, gas exchange rates, yield, hardlock/boll rot incidence, and fiber quality. However, there was no interaction between cultivar and irrigation termination time for any parameter. We conclude that irrigation can be terminated at cutout to maximize IWUE, for early and late‐maturing cultivars, without limiting yield or fiber quality, assuming a water‐replete soil profile at termination. Defining early irrigation termination times that do not penalize yield in cotton can increase water use efficiency.Terminating irrigation at cutout maximized water use efficiency in an early and a late maturing cultivar.Cultivar affected yield, fiber quality, water use efficiency, and disease incidence.

Cotton (Gossypium hirsutumL.) yield can be expressed as the product of intercepted photosynthetically active radiation (IPAR), radiation use efficiency (RUE), and harvest index (HI). Studies comparing genetic diversity in functional yield drivers for the progeny of elite breeding lines are limited or non‐existent. A field study was conducted during the 2020 and 2021 growing seasons to characterize crop development and to evaluate yield and underlying yield drivers in 16 advanced breeding lines (F7generation). Significant breeding line differences existed for lint yield, cutout date, reproductive, vegetative, and total biomass, RUE, and HI but not for IPAR. The lint yield for the lowest yielding lines was 24% lower than the highest yielding line with a lint yield of 1706 kg ha−1. Differences in RUE were not associated with single‐leaf photosynthetic rates. HI positively contributed to lint yield gain for most lines evaluated, whereas RUE was negatively correlated with lint yield for the majority of breeding lines evaluated. However, in the two highest‐yielding lines, two different strategies of yield maximization were identified. One line exhibited the earliest cutout date, reduced biomass production, low RUE, and the highest HI values, whereas the other line had the latest cutout date and produced the highest total biomass, highest RUE, and a low to intermediate HI. Breeding lines used in the current study achieved high yields by differentially manipulating underlying physiological components such as RUE, biomass accumulation, or dry matter allocation to fiber. Our work provides future direction for efforts aimed at maximizing yield through the selection for functional yield drivers. Genetic yield differences could be explained by variations in intercepted photosynthetically active radiation, use efficiency (RUE), and harvest index (HI). Breeding lines varied in lint yield, biomass, HI, and RUE.Variation in RUE was not associated with single‐leaf photosynthesis.Maximal yields are achieved by differentially manipulating underlying processes.

Rotylenchulus reniformisLinford and Oliveira (reniform nematode) infestation has been a concerning issue in the Cotton Belt region of the United States for the past decade. Reniform nematode damage is more evident on cotton compared to other row crops in US Mid‐South because they share common edaphic conditions to sustain and develop. Annual cotton (Gossypiumspp.) yield loss over the United States due to reniform nematode ranged from 1.14% to 2.37% in the past decade but exceeded 8% in the US Mid‐South States such as Mississippi. Yield losses due to nematode damage are mainly due to inconsistent control by cultural and chemical practices. In addition, there are location‐specific responses due to agronomic practices that result in its wide adaption. This review summarizes factors that influence reniform nematode infestations and the process of a plant infection, as well as management practices to mitigate nematode cotton production losses in the United States. The recent development of resistant cotton germplasm is a promising tool for reniform nematode management, although limited research has been conducted on the physiological mechanisms of resistance. In addition, understanding the role of host plant resistance and the interaction with other soilborne pathogens or abiotic stresses to control the nematode also is lacking. Future research must investigate best suited production practices specific to a region that could exploit the full potential of host plant resistance to minimize the risk of reniform nematode damage in cotton while protecting the environment. Reniform nematode caused up to 8% annual loss to cotton production in the US Mid‐South over the last decade.Chemical and cultural practices showed inconsistent control of reniform nematode damage.The recently released reniform nematode‐resistant varieties are invaluable for cotton producers, industry, and researchers.

Tall cotton plants do not necessarily produce maximum yields or quality. Growth‐promoting field conditions in the absence of chemical growth control can produce cotton plants that are extremely tall but exhibit excessive vegetative growth at the expense of reproductive growth. Cotton producers must often consider incorporating plant growth regulators (PGRs) as a part of their management decisions during the growing season. The focus of article is on the use of the PGR mepiquat chloride and the role of production environment, cultivar, and other management considerations. Earn 0.5 CEUs in Crop Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.

Lint yields and their underlying yield components can be substantially influenced by genotype and environment. Thus, the objectives of the current study were to quantify genotypic and environmental contributions to lint yield, yield components, and fiber quality in multi‐site variety trials conducted in Arkansas over a 19‐year period, to identify the traits most strongly associated with lint yield, and to quantify long‐term trends in the aforementioned traits. Annual assessments included lint yield, seeds per hectare (SPH), intra‐boll yield components, and fiber quality parameters. Production environment accounted for a higher percentage of all yield variability in 15 out of 19 years. However, four years were identified in which genotypic contributions were greater than environmental contributions. Genotype was a dominant driver of variability in lint percent, lint index, seed score, seed index, fibers per seed, fiber density, fiber length, strength, and uniformity. Production environment was the dominant driver of variability in SPH, and micronaire. Correlations between yield components and yield varied substantially from year to year, even when genotype was the primary yield driver. A regression function that utilized lint index and SPH was a stronger and more consistent indicator of genotypic variation in lint yield than any single yield component. Finally, long‐term trends show that lint percent has increased significantly over the past 19 years, whereas seed index has declined 19.6% for cotton varieties with the highest lint yields. Production environment was the main factor influencing lint yield variability, seeds per hectare, and micronaire.Genotype was dominant driver of variability in lint index, seed score, seed index, fiber density, and fibers per seed.A two‐trait function was developed that was a strong predictor of genotypic variability in yield.Lint index has increased significantly (5.3%) over the past 19 years.Seed index for the highest‐yielding genotypes has decreased 19.6% in 19 years.

Cotton (Gossypium hirsutumL.) is not only the dominant fiber crop grown worldwide, but it is also an important source of plant‐based oil and protein. Previous research has documented a significant effect of cotton cultivar and nitrogen application individually on lint yield and seed composition, but very limited studies have evaluated the lint, seed, oil, and protein yield responses of cultivars with different seed mass and composition to a broad range of N application rates. The objective of this study was to evaluate the lint, seed, oil, and protein yield responses of cultivars with different seed mass and composition to N application rates (0–168 kg N ha−1) for field‐grown cotton. A field experiment was conducted in Tifton, GA, USA during the 2019 and 2020 growing seasons that included six cultivars and six N application rates. Cultivar significantly affected seedcotton, lint, seed, and seed reserve yields in both growing seasons. Lint yield did not follow identical trends as seed yield mainly due to cultivar variation in lint percent. Similarly, protein and oil yield were influenced by cultivar variation in seed composition. Seedcotton, seed, protein, and oil yields continually increased with increases in N application from 0 to 168 kg N ha−1, whereas for lint yield, all fertilized treatments produced comparable yields that were significantly higher (68%) than the 0 kg N ha−1treatment. We conclude that variability in the distribution of photosynthates to fiber and seed as well as seed oil and protein composition can significantly alter trends in fiber, seed, and seed component yields in response to cultivar or N application rates for field‐grown cotton. Cultivar significantly affected seedcotton, lint, seed, and seed reserve yields.Lint and seed yield did not follow identical trends mainly due to variation in lint percent among the cultivars.Cultivar variation in seed composition further altered protein and oil yield responses.Seedcotton, seed, protein, and oil yields increased with increases in N application from 0 to 168 kg N ha−1.All fertilized treatments had comparable lint yields that were significantly higher than the 0 kg N ha−1treatment.

Cultivar variation in seed characteristics can affect seedling vigor, and nitrogen (N) availability influences early‐season growth in some instances. However, interactions between cultivar and N application rate for early‐season growth have received limited attention. Thus, the objectives of this research were to quantify the effects of cultivar, N‐application rate, and their interaction on early‐season growth, predict seedling vigor from plant morphology, and identify associations between early‐season crop growth rates (CGR) and other growth indices. To this end, a 2‐year (2018 and 2019) field study was conducted using six cotton cultivars having different seed characteristics and six different N‐application rates. In both years, all single‐plant and whole‐crop growth indices were affected by cultivar but not early‐season N‐application rates. A function was developed that was strongly predictive (R2= 0.78) of seedling dry weight and utilized only plant height and mainstem node assessments. Leaf area index was a strong and consistent predictor of early‐season CGR, whereas net assimilation rate was only associated with CGR in one of the 2 years. Thus, it is concluded that of the two factors assessed in the current study, cultivar is the dominant driver of seedling vigor up to 35 days after planting. Additionally, leaf area development is a more consistent driver of early‐season CGR than average assimilation rates of the canopy. In contrast, an application of N at planting did not affect seedling vigor or early‐season canopy growth in cotton. Cultivar variations in seed characteristics significantly impact seedling vigor and early‐season canopy growth.A function was developed that utilized simple plant height and node measurements to predict seedling dry weight.Leaf area index was more consistently associated with early‐season crop growth rates than net assimilation rates.At‐plant nitrogen application had no effect on seedling vigor up to 35 days after planting.

Whole‐crop growth at early season in peanuts (Arachis hypogaeaL.) can be influenced by genotype, management, and environmental conditions such as soil and air temperatures. To determine the effect of different planting conditions on peanut growth and vigor in the early season, modern peanut cultivars were planted in two growing seasons on 17 April, 10 May, and 5 June in 2017 and 25 April, 14 May, and 11 June in 2018 season, targeted to generate differences in temperature during early growth. Field measurements included emergence assessments and destructive harvest at 21 and 35 days after planting to quantify plant density, height, leaf area, and dry matter accumulation. Additionally, crop growth indices were calculated. Results showed that planting date and cultivar significantly affected plant growth parameters and derived growth indices. Planting in June resulted in greater growth parameters, crop growth rate, and leaf area index compared to April and May for both seasons. However, net assimilation rate was highest for May in 2017 and for June in 2018. Comparing cultivars, Georgia‐06G and TifNV‐high O/L were more vigorous than Georgia‐14N. Average soil and air temperatures were the highest with June planting and produced more vigorous seedling growth and greater crop growth rates than planting in April and May. Furthermore, our results suggest that the differences in the early season crop growth of modern peanut cultivars were more strongly and closely associated with leaf area development rather than specific leaf activity, that is, net assimilation rate of the canopy.

Rapid development of the first true leaf has been suggested as a key driver of seedling vigor in cotton, yet studies demonstrating an association between first true leaf physiological processes and early season cotton growth are limited. It was hypothesized that both first true leaf area (FTLA) and photosynthetic rates would be positively associated with cotton (Gossypium hirsutumand G. barbadense) seedling vigor, and that photosynthetic component processes would differ in their contribution to net photosynthesis (An) of the first true leaf. To test these hypotheses, three different cotton cultivars were planted in the 2017 and 2018 seasons on three selected dates each year to generate broad differences in seedling vigor. Growth analysis was conducted to assess seedling vigor at 3 and 5 wk after planting, and a combination of dark‐ and light‐adapted gas exchange and fluorescence measurements were performed on the first true leaf, concurrent with growth assessments. Seedling vigor was much more strongly associated with FTLA than Anon a per unit leaf area basis, suggesting that FTLA was a stronger indicator of seedling vigor. Correlation analysis between Anand a number of component processes derived from combined gas exchange and fluorescence measurements indicated that Anwas strongly correlated with electron transport rates and stomatal conductance. However, we suggest that most of the variability we observed in Anof the first true leaf was primarily driven by nonstomatal factors, since no significant correlations between Anand chloroplast CO2concentration or substomatal CO2concentration was apparent.

Cultivar and early growth conditions are known to influence seedling vigor in cotton (Gossypium hirsutumL. and Gossypium barbadenseL.). What has not been explored fully is the relative importance of physiological contributors to early season, whole‐crop growth under field conditions. It was hypothesized that variability in early season crop growth will be associated, to varying degrees, with leaf area development and whole‐canopy net assimilation rate (NAR). To test this hypothesis, three cultivars with anticipated differences in seedling vigor were planted in 2017 and 2018 on three different dates each year to generate differences in early season crop growth. For crop growth rate (CGR) and leaf area index (LAI) there was a significant interaction between cultivar and planting date in both years. In 2017, only planting date significantly affected NAR, but in 2018, planting date and cultivar main effects were observed for NAR. When considered across both years, variability in early crop growth, whether driven by cultivar or planting date, was strongly and positively associated with LAI, but only weakly associated with NAR. High early season LAI and CGR were also positively correlated with leaf area per plant but not leaf area ratio, specific leaf area, or leaf fraction. Thus, vigorous whole‐crop growth in the early season is more dependent on leaf area development than specific leaf activity.

Fiber length of cotton (Gossypium hirsutumL.) decreases under drought stress, potassium (K) could diminish the decreased caused by drought, but the mechanism associated with this alleviation effect is not clear. We evaluated the effect of K on fiber elongation using two cotton cultivars, Simian 3 and Siza 3, grown in well-watered and drought-stressed conditions. Potassium fertilizer (K2O) was applied 0, 150, or 300 kg ha−1in each growing condition. Drought stress reduced the final fiber length due to a decline in the maximum rate of rapid elongation (Vmax, mm day−1). The application of K alleviated the drought-induced fiber length reduction by increasing Vmax. At 10 and 15 days post-anthesis (DPA), drought significantly reduced osmotic potential (OP) and increased K+and malate contents at all K rates, relative to well-watered conditions, which was associated with increased activities of phosphoenolpyruvate carboxylase (PEPC), V-ATPase, PPase, and PM H+-ATPase in cotton fiber. However, the relative contribution of K+and malate to OP declined under drought in comparison with well-watered condition. Compared with control without K, K application decreased OP and increased the accumulation of osmolytes (K+, malate and soluble sugar) as well as the activities of related enzymes in fiber irrespective of water treatments. Moreover, K application increased osmotic adjustment during drought, and improved the contribution of K+and malate to OP, especially under drought stress. This study showed that drought decreased fiber length by reducing Vmax, and K application ameliorates the decline in fiber elongation due to drought by enhancing osmolytes accumulation and their contribution to OP in fiber cells.

There was little interaction between tillage and irrigation on agronomic parameters.Excessive rainfall minimized agronomic benefits of the rolled rye cover crop.Continuous experiments are likely optimal to properly evaluate cover crop systems. Concerns surrounding agricultural water use have increased interest in investigating more efficient cotton (Gossypium hirsutumL.) production practices. A study was conducted to determine potential water savings from using a conservation tillage system employing a cereal rye (Secale cerealeL.) cover crop. The performance of early and late maturing cotton cultivars was assessed in two tillage systems, conventional or strip tillage with a rye cover crop, under various irrigation levels (100, 75, and 50% of University of Georgia recommendations, and non‐irrigated) to determine the effect of crop growth, development, and yield in Camilla, GA (2013 and 2014), Moultrie, GA (2014), and Vienna, GA (2014). At Camilla, increases in irrigation typically benefited the cotton crop regardless of tillage treatment; however, there was little difference between the two highest irrigation treatments, suggesting that application rates <100% recommendations could result in water savings. During 2013, excessive rainfall resulted in minimal soil moisturedifferences; subsequently, cotton growth, development, and yield were negatively impacted under strip tillage compared with conventional. Although almost half the rainfall was received in 2014 compared with 2013, and the conservation tillage system benefited crop growth and development, no yield differences were observed. At Moultrie and Vienna, either no difference between tillage systems or only benefits to crop growth and development in the conventional tillage system occurred. Results illustrate that the potential impact of cover crops is highly dependent on environmental conditions and is likely minimal under slight to moderate water deficit conditions, but can be detrimental when excessive rainfall occurs.

The current study evaluated the possibility that growth‐limiting, early‐season drought stress sufficient to decrease net photosynthesis (AN) would be associated with declines in stomatal conductance (gs) and ATP content, regardless of stress level. Studies were conducted in greenhouse facilities in Athens and Tifton, GA, and imposed different early‐season drought durations to generate a range of early‐season water‐deficit stress conditions. The early‐season drought durations imposed decreased ANto values ranging from 20 to 60% of the levels observed in well‐watered plants. Where declines in ANwere observed, gsand photosynthetic electron transport rate (ETR) declined substantially, indicating some level of metabolic and possibly diffusional limitation to photosynthesis. The ATP content was unaffected or actually increased in response to photosynthesis‐limiting drought in both years of the study, suggesting that ATP‐induced limitations to photosynthesis are minimal over a broad range of AN–limiting, early‐season drought stress conditions in cotton (Gossypium hirsutumL.). All drought durations limited leaf, stem, reproductive, and total dry matter production. Declines in dry matter under mild stress were primarily associated decreased leaf area production, whereas decreased ANwas likely an important contributor under more severely stressed treatments. Photosynthetic declines under growth‐limiting, early‐season drought do not appear to be associated with reduced ATP production, as suggested in other plant species.

Producers need to know the contributions of genotype, environment, and their interaction (G×E) in determining cotton (Gossypium hirsutumL.) lint yield, lint percentage, and fiber quality. The recent introduction of longer upper half mean length (UHML) fiber, lower micronaire cultivars may alter previously defined contributions. The objectives of this research were to define the genotype, environment, and G×E contributions to lint yield, lint percentage, and fiber quality from common cultivars evaluated within the US Mid‐South and define shifts in these contributions caused by the introduction of a longer UHML, lower micronaire cultivar. Data from 102 large‐plot trials within Alabama, Arkansas, Louisiana, Mississippi, Missouri, and Tennessee were compiled from the 2015 and 2016 seasons; 85 site‐years contained three common cultivars, and 69 contained four common cultivars. Analysis of three common cultivars within the 69‐site‐year dataset indicated environment dominated factors of lint yield (85.8%), lint percentage (88.5%), micronaire (70.9%), length (70.5%), and uniformity (70.4%). Large increases in the contribution of genotype to micronaire (26.0%) and length (37.6%) were observed when the lower micronaire, longer UHML cultivar was included. The relatively minor role of cultivar in determining lint yield and the substantial role of cultivar in determining micronaire and length suggest that producers within the Mid‐South should begin to place more importance on fiber quality data when selecting cultivars.

Grain development is the final and most critical growth stage in wheat life cycle. During this phase, developing grains accumulate energy reserves to form the economic yield of the crop and staple for the humanity. Grain development is severely influenced by environmental stresses. For example, drought during this phase primarily reduces grain size formation as well as the rate, duration, and quality of grain filling, resulting in impaired grain formation and substantial yield losses. Extensive yield loss due to post-anthesis drought in wheat is mainly attributed to enhanced flag leaf senescence, suppressed carbon assimilation, and poor remobilization. These result in source-deprived grain filling, imbalanced production of growth hormones, and altered enzyme activities involved in carbon metabolism in both source and sink organs of the plant. Therefore, improving tolerance to drought stress, especially during reproductive period, has become target for increasing yield sustainability in drought-prone areas of wheat cultivation. Some recent studies in different crop species explore an intriguing possibility of developing stress tolerance in plants through the preexposure of plants to stress conditions, referred to as “priming.” Studies show that plants can perceive and accrue information about earlier experiences and recall this information to respond to later environmental challenges. Recently, priming strategy has gained a great attention in plant stress physiology due to its feasibility, efficiency, and cost- and labor-effectiveness. In this chapter, we accumulated the information about the role of pre-drought priming to sustain grain development under post-anthesis drought stress by regulating carbon assimilation, translocation, leaf senescence, grain size initiation, grain filling, levels of growth hormones, and activities of enzyme related to grain development. In addition, recent advances made in prestress priming for improving tolerance against a range of environmental stresses in different crop species are also discussed in this chapter.

This study addressed the potential of reduced prebloom irrigation, referred to as primed acclimation (PA), to increase agricultural water‐use efficiency (WUE) using a soil‐moisture‐based irrigation scheduling system in cotton (Gossypium hirsutumL.). To address this, a study was conducted near Camilla, GA, under a variable‐rate, center‐pivot irrigation system using a Watermark‐based automated soil moisture sensing approach to measure soil water potential (SWP) and impose varying irrigation scheduling treatments during the prebloom stage of development. Early season thresholds were −20 (Treatment 1), −40 (Treatment 2), −70 (Treatment 3), to −100 kPa (Treatment 4) prior to flowering. Reductions in prebloom irrigation of up to 17% were noted in this study for the driest thresholds (−100 kPa) with no reduction in lint yield relative to the −20 and −40 kPa thresholds. In some cases, prebloom irrigation was eliminated completely in the drier prebloom threshold treatments with no appreciable yield reductions. In rainfed treatments, episodic drought during flowering (2014) limited plant growth and node production, hastened cutout, decreased boll numbers per plant, produced a more compact boll distribution on the plant, and decreased yield and WUE relative to irrigated treatments. In contrast, season‐long rainfed treatments exhibited the highest WUE in 2015 (a wet season). The results of this study conclude that prebloom irrigation thresholds between −70 and −100 kPa appear to be viable for use in a sensor‐based PA irrigation scheduling system, whereas episodic drought coinciding with flowering represents a major threat to yield stability and WUE for cotton production in the southeastern United States.

To address the effectiveness of predawn leaf water potential in plant‐based irrigation scheduling, Gossypium hirsutumL. plants were grown under fully irrigated and dryland conditions and under three predawn water potential (ΨPD) thresholds (−0.5, −0.7, and −0.9 MPa). Measurements included ΨPD, plant height, mainstem node number, lint yield, water productivity, and continuous crop canopy temperature. We found that ΨPDproduced similar yields to current practices, while decreasing overall water use from 7 to 31%, depending on rainfall levels and the treatment utilized. When considered across both years of the study (2013 and 2014), using a −0.5‐MPa ΨPDirrigation threshold consistently resulted in less irrigation applied than the checkbook method and maximum water productivity and lint yield. Using a well‐watered baseline developed in 2013 for canopy temperature versus vapor pressure deficit, we calculated a crop water stress index (CWSI) that exhibited a very strong, nonlinear relationship with season average ΨPDvalues between approximately −0.4 and −0.7 MPa (r2= 0.81). A strong, nonlinear relationship was also seen between CWSI and lint yield (r2= 0.81). Predawn water potential appears to be an effective means of determining the need for irrigation in cotton, and in the current study, yield and water productivity were maximized at a season‐long average ΨPDthreshold of −0.5 MPa. Furthermore, when calibrated using ΨPD–based irrigation triggers, canopy‐temperature derived CWSI appears to be a promising tool for future automated plant‐based irrigation scheduling in the southeastern United States.

Heat stress can reduce crop yield or even cause total crop failure. The ability to predict heat stress in advance would allow growers time to implement protective measures, helping to avoid such losses. This study presents a strategy for producing probabilistic heat stress forecasts for well‐watered cotton (Gossypium hirsutumL.) in the Camilla, GA, region. Multiple linear regression was used to develop a cotton canopy temperature model based on predicted air temperature, humidity, solar radiation, and wind speed. The European Centre for Medium‐Range Weather Forecasts Ensemble Prediction System was used to predict the meteorological variables used in the canopy temperature model, which produced 10‐d probabilistic canopy temperature forecasts for each day of observations during 2014. A statistical mean bias correction was applied to improve on the raw model forecasts. The forecasts were found to be skillful, with relative operating characteristic areas greater than 0.5. The bias‐corrected forecasts were found to increase skill. A heat stress warning system was then created using the forecasts. Additionally, an economic analysis was performed as an example of how probabilistic forecasts can be used to aid producers with financial decisions pertaining to weather‐related risks. Creating heat stress advisories for crops provide growers time to protect assets.Coupling crop and atmospheric models translates weather data into usable information for growers.Probabilistic canopy temperature forecasts can be used to evaluate on‐farm weather‐related risks.

Experiments conducted from 2007 to 2012 evaluated the genotype × environment effects on breeder seed of eight peanut (Arachis hypogaeaL.) cultivars grown under similar production practices. Seed germination and vigor by plot replication were evaluated in Petri‐dishes incubated over a thermal gradient ranging from 12 to 36°C at approximately 1.0°C increments. Growing degree day (GDD) accumulation for each temperature increment was calculated based on daily mean temperature measured by thermocouples. Lorentzian distribution models were used to establish the temperature and time (hours) to maximum germination. With respect to maximum germination and temperature; Georgia‐07W (23.9°C) < Florida‐07 (25.0°C) < Georgia Greener (25.2°C) < Georgia‐06G (25.3°C) = Tifguard < Georgia Green (26.4°C) < Georgia‐09B (27.1°C) = Georgia‐02C. Nonlinear regression indices from logistic growth curves with three parameters were used to elucidate seed germination by cultivar. These data included maximum indices of germination for each cultivar by year establishing parameter estimates using nonlinear regression, GDD value at 80% germination (Germ80), and temperature required by each cultivar for optimum germination. Peanut cultivar vigor varied by year with respect to overall GDDs to reach Germ80and maximum germination (b0). Ranking of cultivars by GDD to reach Germ80were: Georgia Green < Georgia‐02C < Georgia‐06G = Georgia Greener < Georgia‐09B < Georgia‐07W < Tifguard < Florida‐07. This indicates that Georgia Green had much greater vigor than Florida‐07 over the course of the experiments. Georgia‐06G peanut seed were consistent with respect to germination, Germ80, and b0. All cultivars exhibited phenotypic variation by year, with genotype consistency across years. Core IdeasPeanut cultivars evaluated exhibited phenotypic vigor variation by year, with genotypic stability across years.This form of evaluation provided an indication of vigor which may assist breeders in determining the success of the cultivar over a range of temperatures.Larger seeded peanut cultivars exhibited less vigor than smaller seeded cultivars. Peanut cultivars evaluated exhibited phenotypic vigor variation by year, with genotypic stability across years. This form of evaluation provided an indication of vigor which may assist breeders in determining the success of the cultivar over a range of temperatures. Larger seeded peanut cultivars exhibited less vigor than smaller seeded cultivars.

Reproductive development in sexual plants is substantially more sensitive to high temperature stress than vegetative development, resulting in negative implications for food and fiber production under the moderate temperature increases projected to result from global climate change. High temperature exposure either during early pollen development or during the progamic phase of pollen development will negatively impact pollen performance and reproductive output; both phases of pollen development are considered exceptionally sensitive to moderate heat stress. However, moderately elevated temperatures either before or during the progamic phase can limit fertilization by negatively impacting important pollen pistil interactions required for successful pollen tube growth toward the ovules. This mini-review identifies the impacts of heat stress on pollen-pistil interactions and sexual reproduction in angiosperms. A special emphasis is placed on the biochemical response of the pistil to moderately high temperature and the resultant influence on in vivo pollen performance and fertilization.