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Drought stress and nitrogen (N) deficiency are important abiotic stresses that severely limit net photosynthetic rate (AN). A number of studies have investigated the underlying physiological limitations to AN in response to water deficit or N deficiency; however, the relative sensitivities of photosynthetic component processes and carbon loss processes to combined drought and N deficiency in field‐grown cotton (Gossypium hirsutum L.) have not been explored. Therefore, the objective of the present study was to determine the effects of combined water deficit and nitrogen deficiency on the underlying physiological processes driving AN in field‐grown cotton. Water‐deficit stress caused substantial reductions in AN, but reductions in AN were greater under optimum N conditions (74%) than under N deficiency (22%). Decreased CO2 diffusion, RuBP regeneration, and Rubisco carboxylation were major contributors to a decline in AN due to water‐deficit stress. Reductions in Rubisco carboxylation and RuBP regeneration were the greatest drivers of N deficiency‐induced decline in AN. Lower CO2 diffusion and Rubisco carboxylation were main constraints to AN due to combined water deficit and N deficiency. Regarding carbon loss processes, both dark respiration and photorespiration under water‐deficit stress or N deficiency, and only photorespiration under combined water deficit and N deficiency, contributed to declines in AN. Increased non‐photochemical quenching and/or photorespiration prevented photoinhibition of photosystem II under stress conditions. Overall, response of photosynthesis to water‐deficit stress was dependent on N availability, and rate‐limiting physiological processes contributing to declines in AN were dependent on the type of prevailing stress. Core Ideas: Response of photosynthesis to water‐deficit stress was dependent on nitrogen rate.CO2 diffusion, RuBP regeneration, and Rubisco carboxylation were major limitations to photosynthesis under water deficit.Rubisco carboxylation and RuBP regeneration co‐limited photosynthesis under nitrogen deficiency conditions.CO2 diffusion and Rubisco carboxylation limited photosynthesis under combined water deficit and nitrogen deficiency.Non‐photochemical quenching and/or photorespiration prevented photodamage to photosystem II under stress conditions. [ABSTRACT FROM AUTHOR]

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 shortterm 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 hirsutum L.) 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 [ABSTRACT FROM AUTHOR]

With grower interest in skip and wide row cotton systems, varietal performance in such systems has become a major question. An experiment was conducted in 2022 and 2023 in Tifton and Midville, GA, evaluating three row arrangements (standard 91‐cm row spacing, 2 × 1 skip row, and 183‐cm row spacing or wide row) and four commercially available varieties (Stoneville [ST] 5091 Bollgard 3 Xtendflex [B3XF], Phytogen [PHY] 400 Widestrike 3 Roundup Flex Enlist [W3FE], DynaGro [DG] 3799 B3XF, and Deltapine [DP] 1840 B3XF). There were no interactions between variety and row arrangement for any response variable, indicating the best variety for standard row spacings would also be the best variety in alternative row arrangements. Plant populations were reduced 32% and 53% in 2 × 1 skip‐row and wide‐row systems, respectively, compared to standard row arrangements, which accomplishes the major goal of these systems in reducing seed cost. Boll rot and hard lock were reduced in wide row treatments only, which could benefit cotton growers in the lower Southeast. However, reductions in lint yield were associated with 2 × 1 skip row (all site years) and wide row arrangements (three out of four site‐years) compared to the grower standard. Differences among varieties were observed in plant heights, lint yield, and fiber quality, which is to be expected. These results confirm much of the work conducted on skip and wide row cotton systems and indicate that for growers in the lower Southeast to achieve maximum lint yields, standard row arrangements are superior to alternative row arrangements. Core Ideas: Cotton growers remain interested in skip‐ and wide‐row systems to reduce input costs.Plant population was reduced 32% and 53% in 2 × 1 skip and wide row treatments, respectively.Boll rot and hard lock was reduced in wide row arrangements, but not in 2 × 1 skip row treatments.In all four site‐years, lint yield was reduced in 2 × 1 skip row arrangements by 14%–32%.In three out of four site‐years, lint yield was reduced in wide row arrangements by 13%–31%. [ABSTRACT FROM AUTHOR]

Understanding the complex interactions between genotype-environment dynamics is fundamental for optimizing crop improvement. However, traditional phenotyping methods limit assessments to the end of the growing season, restricting continuous crop monitoring. To address this limitation, we developed a methodology for spatiotemporal registration of time-series 3D point cloud data, enabling field phenotyping over time for accurate crop growth tracking. Leveraging multi-scan terrestrial laser scanning (TLS), we captured high-resolution 3D LiDAR data in a cotton breeding field across various stages of the growing season to generate fourdimensional (4D) crop models, seamlessly integrating spatial and temporal dimensions. Our registration procedure involved an initial pairwise terrain-based matching for rough alignment, followed by a bird's-eye view adjustment for fine registration. Point clouds collected throughout nine sessions across the growing season were successfully registered both spatially and temporally, with average registration errors of approximately 3 cm. We used the generated 4D models to monitor canopy height (CH) and volume (CV) for eleven cotton genotypes over two months. The consistent height reference established via our spatiotemporal registration process enabled precise estimations of CH (R² = 0.95, RMSE = 7.6 cm). Additionally, we analyzed the relationship between CV and the interception of photosynthetically active radiation (IPARf), finding that it followed a curve with exponential saturation, consistent with theoretical models, with a standard error of regression (SER) of 11%. In addition, we compared mathematical models from the Richards family of sigmoid curves for crop growth modeling, finding that the logistic model effectively captured CH and CV evolution, aiding in identifying significant genotype differences. Our novel TLS-based digital phenotyping methodology enhances precision and efficiency in field phenotyping over time, advancing plant phenomics and empowering efficient decision-making for crop improvement efforts. [ABSTRACT FROM AUTHOR]

This study quantifies the effects of wide row spacing on lint yield, yield components, and fiber quality of upland cotton (Gossypium hirsutum L.). 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−1 and density ha−1 were 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−1 with 152‐ and 183‐cm rows demonstrating a 24%–28% increase in sympodial bolls plant−1. Sympodial bolls ha−1 were reduced 22% in the 183‐cm row spacing compared to the 91‐cm row spacing. There were no differences in bolls ha−1 or lint yield ha−1 with 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−1 was reduced in the 91‐cm row spacing. Core Ideas: Cotton produced in 152‐ and 183‐cm row spacings produces more sympodial bolls plant−1 than traditional 91‐cm rows.Sympodial bolls ha−1 were 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−1 in the wider rows, there are no differences in monopodial bolls ha−1. [ABSTRACT FROM AUTHOR]

In this study, we investigated the potential involvement of endogenous viral elements (EVEs) in the development of apical tissue necrosis, resulting in the terminal abortion of upland cotton (Gossypium hirsutum L.) in Georgia. The high-throughput sequence analysis of symptomatic and asymptomatic plant tissue samples revealed near-complete EVE-Georgia (EVE-GA) sequences closely related to caulimoviruses. The analysis of EVE-GA's putative open reading frames (ORFs) compared to cotton virus A and endogenous cotton pararetroviral elements (eCPRVE) revealed their similarity in putative ORFs 1–4. However, in the ORF 5 and ORF 6 encoding putative coat protein and reverse transcriptase, respectively, the sequences from EVE-GA have stop codons similar to eCPRVE sequences from Mississippi. In silico mining of the cotton genome database using EVE-GA as a query uncovered near-complete viral sequence insertions in the genomes of G. hirsutum species (~7 kb) but partial in G. tomentosum (~5.3 kb) and G. mustelinum (~5.1 kb) species. Furthermore, cotton EVEs' episomal forms and messenger RNA (mRNA) transcripts were detected in both symptomatic and asymptomatic plants collected from cotton fields. No significant yield difference was observed between symptomatic and asymptomatic plants of the two varieties evaluated in the experimental plot. Additionally, EVEs were also detected in cotton seeds and seedlings. This study emphasizes the need for future research on EVE sequences, their coding capacity, and any potential role in host immunity or pathogenicity. [ABSTRACT FROM AUTHOR]

Cotton is well adapted to dry areas, but progressive water deficits can lead to declines in net photosynthesis (A), ultimately reducing yield. However, the exact mechanism responsible for this decline in net photosynthesis (stomatal or non‐stomatal) is not fully understood under field conditions, partially due to limitations in the ability to collect critical data. To our knowledge, no other study has compared the drought responses of Pima and upland cotton using both CO2 response and chlorophyll fluorescence under field conditions. To this end, a field study was conducted to quantify the impact of progressive mild drought, as measured by midday stomatal conductance to water vapour (gs), on cotton leaf metabolism in Pima and upland cotton. Survey gas exchange and rapid photosynthetic CO2 response (RACiR) were conducted during flowering on the same leaf. The study observed decline in A as gs declined for both species. Correlation analysis indicated typical relationships with A and parameters associated with stomatal limitations such as decreased CO2 inside the leaf and at the site of carboxylation; however, it was found that while Pima exhibited a strong relationship between maximum electron transport rate (Jmax) and electron transport rate (ETR), upland cotton did not. Furthermore, when ETR is broken down into proportions contributing to net photosynthesis and photorespiration (ETRA, ETRP, respectively), we found that a greater proportion of ETR is being shuttled to the photorespiratory pathway in upland, relative to Pima as gs decreases. Our results fill critical knowledge gaps that can be useful for modellers and breeders when preparing for future climate change scenarios. [ABSTRACT FROM AUTHOR]

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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Water deficit stress limits net photosynthetic rate (AN), but the relative sensitivities of underlying processes such as thylakoid reactions, ATP production, carbon fixation reactions, and carbon loss processes to water deficit stress in field-grown upland cotton require further exploration. Therefore, the objective of the present study was to assess (1) the diffusional and biochemical mechanisms associated with water deficitinduced declines in AN and (2) associations between water deficit-induced variation in oxidative stress and energy dissipation for field-grown cotton. Water deficit stress was imposed for three weeks during the peak bloom stage of cotton development, causing significant reductions in leaf water potential and AN. Among diffusional limitations, mesophyll conductance was the major contributor to the AN decline. Several biochemical processes were adversely impacted by water deficit. Among these, electron transport rate and RuBP regeneration were most sensitive to AN-limiting water deficit. Carbon loss processes (photorespiration and dark respiration) were less sensitive than carbon assimilation, contributing to the water deficit-induced declines in AN. Increased energy dissipation via non-photochemical quenching or maintenance of electron flux to photorespiration prevented oxidative stress. Declines in AN were not associated with water deficit-induced variation in ATP production. It was concluded that diffusional limitations followed by biochemical limitations (ETR and RuBP regeneration) contributed to declines in AN, carbon loss processes partially contributed to the decline in AN, and increased energy dissipation prevented oxidative stress under water deficit in field-grown cotton. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium hirsutum L.) lint yield and fiber quality are associated with various yield components. Research efforts addressing intra‐boll yield component contributors to lint production boll−1 are 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−1 and to identify yield components most strongly associated with lint production boll−1 in 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−1 and seedcotton weight boll−1 (r = 0.896) compared to lint production boll−1 and 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−1 and 0.22 to 0.24 g boll−1, respectively, suggesting a relatively greater influence of seedcotton weight boll−1 on lint weight boll−1. Lint production boll−1 can 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−1 for seven breeding lines and FD for nine breeding lines. A strong positive association was observed between lint production boll−1 and IFW (r = 0.656, p < 0.001); however, no significant association between lint weight boll−1 and 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. Core Ideas: Significant genetic differences exist for all measured parameters except seeds per boll.Seedcotton weight boll‐1 has a relatively greater influence on lint weight boll‐1 compared to lint percent.Individual fiber weight has a greater influence on lint weight boll‐1 compared to fiber density and seed surface area. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium hirsutum L.) 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 (F7 generation). 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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Copyright of Agronomy Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Agronomy Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Agronomy Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cotton (Gossypium hirsutum L.) is a major fiber crop; however, cotton yields are often limited due to its extreme sensitivity to environmental stress such as high temperature and drought. The current project was designed to evaluate the use of the plant growth regulator 1-methylcyclopropene (1-MCP) to alleviate the adverse effect of environmental stress on cotton yields. Three field studies were conducted in Arkansas in 2006 and 2007. An untreated control was compared with 1-MCP at 10 g ai ha-1 applied at first flower (FF), and another applied at FF and again two weeks later. Measurements were made of boll weight, boll number and yield, as well as on plant physiological and biochemical responses. During the period of cotton fruit development, the maximum temperatures for Marianna, AR in 2006 and 2007 were well above the optimum 30oC temperature for cotton growth, indicating that cotton was under heat stress. Plants that received 1-MCP at FF and FF+2 weeks had significantly higher seed cotton and lint yields than the untreated control. This result was possibly due to a significant weight increase in 1-MCP treated bolls located in the middle of the plant canopy as no effect was observed on cotton fruit abscission. Applications of 1-MCP significantly decreased the stress levels of cotton plants as indicated by higher maximum quantum efficiency of Photosystem II and lower activity of the leaf antioxidant glutathione reductase. No 1-MCP effect on protein and malondialdehyde content in leaves was observed. The study showed that foliar application of 1-MCP has the potential to improve yields due to reduced plant stress. [ABSTRACT FROM AUTHOR]

Lint yield in cotton is governed by light intercepted by the canopy (IPAR), radiation use efficiency (RUE), and harvest index (HI). However, the conventional methods of measuring these yield-governing physiological parameters are labor-intensive, time-consuming and requires destructive sampling. This study aimed to explore the use of low-cost and high-resolution UAV-based RGB and multispectral imagery 1) to estimate fraction of IPAR (IPARf), RUE, and biomass throughout the season, 2) to estimate lint yield using the cotton fiber index (CFI), and 3) to determine the potential use of biomass and lint yield models for estimating cotton HI. An experiment was conducted during the 2021 and 2022 growing seasons in Tifton, Georgia, USA in randomized complete block design with five different nitrogen treatments. Different nitrogen treatments were applied to generate substantial variability in canopy development and yield. UAV imagery was collected bi-weekly along with light interception and biomass measurements throughout the season, and 20 different vegetation indices (VIs) were computed from the imagery. Generalized linear regression was performed to develop models using VIs and growing degree days (GDDs). The IPARf models had R2 values ranging from 0.66 to 0.90, and models based on RVI and RECI explained the highest variation (93%) in IPARf during cross-validation. Similarly, cotton above-ground biomass was best estimated by models from MSAVI and OSAVI. Estimation of RUE using actual biomass measurement and RVI-based IPARf model was able to explain 84% of variation in RUE. CFI from UAV-based RGB imagery had strong relationship (R2 = 0.69) with machine harvested lint yield. The estimated HI from CFI-based lint yield and MSAVI-based biomass models was able to explain 40 to 49% of variation in measured HI for the 2022 growing season. The models developed to estimate the yield-contributing physiological parameters in cotton showed low to strong performance, with IPARf and above-ground biomass having greater prediction accuracy. Future studies on accurate estimation of lint yield is suggested for precise cotton HI prediction. This study is the first attempt of its kind and the results can be used to expand and improve research on predicting functional yield drivers of cotton. [ABSTRACT FROM AUTHOR]

Rotylenchulus reniformis Linford 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 (Gossypium spp.) 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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Taxonomy:Cotton leafroll dwarf virus (CLRDV) is a member of the genus Polerovirus, family Solemoviridae. Geographical Distribution: CLRDV is present in most cotton‐producing regions worldwide, prominently in North and South America. Physical Properties: The virion is a nonenveloped icosahedron with T = 3 icosahedral lattice symmetry that has a diameter of 26–34 nm and comprises 180 molecules of the capsid protein. The CsCl buoyant density of the virion is 1.39–1.42 g/cm3 and S20w is 115–127S. Genome: CLRDV shares genomic features with other poleroviruses; its genome consists of monopartite, single‐stranded, positive‐sense RNA, is approximately 5.7–5.8 kb in length, and is composed of seven open reading frames (ORFs) with an intergenic region between ORF2 and ORF3a. Transmission: CLRDV is transmitted efficiently by the cotton aphid (Aphis gossypii Glover) in a circulative and nonpropagative manner. Host: CLRDV has a limited host range. Cotton is the primary host, and it has also been detected in different weeds in and around commercial cotton fields in Georgia, USA. Symptoms: Cotton plants infected early in the growth stage exhibit reddening or bronzing of foliage, maroon stems and petioles, and drooping. Plants infected in later growth stages exhibit intense green foliage with leaf rugosity, moderate to severe stunting, shortened internodes, and increased boll shedding/abortion, resulting in poor boll retention. These symptoms are variable and are probably influenced by the time of infection, plant growth stage, varieties, soil health, and geographical location. CLRDV is also often detected in symptomless plants. Control: Vector management with the application of chemical insecticides is ineffective. Some host plant varieties grown in South America are resistant, but all varieties grown in the United States are susceptible. Integrated disease management strategies, including weed management and removal of volunteer stalks, could reduce the abundance of virus inoculum in the field. [ABSTRACT FROM AUTHOR]