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Background water shortage is the greatest significant reason controlling crop yield that harmfully affects fruit production, boll shedding, lint yield and fiber properties quality in cotton plants. Objectives: this study was carried out at Sakha Agricultural Research Station, Kafr El-Sheikh, Agric. Res. Center, Egypt, during 2014 and 2015 growing seasons. A study was undertaken in cotton (G. barbadense L.) to detect the magnitude of genetic divergence among parental cotton genotypes and their F1s cross combinations and to select most suitable combinations for tolerant water deficient. Results and conclusion: the data showed that the first eight main principal components with eigen value more than one are extracted from the complicated components, the total cumulative variance of these eight factors amount for about 85.28% of the total multivariate variance. Suggesting that these PCA scores might be used to summarize the original variables in any further analysis of the data. The female parent 10,229 formed wide cluster having wide divergent distance from the other groups. On the same trend, the extra-long varieties Giza 96 and Giza 45 formed unique groups, cluster number 8 and cluster 1 nearly related. Cluster number 7 and cluster 4 which consisted of two genotypes for each characterized by susstable to water deficit conditions. The cross combinations Giza 77 x Dandra, Giza 77 x Pima S6, Giza 96 x Australy and Minufy x Dandra grouped at the same cluster, however the cross combinations Giza 86 x Dandra and Giza 68 × 10,229 classified into two different clusters. The data revealed that the inter cluster distance was higher than the intra cluster, indicating wide genetic divergent among the studied genotypes. Principal components analysis is useful in identifying and most influential characters affecting genetic variation of population.

Water stress is a critical abiotic stress for plant reduction in arid and semiarid zones and, has been discovered to be detrimental to the development of seedlings as well as the growth and physiological characteristics of many crops such as cotton. The objectives of our study were to determine the combining ability and genetic components for five quantitative traits [(leaf area (LA), leaf dry weight (LDW), plant height (PH), fiber length (2.5 percent SL), and lint cotton yield/plant (LCY/P)] under water shortage stress, a half diallel cross between six cotton genotypes representing a wide range of cotton characteristics was evaluated in RCBD with four replications. The genotype mean squares were significant for all traits studied, demonstrating significant variation among genotypes for all characters under water shortage stress. LCY/P had the highest phenotypic and genotypic correlation co-efficient with PH, LDW, and LA shortage. The highest direct effect on lint cotton yield was exhibited by leaf area (3.905), and the highest indirect effects of all traits were through LA, with the exception of 2.5 percent SL, which was through LDW. The highest dissimilarity (Euclidean Distance) between parental genotypes was between G.87 and G.94, followed by G.87 and Menoufi. G.94 was also a well-adapted genotype, and the combinations G.87 x G.94 and G.87 x Menoufi may outperform their parents. The combining ability analysis revealed highly significant differences between parental GCA effects and F1 crosses SCA effects. The variation of GCA and SCA demonstrated the assurance of additive and non- additive gene action in the inheritance of all traits studied. In terms of general combining ability (GCA) effects, parental genotype G.94 demonstrated the highest significant and positive GCA effects for all traits studied, with the exception of 2.5 percent SL, where G.87 revealed the highest significant and positive GCA effects. The effects of specific combining ability (SCA) revealed that the cross (G.87 x2G.94) revealed stable, positive, and significant SCA for all of the studied traits.

Naturally colored cotton fiber is environment-friendly but has monotonous color and poor fiber quality. Identification of green fiber or fuzz genes would aid in investigating the biosynthesis of green pigments in cotton fibers. In this study, we established a mapping population and found that the Lgf trait (white lint and green fuzz) from Gossypium hirsutum race latifolium is controlled by an incompletely dominant gene. The Lgf locus was mapped to a 71-kb interval on chromosome 21 containing seven genes, including a transcription factor with similarity to Arabidopsis MYB9. Harboring 13 SNPs and a 4-bp insertion/deletion in its promoter, GhMYB9 was highly up-regulated in the critical period for green pigment development in fuzz. Virus-induced gene silencing of GhMYB9 in a green-fuzz accession of G. hirsutum race latifolium TX-41 conferred white or light green fuzz. These results suggest that GhMYB9 is an important contributor to green pigments in cotton fiber and shed light on the regulatory mechanism controlling green pigmentation.

Potassium (K) being the major limiting factor affecting cotton yield and quality has received massive research attention and the effects of various K fertilization techniques/organic amendments have been studied extensively. However, it is not clear whether the straw based, high pH biochar affects K availability, lint yield and quality of the cotton crop in alkaline calcareous soils. In the present study, we carried out a field experiment on a moderate to strongly calcareous silt loam soil to demonstrate the effect of straw-based biochar and potassium application levels on the growth, seed cotton yield and the lint quality. The experimental treatments comprised of two factors, A) biochar types i) Control no biochar, ii) Rice husk biochar (RHB), iii) Wheat straw biochar (WSB), and iv) Rice straw biochar (RSB), factor B) potassium application levels (i) control, no K fertilizer application, ii) K at 15 kg ha−1, and iii) K at 30 kg ha−1 (4 × 3 × 3, n = 36). Results showed that overall cotton growth and yield was significantly improved with increasing rates of potassium application. Three biochar sources affected seed cotton yield and quality with varying effects. For instance, the RSB increased plant height (11.71% to 22.47%), number of bolls per plant (0.74% to 13.75%), average boll weight (35.44% to 36.22%), the seed cotton yield was increased by 14.48% over the control when rice straw biochar was applied in combination with potassium at 30 kg ha−1. However, the ginning out turn (%) was declined with potassium application in combination with all three-biochar compared to control (no biochar addition). The WSB increased staple length and micronaire by 4.32% and 24.50% without potassium application. The potential effects of straw based biochar and potassium application on seed cotton yield and quality deserve further studies to identify the most suitable biochar as per soil chemical properties.

Cotton producers have substantially reduced their inputs (labor, nutrients, and management) mainly by adopting a short-season cropping management that is characterized by late sowing, high density, and reduced fertilization with one-time application at the first bloom stage without lint yield reduction. However, it has been hypothesized that one-time fertilization at an earlier growth stage could be a more effective and economic management practice. A two-year field experiment was conducted by applying five fertilizer one-time fertilization at 0 (FT1), 5 (FT2), 10 (FT3), 15 (FT4), and 20 (FT5) days after the first flower appeared in the field and one three-split fertilizer application taken as the conventional control (FT6), making six treatments altogether. Cotton growth period, biomass accumulation, yield, and its formation were quantified. The results showed that the one-time fertilization did not affect the cotton growth progress as compared to FT6, however, the total crop cycles for FT3–FT5 were 3 days shorter. FT1 produced the highest cotton lint yield (1 396 kg ha−1), which was similar to the FT6 but higher than the other treatments, and could be attributed to more bolls per unit area and higher lint percentage. Cotton yield was positively correlated with cotton plant biomass accumulated. FT1 had both the highest average (VT) (193.7 kg ha−1 d−1) and the highest maximum (VM) (220.9 kg ha−1 d−1) rates during the fast biomass accumulation period. These results suggest that one-time fertilizer application at the first flower stage might be an adjustment that is more effective than at first bloom, and allowed for easier decision making for application date due to non counting of plants with flowers is needed.

To optimize the spatial distribution of cotton bolls and to increase the yield, the relationship between yield components and boll spatial distribution was investigated among different Bt (Bacillus thuringensis) cotton varieties. A five-year field experiment was conducted to reveal the reasons for the differences in lint yield and fiber quality across three Bt cotton varieties with different yield formations from 2013 to 2017. The lint yield of Jiman 169 (the average yield from 2013–2017 was 42.2 g/plant) was the highest, i.e., 16.3 and 36.9% higher than Lumianyan 21 (L21) and Daizimian 99B (99B), respectively. And the differences in boll weight among the three cultivars were similar to the lint yield, while the others yield components were not. So the increase in lint yield was mainly attributed to the enlargement in boll weight. However, the change in fiber quality was inconsistent with the lint yield, and the quality of L21 was significantly better than that of Jimian 169 (J169) and 99B, which was caused by the diversity of boll spatial distribution. Compared with 99B, the loose-type J169 had the highest number of large bolls in inner positions; the tight-type L21 had a few large bolls and the highest number of lower and middle bolls. And approximately 80.72% of the lint yield was concentrated on the inner nodes in Jiman 169, compared with 77.44% of L21 and 66.73% of 99B during the five-year experiment. Although lint yield was significantly affected by the interannual changes, the lint yield of J169 was the highest and the most stable, as well as its yield components. These observations demonstrated the increase in lint yield was due to the increase in boll weight, and the large bolls and high fiber quality were attributed to the optimal distribution of bolls within the canopies.

Productivity of hybrid cottonseed by steady male sterile line is considered as an effective strategy in heterosis utilization. The male sterility was obtained by glyphosate application on transgenic glyphosate-tolerant (TGT) cotton line GRR, and its phenotypes were stable and apparent from previous primarily study. Systematic characterizations and safety assessments on the male sterility must accelerate its utilization and release in hybrid cottonseeds productions. In this study, featured characteristics in the male sterility were revealed from morphological phenotype, microsporogenesis, expressing pattern of exogenous G6-EPSPS mRNA, antioxidant enzymes response. Additionally, safety assessments on the male sterility obtained from GRR, based on outcrossing rate test, yield and fiber quality traits, in comparison with conventional manual emasculating, which were conducted for 3 seasons. The results indicated that the male sterile is stable with typical characteristics as following: (1) shorter and fusion filaments, larger distance between androecium and stigma, and anther indehiscence; (2) pre-degradation on tapetum and “cavitation” pollen during microsporogenesis; (3) Higher increasing expression efficiency of G6-EPSPS, as much as approximate 8 times, in pistil versus stamen in GRR-GT (GRR after glyphosate) was revealed, comparing with the control GRR (4) APX activity increased in stamens while decreased in other organs, in GRR-GT versus GRR. GRR-GT is safe as complete abortion and capable in cotton heterosis utilization, since there were no negative effects on F1 yield traits and significance in fiber quality parameters, in comparison with conventional manual emasculation. In details, the all fiber lint yields and Micronaire values ranged from 1536.80 ± 115.64 to 1883.90 ± 18.58 kg/ha and 4.60 ± 0.10 to 5.10 ± 0.79 respectively.

Stubble return is a proposed practice for soil amelioration and yield improvement. However, from the perspective of reducing soil salinity and improving soil nutrient availability, we have little knowledge of the effect of successive stubble return on cotton yield and nutrient uptake when cotton stubble is incorporated into saline field soil. Hence, a 5-year field study was conducted to investigate the effects of successive stubble management (stubble return and stubble removal) on lint yield and nutrient uptake of cotton, soil nutrients and salinity in the 0–80-cm soil profile. Stubble return increased lint yield by 22.7% and 47.3% in the fourth and fifth year, respectively, mainly through the production of more and larger bolls and the acquisition of more nutrients compared with stubble removal. 5-year cotton stubble return produced 20.0% more bolls and 7.7% larger bolls than stubble removal. Cotton plants accumulated 58.9% more nitrogen (N), 54.5% more phosphorus (P), and 48.2% more potassium (K) under stubble return than stubble removal during the last two years of the experiment. Stubble return increased internal N use efficiency (iNUE) and internal K use efficiency (iKUE) at the fourth or fifth year compared with stubble removal, without influence on internal P use efficiency (iPUE). Stubble return decreased soil pH and salinity in the 0–40-cm soil layer in the fourth and fifth year. The soil nitrate content below the 40-cm soil layer was reduced, while the nitrate concentration in the 0–20-cm soil layer increased after 4 years of stubble return. Available K in the 0–40-cm soil layer increased, while available P in the 0–20-cm soil layer was reduced after 5 years of stubble return. Our analyses demonstrate that cotton stubble return has the potential to improve cotton yield and may be an effective practice to apply in coastal saline areas.

Nitrogen (N) and irrigation can be two of the costliest management inputs in United States (U.S.) cotton (Gossypium hirsutum L.) production systems. Furthermore, input amounts are often dependent on yearly environmental conditions, making it challenging to optimize N and irrigation management. The objectives of this research were to determine optimal N and irrigation management by: (i) evaluating equally split in-season N rates applied at first square and bloom in combination with varying levels of plant available water replacement (PAWR) estimated by an ET-based soil water balance model for cotton; and (ii) evaluate the whole-plant responses to the interaction between N and water management levels. Field experiments were conducted during 2015 and 2016 at two locations in Florida (Jay and Citra), southeastern U.S. with differing soil textures consisting of a deep sand and sandy loam. Irrigation treatments consisted of: (i) 100% of PAWR (100%); (ii) a primed acclimation (PA) treatment consisting of 50% of PAWR until first bloom and then 100% of PAWR (50%PA); (iii) 50% PAWR for the entire season (50%); (iv) a rain-fed control (RF). Nitrogen treatments consisted of even application splits at first square and bloom applied at a rate of 0 (N0), 22 (N22), 34 (N34), and 45 kg N ha−1 (N45). Lint yield assessments were conducted at both locations in both years. To link yield responses to possible physiological responses, in depth crop measurements consisting of SPAD chlorophyll content, leaf area index (LAI), N uptake, and harvest index (HI) were conducted at the Citra site. Contrasting soil textures and weather conditions between research locations and years allowed for a comprehensive assessment of both N and irrigation management across varying environmental conditions. Lint yield was either increased or at least maintained during the two years of this research at the Citra location by making two split N applications at first square and bloom of N22; while the optimal N treatment at the Jay location was N34 at first square and bloom in both years of this research. Additionally, a yield reduction occurred in the dry year of 2016 at the Citra location when N45 was applied at first square and bloom. The most efficient irrigation strategy at the Citra location was the primed acclimation treatment. At the Jay location, the RF control had similar lint yields as the irrigated treatments in both years, indicating that water application was not limiting at this site. These management strategies offer ways to optimize costly inputs when growing cotton in the southeastern U.S.

Lint percentage is an important cotton (Gossipium hirsutum L.) lint yield character which may have a close association with photoassimilates partitioning between fibers and seeds. A three-year field experiment was conducted with an aim to determine whether or not the formation of lint percentage is associated with sucrose metabolism in both of fibers and seeds, and potential contributors to the performance of lint percentage. Two upland cotton (Gossypium hirsutum L.) lines A705 and A201 differing in lint percentage and seed size were employed to examine genotypic difference in within-boll yield components, nonstructural carbohydrate components (hexose, sucrose and starch) and key sucrose metabolism enzymes across 2015–2017. A705 had greater lint mass per boll, lint index, and higher lint percentage and cellulose content in fibers, but smaller boll weight, seed mass per boll, seed index and lower oil content in embryos compared to A201. The result indicated that the fiber sink strength was greater in A705 than in A201, but the reverse was true of the seed sink strength. A705 exhibited consistently higher sucrose concentration and sucrose synthase (Sus) activity in fibers during fiber development relative to A201, while the latter recorded consistently higher sucrose concentration and Sus activity in younger ovules during 5–17 days post anthesis (DPA) and in older embryos and seed coats during 24 DPA to 45 DPA. Higher starch concentration and sucrose phosphate synthase (SPS) activity with seed coats were detected in A705 than in A201, implying sucrose synthesized by SPS in A705 at sink storage stage is preferentially partitioned to starch biosynthesis in seed coats. It is concluded that a higher lint percentage in A705 than in A201 is attributable to a combination of greater fiber sink strength and smaller seed sink strength available in the former relative to the latter. Sucrose and Sus may function as key biomarkers for assessing fiber and ovule sink strengths.

Incredible accomplishments have been achieved in agricultural production in China, but many demanding challenges for ensuring sustainable cotton production remain. An efficient cropping model characterized with late sowing, higher density and low fertilizer application is a promising alternative to cope with the present high cost cotton production. However, it is not confirm that mepiquat chloride (MC) application is still required in this new planting model. We hypothesized that MC application might reduce lint yield and thus not be necessary in this new system. A 2-year (2015–2016) field experiment was performed to test this hypothesis in which cotton was planted in mid-May at 10 plants m−2 and with single fertilizer application (225 kg N ha-1). MC was sprayed thrice with 5 leaf intervals initiated from the 6th leaf stage in 5 different dosages i.e. 0 (control), 30, 60, 90, and 120 g ha-1. Morphological attributes viz. plant height, main stem diameter, number of fruiting branches, main stem nodes, main stem green leaves and main stem internode length were evidently reduced by 9–40%, 2–13%, 2–11%, 4–27%, 6–24% and 3–19%, respectively. Cotton potassium accumulation was not significantly influenced; specifically the uptake in reproductive organs from MC0 to MC120 of 45 to 44 kg K ha-1 in MC treated plants averaged across two years. Photosynthesis was reduced by 1–26% due to diminished Rubisco activity by 3–37% in MC treated plants and lint yield decreased by 5–27% as MC dosage increased. Furthermore, alpha amylase, beta amylase and total amylase activities were decreased by 2–16%, 3–19% and 1–17% but sucrose transformation rate was increased in the 4th functional leaf from the apex, respectively. Our data suggest that increased accumulation of sucrose and starch in the leaf with reduced photosynthesis, Rubisco and amylase activity could explain the yield loss. Conclusively, MC application is not needed for this new cotton planting model in Yangtze River Valley of China.

There is a consistent demand to improve cotton fibre quality from both the producer and the end user. However, this is a major hurdle for breeders due to its negative association with yield. This study investigated the breeding values of different cotton fibre strength sources for improvement without compromising lint yield. A North Carolina mating design II was performed between five high yield locally bred female parents (>2100 kg/ha) and four high fibre strength male parents (>31 g/tex) to obtain 20 crosses. Their F1’s were grown in the glasshouse and the F2’s and F3’s in the field, for two years, to determine general and specific combining ability of lint yield and fibre quality traits. The general combining ability effect was much larger than specific combining ability effect in determining significant variability among the crosses, implying that all traits were controlled primarily by additive gene action. Heritability estimates were moderate to high (0.36 ∼0.80) for lint percentage and fibre quality traits except fibre maturity. Lint yield had a moderate negative association with fibre strength. Early generation tests in the glasshouse and field identified the same good combiners. Acala Ultima and Sicala 40 were good general combiners for high fibre strength but poor for lint yield. However, two new locally bred high strength parents had positive general combining ability for both yield and fibre strength. Therefore, adapted high strength parents must be chosen first in crossing to achieve improvements in not only strength but also other quality traits and yield, demonstrating the importance of adaptation in parent selection in breeding for both yield and quality.

For many agricultural commodity sectors, efforts to meet international obligations regarding emissions reduction are increasing. The Australian cotton industry has already made advances in this regard and the high yields associated with Australian cotton production dramatically minimise greenhouse gas emissions intensity. However, certainty about the quantum of greenhouse gas emissions and the relative contribution of different components of the emissions profile is somewhat unclear; and opportunities for farm-level practice change have not been fully explored. The objectives of this paper were to, (a) build a robust greenhouse gas emissions profile for the product-chain of Australian cotton fibre (lint) grown in northwest New South Wales, (b) using Life Cycle Assessment (LCA), compare the relative contributions of the different industries involved in the product-chain of cotton fibre (e.g. fertiliser producers, cotton farmers, cotton ginning plants) and (c) assess the effects of an array of on-farm mitigation options. Testing the various management options provides information for growers and policy-makers about the relative emissions reduction benefits possible. Additionally, we compared results of previous Australian cotton production studies using similar assumptions and extrapolated the emissions profile to a national scale, with the intention of informing commodity and carbon markets. The foreground data for the study were for the three production seasons from 2011-2012 to 2013–2014 in northwest New South Wales, with a functional unit of one tonne of cotton lint at port. We also drew upon published data, survey data, scientific literature and Australian and international databases. To ensure consistency between our approach and that applied to meet international emissions reporting obligations, we applied emissions formulae and factors from the Australian National Inventory Report, except where more specific published data were available. We assumed that 96% of production was from irrigated systems, with 85% of irrigation water pumped by diesel-powered irrigation pumps and a median irrigated yield of 10.3 bales per ha. We tested the sensitivity of the resulting emissions profile to a wide array of enterprise assumptions and calculation variables. The climate change impact of cotton lint on a cradle-to-port basis was 1601 kg CO2e per tonne of cotton lint. The ‘hot-spots’ within the emissions profile included the production and use of synthetic nitrogen (N) fertilisers (46% of emissions), the production and use of electricity and diesel used for irrigation (10%) and the production and use of diesel for farm machinery (9%). Farm level management options with potential to minimise life cycle GHG emissions were: reducing N fertiliser rate from a commercial rate of 255 kg N/ha to 240 kg N/ha or 180 kg N/ha (2.6% and 13.2% emissions reduction); use of controlled-release and stabilised N fertilisers (5.9% reduction), changing from diesel to solar-powered irrigation pumps (8.1% reduction), changing from diesel to biofuel-powered farm machinery (3.4% reduction), changing from continuous cotton to a cotton-legume crop rotation (3.9% reduction) and use of N fertigation (2.1% reduction). Whilst we focused on farm-level mitigation strategies, these changes were placed in the context of the cradle-to-gate system, to account for associated changes in pre-farm and post-farm emissions.

Microfibers are a common type of microplastic. One known source of microfibers to the environment is domestic laundering, which can release thousands of fibers into washing machine effluent with every wash. Here, we adapted existing methods to measure the length, count and weight of microfibers in laundry effluent. We used this method to test the efficacy of two technologies marketed to reduce microfiber emissions: the Cora Ball and Lint LUV-R filter. Both technologies significantly reduced the numbers of microfibers from fleece blankets in washing effluent. The Lint LUV-R captured an average of 87% of microfibers in the wash by count, compared to the Cora Ball which captured 26% by count. The Lint LUV-R also significantly reduced the total weight and average length of fibers in effluent. While further research is needed to understand other sources of microfiber emissions, these available technologies could be adopted to reduce emissions from laundering textiles.

The fast fruiting and early maturing cotton varieties demand higher potassium (K) supply to achieve full yield potential. The supplemental foliar application of K may enhance the efficacy of soil applied basal dose of K. The main objective of this study was to quantify the impact of foliar application of KNO3 alone and in combination with soil applied K on cotton yield and lint quality. The treatments included control (no K application), four foliar sprays of 2% KNO3, 100 kg K2O ha−1 to soil, 200 kg K2O ha−1 to soil, combination of 100 kg K2O ha−1 to soil + four foliar sprays of 2% KNO3, and combination of 200 kg K2O ha−1 to soil + four foliar sprays of 2% KNO3. The results revealed that foliar and basal-applied K in alone and in different combinations significantly improved the plant morphology, seed cotton yield, boll characteristics and K concentrations in various plant parts. The K concentration in vegetative and boll components was improved with the higher K application rate. On overall basis, a yield benefit of 406 and 432.5 kg ha−1 was achieved with foliar spray in combination with 100 and 200 kg K2O ha−1 compared to their respective sole soil application. Non-significant differences for ginning out turn (GOT), staple length, strength, micronaire and uniformity index due to various K application methods indicate that K fertilization does not improve the fiber quality and GOT when soil has adequate K levels. It is concluded that foliar K application should be combined with basal K applications to achieve the highest returns from cotton grown on K-deficient soils.

Late sowing of short growing season cotton, planted in high density with one time fertilization is a potential economic alternative for the conventional cotton growing practice in the Yangtze River Valley, China. The appropriate proportion of nutrients is indispensable for an economic crop production. Therefore, the present study was designed to explore the best relative ratios of potassium (K) to nitrogen (N), under a new short-season and high density planting model, based on the photosynthetic performance of cotton plants in relation with the yield. A two-year (2016–17) field experiment was conducted with three K relative ratios to N [0.8 (K08: 168 kg ha−1 K2O), 1.0 (K10: 210 kg ha−1 K2O) and 1.2 (K12: 252 kg ha−1 K2O)]. The results indicated that K10 increased seed cotton and lint yield by 10–20% and 10–24%, respectively, over K08 and no difference was existed between K10 and K12. Similarly, K10 and K12 increased SPAD value by 3–10% and 11–18%, photosynthetic rate by 7–57% and 0.7–89%, and chlorophyll fluorescence parameters by 1–8% and 1–29%, respectively, as compared to K08. And the highest photosynthetic attributes were achieved for the 4th main stem leaf from the top at peak bloom (PB) stage. These results suggested that the K10 is the most suitable ratio as for cotton yield and economic concerns under the newly proposed planting model in the Yangtze River Valley, China.

Technology fees associated with modern cotton cultivars have increased seed costs considerably, giving producers the impetus to reduce plant population density, where possible. Most recent studies on cotton population density, conducted across diverse environments, report similar patterns of crop response: decreases in lint yield only at very low densities, with generally consistent yield across all higher densities. But no work had been done to bring the literature together, quantitively synthesizing the yield data collectively, to better pinpoint a population density threshold. And, notably, little had been reported on the effects of population density in lower-yielding dryland environments. Quantitatively synthesizing population density datasets from the literature, including our own dryland data, was the objective of this research. The dryland data showed that lint yield and biomass partitioning were not affected by population density, similar to higher-yielding environments over the same range in density. Following normalization of all lint yield data (literature and dryland datasets), a breakpoint in population density at 35,000 plants ha−1 was identified, which can be interpreted as the minimum plant density at which yield may be optimized. This rate is lower than the common density recommendation of 81,000 plants ha−1 and substantially lower than the risk-averse rates at which many producers plant (129,000 seeds ha−1 or greater). The analysis showed that yield will decline precipitously below 35,000 plants ha−1, exposing the enormous risk to cotton producers in approaching this low density, particularly if significant seed or plant loss is expected. However, the analysis suggests that excessive over-seeding may be occurring in many cases, resulting in economic losses to producers. The analysis also provides guidance on a threshold for producers facing replanting decisions.

A primary utility of satellite remote sensing technology is monitoring and assessment of agricultural lands for determining the area, amount, type, and quality of crop production. Since the mid-1970s agricultural scientists have sought to advance this utility through development of precision agriculture (PA) methods and technologies. Consequently, PA has taken advantage of freely available medium-spatial resolution remote sensing technology and instrumented fields to monitor crop biomass, phenology, and yield of crops at the sub-field to larger scales. The main goal of this study was to determine cotton lint yield in a 73-ha irrigated field in western Tennessee using remote sensing technology. We used two growing seasons (2013 and 2014) of Landsat 8 transformed to 8 input predictors including Red, near infra-red (NIR), the simple ratio (SR), normalized difference vegetation index (NDVI), green NDVI (GNDVI), and the tasselled cap transformation’s greenness, wetness, and soil brightness indices: GI, WI, and SBI, respectively, as proxies for cotton lint yield and crop phenology (in this study all input predictors are being referred to as crop indices, CIs). We used artificial neural network (ANN) approach to generate 61,200 models relating individual CIs and CI phenology to field estimates of lint yield to predict and map the field’s cotton lint yield in two cropping seasons. The correlation between cotton lint yield and CIs ranged from -0.20 to 0.60 in 2013 and from −0.79 to 0.84 in 2014. The best ANN models were in 2013 (r = 0.68 and the normalized MAE = 11%) and 2014 (r = 0.86 and the normalized MAE = 8%) growing seasons. The WI and GI were the best CI predictors of cotton lint yield, and overall for the early to mid-season prediction, CI phenologies had better performance than single date CI models. Consequently, we recommend the use of Landsat 8 derived WI or GI phenology to predict crop yields.

Recent advances in molecular breeding and bioinformatics have greatly accelerated the screening of large sets of genotypes. Development of field-level phenotyping, however, still lags behind and is considered by many as the main bottleneck to improved efficiency in breeding programs. Unmanned Aerial System (UAS) and sensor technology available today enables collection of data at high spatial and temporal scales, previously unobtainable using traditional airborne remote sensing technologies. Here, we propose an UAS-assisted high throughput phenotyping framework for cotton (Gossypium hirsutum L.) genotype selection. UAS data collected on July 24, 2015 were used to calculate canopy cover, and UAS data collected on August 5, 2015 were used to extract open boll related phenotypic features including number of open bolls, average area of open bolls, average diameter of open bolls, perimeter of open bolls, perimeter to area ratio. Using the extracted features, a sequential selection procedure was performed on a population of 144 entries. Entries selected from the proposed framework were compared to the highest yielding entries determined by mechanical harvest results. Experimental results indicated that the selection process increased minimum and average lint yield of the remaining population by 7.4 and 10%, respectively, and UAS-selected entries and genotypes matched 80 and 73%, respectively, the same lists ranked by actual field harvest measurements.

Novel yield component traits and fiber quality indices have been recently developed by breeders to screen for desirable cotton (Gossypium hirsutum L.) lines, but assessing these components in response to water-induced yield variability has received little attention. We investigated the hypothesis that differential sensitivities of whole-crop and intra-boll yield components to drought will largely explain water-induced yield and fiber quality variation in cotton. To test this hypothesis, two cotton cultivars were grown in the field under five contrasting irrigation regimes during the 2013 and 2014 growing seasons near Camilla, GA. Measurements included predawn leaf water potential (ΨPD) throughout the growing season and extensive yield component and fiber quality assessments at the end of the season. Water-induced yield variability was primarily associated with ΨPD at the flowering and boll development phase of crop growth. Boll density (bolls ha−1) was the dominant driver of drought-induced yield loss, but reduced boll mass and seed number per boll also contributed somewhat to yield loss. By comparison, increased drought severity decreased fiber density but increased individual fiber mass, producing a peak in total fiber weight per seed at a −0.7 MPa ΨPD irrigation threshold and increasing lint percentage in stressed treatments. Thus, the negative impacts of drought on overall boll mass and seed number per boll are partially offset by increased dry matter partitioning toward fiber growth. Fiber length declined with increased drought severity, whereas fiber micronaire increased in the most severely stressed treatments. This indicates that increasing drought severity during flowering and boll development decreases the number of individual fibers per seed and their final length, but their thickness is increased. The end result is a decline in the overall fiber quality index (Q-score) under drought stress.

Two cotton (Gossypium hirsutum L.) cultivars, Kemian 1 (cool temperature-tolerant) and Sumian 15 (cool temperature-sensitive) were used to study the effects of cool temperature on carbohydrates, yield, and fiber quality in cotton bolls located at different fruiting positions (FP). Cool temperatures were created using late planting and low light. The experiment was conducted in 2010 and 2011 using two planting dates (OPD, the optimized planting date, 25 April; LPD, the late planting date, 10 June) and two shading levels of crop relative light rate (CRLR, 100 and 60%). Compared with fruiting position 1 (FP1), cotton yield and yield components (fiber quality, leaf sucrose and starch content, and fiber cellulose) were all decreased on FP3 under all treatments. Compared with OPD-CRLR 100%, other treatments (OPD-CRLR 60%, LPD-CRLR 100%, and LPD-CRLR 60%) had significantly decreased lint yield at both FPs of both cultivars, but especially at FP3 and in Sumian 15; this decrease was mainly caused by a large decline in boll number. All fiber quality indices decreased under late planting and shading except fiber length at FP1 with OPD-CRLR 60%, and a greater reduction was observed at FP3 and in Sumian 15. Sucrose content of the subtending leaf and fiber increased under LPD compared to OPD, whereas it decreased under CRLR 60% compared to CRLR 100%, which led to decreased fiber cellulose content. Therefore, shading primarily decreased the “source” sucrose content in the subtending leaf whereas late planting diminished translocation of sucrose towards cotton fiber. Notably, as planting date was delayed and light was decreased, more carbohydrates were distributed to leaf and bolls at FP1 than those at FP3, resulting in higher yield and better fiber quality at FP1, and a higher proportion of bolls and carbohydrates allocated at FP3 of Kemian 1 compared to that of Sumian 15. In conclusion, cotton yield and fiber quality were reduced less at FP1 compared to those at FP3 under low temperature and low light conditions. Thus, reduced cotton yield and fiber quality loss can be minimized by selecting low temperature tolerant cultivars under both low temperature and light conditions.

Australian rainfed cotton is grown in regions with highly variable rainfall, with in-crop rainfall ranging from 100 mm to 800 mm. The CSIRO cotton breeding program conducts rainfed germplasm evaluations at its core research site, as well as a number of regional locations. As a direct result of our variable rainfall environment, yields 550 kg ha−1 were not achieved in 27 seasons (18%). These 27 seasons underwent further simulations to determine the most suitable soil water content and crop growth stage where yield was increased with a single irrigation. It was determined that an irrigation should be applied to a ‘rainfed’ experiment if plant available water (PAW) reached approximately 40% by peak flowering (100-110 DAS). Paired rainfed and MSE experiments with 21 genotypes were established in 2013/14, 2014/15 and 2015/16 to provide field validation of the developed protocol. Genotype performance was assessed in terms of lint yield and fibre quality. Results show that in dry seasons (2013/14) irrigating the ‘rainfed’ treatment was necessary to reduce within experiment variability and increase yields above 550 kg ha−1. However, once rainfed yield levels increase due to greater in-crop rainfall (2014/15 and 2015/16), irrigation was no longer necessary. This was further supported by the result that genotype yield ranking differed between rainfed and MSE treatments. Genotype changes in fibre quality between treatments were small. It was concluded that a MSE, designed to produce experimental data better matched to our breeding target environment as well as reducing the risk of experimental failure, would be a worthwhile addition to rainfed evaluations conducted in variable rainfall environments.

Novel intra-boll yield component traits and fiber quality indices have been used by breeders to select suitable Gossypium hirsutum L. lines, but there is little research on how these traits change during cultivation practices, especially fertilizer application. We hypothesized that these novel traits have obvious responses to phosphorus (P) fertilizer, which would explain the variation in yield and fiber quality under different P conditions. To address this hypothesis, a field test was conducted with a low-P sensitive cotton cultivar (Lu 54) and a low-P tolerant cotton cultivar (Yuzaomian 9110) under different P fertilizer rates (0 as control, 100, and 200 kg P2O5 ha−1) from 2016 to 2018. The results showed that P fertilizer application (100, and 200 kg P2O5 ha−1) increased the lint yield, and bolls per ha contributed most to the increase in lint yield, followed by boll weight and lint percentage. The increased bolls per ha under P fertilizer application was due to the accelerated process of boll forming and the slowing of shedding process. The increased boll weight under P fertilizer application could be explained by the higher seed biomass per boll and fiber biomass per boll, especially the latter. The higher seed biomass per boll was due to the increased seeds per boll, and higher fiber biomass per boll should be attributed to the increased fibers per seed under P fertilizer application. The positive contribution of lint percentage to lint yield formation under P fertilizer application could be attributed to the increased fiber biomass per seed. P fertilizer application decreased fiber micronaire, indicating that fiber thickness was decreased by extra P fertilizer, which might be associated with the negative effects of increased fibers per seed and fiber density. In addition, P fertility application promoted the elongation of fiber cells and fiber length uniformity, and increased fiber strength. The end result was an increase in the comprehensive fiber quality index (Q-score) after P application. Moreover, compared to Yuzaomian 9110, yield traits including lint yield, bolls per ha, seeds per boll, seed index, and SSA, and quality indices including fiber length, fiber strength, and Q-score were more sensitive to P fertilizer application in Lu 54.

Direct-seeded-cotton (DSC) leads to low crop and water productivity and energy-output with higher carbon-footprints besides impairing system-intensification under conventional cotton-wheat cropping system (CWCS). Hence, we evaluated two methods of Bt-cotton establishment [transplanted cotton (TPC) & DSC)] at three planting geometries/densities in four Bt-cotton based cropping-systems [DSC-wheat (DSC-W), TPC-wheat-mungbean (TPC-W-M), DSC-onion (DSC-O), TPC-onion-fodder cowpea + fodder maize (TPC-O-FC + FM)] in semi-arid region of south Asia. Poly-glass nursery-raised TPC exhibited significantly higher germination (96.5%), seedling-survival (96.1%) and 14.1% higher plant-stand owing to lower seedling-mortality (3.2%). TPC used ∼60% less irrigation-water but exhibited significantly higher seed-cotton, seed and lint yield, net-returns, radiation-use-efficiency and water-productivity by 11.4, 9.9, 14.3, 17.3, 10.7 and 260.6%, respectively over DSC. Planting geometry/density of 60 × 45 cm (37,037 plants ha−1) exhibited significantly higher crop and water productivity and economic-returns. Bt-cotton transplanting led system-intensification enhanced the system-productivity (26.1%), profitability (30.5%), water-productivity (19.3%) and land-use-efficiency (8.5%) over the DSC-based systems with significantly higher values under TPC-O-FC + FM. Energy-use pattern reveled that farm inputs viz. Fertilizers (54–60%), water (15–25%) and diesel (6–10%) consumed bulk of the input-energy in different cropping systems with greatest values under TPC-O-FC + FM. TPC-W-M exhibited highest system energy-output (604.6 × 103 MJ ha−1) and energy-returns (566.2 × 103 MJ ha−1). TPC-O-FC + FM exhibited significantly higher carbon-consumption (668.9 kg CE ha−1) and carbon-output (21431.3 kg CE ha−1) while maintaining significantly higher carbon-efficiency (32.0) and carbon sustainability index (31.0). TPC-O-FC + FM had least carbon-footprints (0.07 kg CE kg−1 SCEY) while conventional-CWCS exhibited 2-folds higher carbon-footprints. Legume-imbedded TPC-based cropping systems markedly increased the soil physical (bulk-density, water-stable-aggregates), chemical (SOC, available-NPK) and biological properties (soil-microbial-biomass-carbon, dehydrogenase and ergosterol activity) over the conventional CWCS and DCS-O systems. Overall, Bt-cotton transplanting led system-intensification upholds great importance in enhancing the system crop and water-productivity, profitability, energy-productivity, resource-use-efficiency and soil-health with minimal carbon-footprints in semi-arid agro-ecosystems of south Asia.

Climate variability is a challenge to the reliable production of high yielding cotton, Gossypium hirsutum L. in the subtropics. Shifting the growing season earlier by sowing during late winter (August) to reduce the risk of exposure to unfavourable radiation, temperature and rainfall during mid-summer offered the potential to improve stagnating and variable yields. This study aimed to determine the effect of late winter sowing on establishment, growth, development and lint yield of cotton. Accepted knowledge from temperate climates suggested cold temperature stress would impede crop establishment, so the application of clear oxodegradable film to the soil surface at sowing to mitigate cold temperature stress was also explored. Crop establishment, biomass accumulation and partitioning, light interception and lint yield were measured for cotton sown with and without film at intervals from early August to mid-September in four consecutive experiments (2013–2016). The application of film provided no benefits for establishment and only marginal improvement for crop growth and yield despite minimum temperatures being well below accepted chilling injury thresholds in temperate environments. Greater daily solar radiation levels both solarised the soil and shortened the duration of daily minimum temperatures, enabling successful crop establishment. Early sowing did not hinder crop production, and in 3 of the 4 experiments, lint yield was significantly higher (P As the occurrence of excessive temperature-related weather events is expected to increase with climate change, particularly for the subtropics, this study demonstrates how a knowledge of crop response can be used to evolve sowing time strategies to better mitigate climatic risk.

Apical dominance inhibition is important in cotton (Gossypium hirsutum L.) production due to its indeterminate growth habit. Apical dominance can be inhibited physically by the manual removal of apical buds or chemically by the application of plant growth regulators. However, knowledge of the yield and boll distribution of cotton under different methods of apical dominance inhibition remains limited. Thus, an experiment was conducted to evaluate the effects of different methods of apical dominance inhibition (physical inhibition, chemical inhibition and no inhibition) on the plant growth, within-plant boll distribution, crop maturity, yield and fiber quality of cotton from 2016 to 2018. Compared with no inhibition, chemical inhibition and especially physical inhibition reduced plant height, whereas only physical inhibition promoted the ratio of fruiting sites to fruiting branches, which indicated that chemical inhibition resulted in a more compact plant type than physical inhibition. Earlier crop maturity was observed with both physical and chemical inhibition methods than without inhibition, and this finding was attributed to a higher number of inner bolls at lower and middle nodes. The lint yield response to the different inhibition methods varied among years and between varieties. The lint yield of XIN4 was significantly enhanced by physical inhibition and chemical inhibition in 2 of the 3 years, by an average of 11.5 % and 8.7 %, respectively. An effect of inhibition method on the lint yield of CRI60 was observed only in 2016, in which physical inhibition significantly improved the lint yield by 14.0 % compared with that obtained without inhibition. Chemical inhibition achieved a similar lint yield to physical inhibition in all three years. Fiber quality was slightly reduced under chemical inhibition compared to physical inhibition, but the values were within the acceptable range regarding grade standards. Overall, although apical dominance inhibition did not consistently improve lint yield, it remains a desirable management tool for achieving a favorable cotton architecture for mechanical harvest. Additionally, chemical inhibition appears to be a promising alternative to physical inhibition in cotton production due to its simplicity as a management tool.

Cotton production is challenged by high cost with multiple management and material inputs including mepiquat chloride (MC) application to avoid excess vegetative growth and yield losses. A competitive planting model has been practiced in recent years in Yangtze River Valley, China characterized with late sowing, high density and low fertilization. We hypothesized that MC could also be ignored under this planting model to cut down the cost further. A 2-year field experiment was performed to determine cotton response to MC in allied growth and yield dynamics in 2015 and 2016. MC was applied thrice with 5 leaf intervals initiated from the 6th leaf stage in 5 different dosages i.e. 0 (control), 30, 60, 90, and 120 g ha−1. The results showed that the lint yield was reduced by 6–29% with increase in MC dosages resulted from the reduced cotton plants biomass (from 1036 gm−2 of MC0 to 841 gm−2 of MC120) especially the reproductive organs biomass (492 gm−2 of MC0 to 376 gm−2 of MC120) averaged across two years. The biomass accumulation for control (MC0) during the fast accumulation period (FAP) had a higher rate (10.1 and 29.8 gm−2 d−1 in 2015 and 2016, respectively) for plant biomass and a longer period (34.5 and 28.0 d in 2015 and 2016, respectively) for reproductive organs biomass. The results suggested that MC application could be omitted in the new cotton planting model, ensuring more economic benefits by waiving off the labor and chemicals cost involved.

Cotton (Gossypium hirustum L.) as well as other crops are asking for an effective production with cost reduction and environment stewardship globally, especially in the developing countries. A new cotton planting strategy should be possible by shortening the growth season (less than six months rather than seven to eight months by late sowing and early harvesting) with low nitrogen (N) and high density. Therefore, a two-year (2018–2019) field experiment was conducted with a split plot design, two planting densities (D1, 6 plants m−2; D2, 8 plants m−2) as the main plot and three N rates (150, 180 and 210 kg ha-1 referred as N1, N2, and N3, respectively) as the subplot, to determine the effects of planting density and N rate on cotton yield and biomass accumulation. Results showed that, averaged across years, cotton yield was greater for treatment D2 as compared with that in D1, and N3 did not differ from that in N2 but was greater than that in N1. The highest lint yield (1271.2 kg ha-1) was achieved in D2N2 which no differ from that in D2N3 and D1N3. The maximal biomass (K) was achieved in treatment D2N2 (1032.4 g m−2) with the average speed (VT) of 21.2 g m−2 d-1 during the fast accumulation period, and the maximal growth rate (Rm, 20.5 g m−2 d-1) of sink during the cotton growth and development. Seedcotton yield was positively correlated (r = 0.72) to the plant biomass during flowering and boll-setting period, and the yield was contributed directly by sink with a coefficient as high as 0.70, while it was contributed indirectly by flow and source with coefficients of 0.63 and 0.59, respectively. The results suggest that N reduction is feasible due to a quicker bulk sink biomass accumulation under a higher planting density, which benefits efficient cotton production in the Yangtze River Valley, China, and areas with similar ecology.

We construct a new partial geometry with parameters pg(5,5,2), not isomorphic to the partial geometry of van Lint and Schrijver., Comment: 5 pages

As the Ogallala Aquifer depletes there is a need to identify management options that might make un-irrigated cotton production sustainable over the U.S. Southern High Plains (SHP). To explore those options, the CSM-CROPGRO-Cotton model was used to simulate the effects of planting options and elevation effects on SHP dryland cotton production. Of the management variables that define the 56 planting options simulated, planting date and density account for the most variability in median SHP yields. Cooler SHP growing seasons have the effect of reducing median lint yields relative to those simulated over the lower elevations of the nearby Rolling Plains. This effect is not as evident in median Rolling Plains yields, which suggests it can be traced to the cooler growing environment of the higher SHP elevations. Also, at both higher and lower elevations lower planting densities maximize median yields, while higher densities result in the lowest yields. These results suggest that the yield suppressing effect of the SHP region’s cooler growing conditions might be compensated for by planting early whenever possible and planting at lower densities. The clear decreasing effect on median yields at higher elevation also suggests the possibility of SHP cotton production moving to the lower elevations of the nearby Rolling Plains as Ogallala Aquifer levels drop.

The Xinjiang Uyghur Autonomous Region in northwest China accounted for 73% of China's total cotton production in 2014. However, Xinjiang's cotton is difficult to market due to poor lint quality and become increasingly acute. The objectives of this study were to determine changes of fiber quality and to investigate the reasons for poor lint quality in the Xinjiang Region. Field production conditions and harvesting methods caused more variability in fiber damage than cleaning processes. Under field production conditions, fiber strength of 35% of the cultivars was reduced by more than 2 cN/tex and fiber length of 12% was reduced by more than 2 mm machine harvesting reduced fiber length by more than 2 mm at 17% of the experimental sites. Cleaning processes caused fiber damages that fiber quality reduced one to two units accounted for 84% of samples. Cotton fiber damage as influenced by field production conditions, harvesting methods, and cleaning processes. But field production conditions increased fiber strength of 27% of the cultivars compared with variety trial reports, machine harvesting increased fiber length and fiber strength at 48% and 33% of the experiment sites compared with hand harvesting. The crucial point about the phenomenon was that how to reduce the foreign matter content of machine harvested cotton.

Cotton is the fifth major oil crop and grown primarily for natural fiber globally. Suitable management practices like planting density (PD) and sowing date (SD) are the major drivers of cotton crop productivity. Cotton production with a normal practice of 3 plants m −2 in Yangtze River Valley China, resulting in an average yield of 1200 kg ha −1 although, high input costs and low productivity are the two major consequences in cotton production systems. The production costs can be decreased and profits can be increased through optimal PD and adjusting SD. The objectives of this study were to optimize growth, yield, biomass partitioning and potassium (K) distribution of a cotton crop under a short growing season and elevated PD. Experiments were conducted with two sowing dates i.e. early (S 1 , May 20 and late S 2 , June 04) as the main plot and three plant densities (D 1 , low 7.5; D 2 , moderate; 9.0 and D 3, high; 10.5 plants m −2 ) as the subplot laid out in a split arrangement with four replicates. D 3 crops significantly delayed cotton growth period under late sowing date compared with early planted crops. Compared with S 2 crops, S 1 plants produced 29% and 26% higher seed cotton and lint yield, respectively. Among the PD, D 2 plants produced 12%, 15%, 13% and 6% more seed cotton yield and lint yield over D 1 and D 3 crops respectively. The increment in yield was due to increased plant reproductive organs biomass occasioned by moderate density and longer cropping season which allowed the utilization of available resources. Higher K acquisition i.e. (0.9 V M kg ha −1 d −1 ), further improved reproductive structures formation in S 1 combined with D 2 crops. The S 1 in combination with D 2 crops resulted in the highest average (77 V T kg ha −1 d −1 ) and maximum (93 V M kg ha −1 d −1 ) rates of reproductive organs biomass accumulation than other combinations. Conclusively, use of medium density under both sowing dates is an effective strategy for optimal seed cotton and lint yield.

This study assesses the effects of plant population density (PPD) and sowing date (SD) on growth, physiology and lint yield of a cotton crop. Seedling transplanting is one of the most dominant cotton production systems in China. But on the other hand, the net benefit is decreasing because the system is labor intensive. Therefore, a shorter cotton growing season is urgently needed to reduce the production costs through management practices such as adjusting sowing date and PPD. The following hypothesis was tested; would cotton yield and physiology from a late sowing be compensated by plant density? Field experiments were conducted with two sowing dates (S1, May 20; S2, June 04) as the main plot and three PPDs (D1, low; 7.5 × 104; D2, moderate; 9.0 × 104 and D3, high; 10.5 × 104 ha−1) as the sub-plot. Early-sown plants produced 23%, 32%, 55%, 77% and 14%, taller stems more nodes, leaves and fruits, respectively, than the late-sown plants. Consequently, S1 produced 26% higher lint yield than S2. This increase in lint yield was mainly attributed to a relatively longer cropping season, which allowed utilization of available resources. Growth and fruit production in S1 plants were further increased by an increased photosynthetic rate (Pn) and N acquisition. Across the plant densities, 13% and 6% more lint yield was achieved under D2 than the D3 and D1, respectively. Moderate PPD increased lint yield by 13% and 6% over high and low, respectively. Nitrogen (N) acquisition was 45%, 33%, higher for S1 sown crop compared with S2, respectively. S1D2 had higher average (3.5 VT kg ha−1 d−1) and maximum (4.5 VM kg ha−1 d−1) rates of N accumulation in reproductive organs at the fastest accumulation point among other treatments. Our data suggest that for both sowing dates moderate PPD is a promising option, which allows light interception and penetration to the lower canopy, efficient N utilization and assimilate distribution to reproductive structures.

The number of fibers per seed surface area (fiber density) is a selection criterion used to improve cotton fiber quality and yield simultaneously in cotton breeding programs. However, the parameters utilized to estimate fiber density are calculated from fiber quality attributes that are sensitive to environmental variations, especially fiber maturity. Fiber maturity is one of the most important fiber properties that influences other fiber properties such as individual fiber strength and length. In order to investigate the impact of within-plant fiber maturity on the estimates of fiber density, field experiments were conducted at Lubbock, Texas during the 2012, 2013 and 2014 growing seasons. A set of twelve upland cotton cultivars popular in the Texas High Plains were grown in a randomized complete block design with three field replications. Bolls were box picked at harvest to provide samples from each cultivar representing a range of fiber maturity. Fuzzy seeds obtained after roller ginning were acid-delinted, scanned on a flatbed scanner, and the WinSeedle Pro software was used to estimate the seed surface area (SSA). The number of fibers per seed was estimated using the fiber quality parameters provided by AFIS (Advanced Fiber Information System), the lint weight, and the number of seeds in the sample. The number of fibers per seed surface area was obtained by dividing the number of fibers per seed by the estimated SSA. In this study, cultivars with relatively less stable fiber maturity across the fruiting branches of the cotton plant tend to have more variable number of fibers per seed surface area estimates, suggesting that the calculation of the number of fibers per seed surface area may be biased. It is likely that the source of bias is fiber maturity (immature fibers are weak and tend to break during mechanical processing). Therefore, fiber maturity should be considered when screening lines based on estimated fiber density because low fiber maturity can lead to unreliable estimates of fiber density.

Cotton is an important source of natural fiber around the world. Cotton lint, however, could be contaminated by various types of foreign matter (FM) during harvesting and processing, leading to reduced quality and potentially even defective textile products. Current sensing methods can detect the presence of foreign matter on the surface of cotton lint, but they are not able to efficiently detect and classify foreign matter that is mixed with or embedded inside cotton lint. This study focused on the detection and classification of common types of foreign matter hidden within the cotton lint by a short wave near infrared hyperspectral imaging (HSI) system using the transmittance mode. Fourteen common categories of foreign matter and cotton lint were collected from the field and the foreign matter particles were sandwiched between two thin cotton lint webs. Operation parameters were optimized through a series of experiments for the best performance of the transmittance mode. After acquiring transmittance images of the cotton lint and foreign matter mixture, minimum noise fraction (MNF) rotation was utilized to obtain component images to assist visual detection and mean spectra extraction from a total of 141 wavelength bands. The optimal spectral bands were identified by using the minimal-redundancy-maximal-relevance (mRMR)-based feature selection method. Linear discriminant analysis (LDA) and a support vector machine (SVM) were employed to classify foreign matter at the spectral and pixel level, respectively. Over 95% classification accuracies for the spectra and the images were achieved using the selected optimal wavelengths. This study indicated that it was feasible to detect botanical (e.g. seed coat, seed meat, stem, and leaf) and non-botanical (e.g. paper, and plastic package) types of foreign matter that were embedded inside cotton lint using short wave infrared hyperspectral transmittance imaging.

The denitrification-decomposition (DNDC) model is a useful tool for integrating the effects of agricultural practices and climate change on soil nitrous oxide (N2O) emissions from agricultural ecosystems. In this study, the DNDC model was evaluated against observations and used to simulate the effect of plastic mulching on soil N2O emissions and crop growth. The DNDC model performed well in simulating temporal variations in N2O emissions and plant growth during the observation period, although it slightly underestimated the cumulative N2O emissions, and was able to simulate the effects of plastic mulching on N2O emissions and crop yield. Both the observations and simulations demonstrated that the application of plastic film increased cumulative N2O emissions and cotton lint yield compared with the non-mulched treatment. The sensitivity test showed that the N2O emissions and lint yield were sensitive to changes in climate and management practices, and the application of plastic film made the N2O emissions and lint yield less sensitive to changes in temperature and irrigation. Although the simulations showed that the beneficial impacts of plastic mulching on N2O emissions were not gained under high fertilizer and irrigation scenarios, our simulations suggest that the application of plastic film effectively reduced soil N2O emissions while promoting yields under suitable fertilizer rates and irrigation. Compared with the baseline scenario, future climate change significantly increased N2O emissions by 15–17% without significantly influencing the lint yields in the non-mulched treatment; in the mulched treatment, climate change significantly promoted the lint yield by 5–6% and significantly reduced N2O emissions by 14% in the RCP4.5 and RCP8.5 scenarios. Overall, our results demonstrate that the application of plastic film is an efficient way to address increased N2O emissions and simultaneously enhance crop yield in the future.

Gastric cancer is the second most common cancer in the world. Due to the time-consuming diagnosis of the disease, it is essential to use new methods (e.g., computer science) for early diagnosis. Among various computer-based detection methods, artificial intelligence algorithms have attracted great attention today. The present study aimed to increase the accuracy of gastric cancer diagnosis by using a combination of deep neural network, support vector machine, and deep convolutional neural network (CNN) based on the surface and color features of the tongue. The proposed method was evaluated in seven CNN architectures. According to the results, using the DenseNet architecture in the proposed method had a higher accuracy compared to the other architectures, and 91 % accuracy was observed in the diagnosis of gastric cancer.

Recently published information on cotton agronomic and photosynthetic component responses to nitrogen (N) application rate is limited for the southeastern US. This experiment was conducted to 1) evaluate cotton yield, fiber quality, growth, and maturity responses to N application rate and 2) quantify associations between photosynthetic component processes and N-induced variation in net photosynthesis. A two-year field experiment was conducted during the 2015 and 2016 growing seasons at a field site in Tifton, GA and evaluated cotton agronomic and physiological response to six N fertilizer application rates ranging from 0 to 168 kg N ha−1. Cotton lint yield was 42–51% lower in 0 N treatments than all other fertilized treatments in both years of the study, and N rates that substantially limited yield decreased final plant height, reduced mainstem node development, and substantially hastened maturity. Date of cutout ranged from 73 to 91 DAP for all N rates and years of the study. Photosynthetic rates were also responsive to N rate on later sample dates (July and August) for both growing seasons. Although declines in chlorophyll content, specific leaf nitrogen, and stomatal conductance were observed for low N plants in some instances, none of these parameters were strongly associated with net photosynthesis overall. In contrast, light-dependent electron transport rate (ETR) was strongly correlated with N-induced variation in net photosynthesis. Estimates of ETR may need to be included along with SLN estimates in future efforts to scale from leaf to canopy level photosynthetic performance in cotton.

Cotton and polyester are the main elements of dryer lint that is generated while drying clothes, and thus it could serve as a promising and sustainable source of renewable energy. In this regard, this is the first research developed to investigate potential applications of dryer lint in the energy recovery field using a pyrolysis process. The suggested strategy was started by collecting dryer lint samples from three different households, followed by analysis of morphology, chemical composition, and elemental analysis of the collected samples using Scanning Electron Microscope- Energy-dispersive X-ray Spectroscopy (SEM-EDS) and ICP, FTIR, Elemental Analyser, respectively. Subsequently, TG-FTIR/GC–MS system was employed to study thermal and chemical decomposition of the collected lint samples up to 900 °C and to simulate the pyrolysis process. Also, the effects of heating rates (5, 10, 15, 20, 25, 30 °C/min) on slow pyrolysis properties and the synthesized chemical compounds of lint were investigated. Finally, the kinetic of pyrolysis of dryer lint for each heating rate using a model-free methods, including Kissinger, Kissinger–Akahira–Sunose, Flynn–Wall–Ozawa, and Friedman model was studied based on the TGA-DTG results. The results showed that the collected lint samples contained a huge amount of polyester, cellulose, etc., that could facilitate significantly the conversion energy process. Meanwhile, the model-free model indicated that the activation energy (Ea) of lint pyrolysis was estimated in the range 167−204 kJ/mol. Also, it was observed that CH2, CH3, Carbon dioxide, acid, phenol, carbonyl, methane compounds are present in the resulted FTIR spectra, especially at a heating rate (25 °C/min). While GC–MS results at 25 °C/min showed that Isobutane (10.77 %), Furan, 3-methyl- (4.78 %), Furfural (6.48 %), carbon dioxide (11.68 %), etc. compounds were strongly present in the synthesized volatile products, which means that lint could be a new sustainable biomass source for renewable energy.

Interest in urea-ammonium sulfate (UAS) as a N fertilizer is increasing due, in part, to increased restrictions on ammonium nitrate. This has resulted in UAS being marketed as an alternative fertilizer source; however, UAS has not been widely tested. A cotton ( Gossypium hirsutum L.) field study was conducted in Central Alabama from 2009 to 2011 on a Coastal Plain soil (Marvyn loamy sand; fine-loamy, kaolinitic, thermic Typic Kanhapludult) comparing UAS to two common granular fertilizers [urea, ammonia sulfate (AS)] under both conservation and conventional tillage systems. The overall objective was to determine the influence of UAS on cotton growth parameters, yield, and fiber quality. Cotton was fertilized with 101 kg N ha −1 urea, AS, or UAS 5–6 wk after planting each year. Plant growth characteristics were evaluated 3–4 wk before defoliation, and cotton yield and fiber quality were determined on the machine-harvested lint. Tillage had little influence on plant growth, while UAS and/or AS tended to produce the largest number of bolls and largest aboveground, root, and total biomass in 2009 and 2011. Lint yield was also influenced by fertilizer source in 2009 and 2011, with UAS and AS producing significantly higher yields than urea. Both tillage and fertilizer source had minimal influence on cotton fiber quality. Results suggest that UAS produces similar or greater yields than urea and is comparable to AS. However, more research is needed to determine the long-term influence of UAS on soil acidity and N loss compared to urea and AS.

Verticillium wilt is responsible for substantial yield losses in cotton. The use of cultivars with partial resistance to Verticillium wilt is a preferred management strategy. Cotton breeders utilize rating scales based on severity of foliar symptom expression and/or defoliation when making cultivar selections. The objective of this research was to determine the yield relationship with cultivars grouped by both incidence of Verticillium wilt during the boll filling stage, and late season defoliation in fields with a history of Verticillium wilt. Small plot, replicated cultivar trials were conducted over an 11 year period in west Texas. Cultivars were divided into four classes (A–D) based on normalized wilt incidence (NW) and four classes based on normalized defoliation ratings (ND). Classes were determined through a mixed model analysis of cultivars, with T-test comparisons between a partially resistant check (Fibermax 2484B2F) and a susceptible check (Deltapine 0912B2RF). The A and C classes did not differ (P = 0.05) from the partially resistant and susceptible checks, respectively. Classes were used in a mixed model analysis with lint yield. In a model with only NW classes, lint yield decreased significantly as NW increased with least square mean values of 1421, 1385, 1284 and 1204 kg/ha, for classes A, B, C and D, respectively. In a model with both NW and ND classes, the A/A class combination of NW and ND had a significantly (P ≤ 0.05) higher lint yield (1776 kg/ha) than any other combination. NW/ND class combinations of A/B, B/A, B/B, and C/A had intermediate yields, and ND classes of C or D had the lowest yields. Cultivars with both low wilt and defoliation incidences should result in higher yields in fields infested with Verticillium dahliae. Furthermore, these two rating criteria could be used to standardize the process for developing resistant cultivars.

Conventional potassium fertilizers had been used widely, but few studies paid attention to controlled-release potassium fertilizer. The objective of this study was to explore the effects of polymer coated potassium chloride (PCPC) -an innovation product, especially the interaction application of PCPC and polymer coated urea (PCU) on cotton yield, fiber quality, leaf photosynthesis and fertilizer use efficiencies under salinity stressed conditions. A two-year experiment was conducted in two nearby fields with the similar fertility but varying salinity, using a split-plot design in the Yellow River Delta area of China. The main plots were assigned to the types of K fertilizers (K1-180 kg ha-1 K from potassium sulfate, K2-90 kg ha-1 K from potassium sulfate + 90 kg ha-1 K from PCPC, K3-54 kg ha-1 K from potassium sulfate + 126 kg ha-1 K from PCPC, hereafter referred to as 0, 50% and 70% PCPC), while the types of N fertilizers (N1-220 kg ha-1 N from urea, N2-110 kg ha-1 N from urea + 110 kg ha-1 N from PCU, N3-66 kg ha−1 N from urea + 154 kg ha-1 N from PCU, hereafter referred to as 0, 50% and 70% PCU) were assigned to the subplots. The results indicated that the lint yield, number of bolls, boll weight, lint percentage, fiber qualities, leaf photosynthesis and fertilizer use efficiencies were significantly affected by the types of K, N fertilizers and their interaction. The K and N release characteristics of PCPC and PCU under field condition were closely matched to the nutrients requirements of cotton growth. The contents of soil available K and inorganic N were significantly augmented from the first bloom stage to the initial boll-opening stage by using PCPC and PCU compared to potassium sulfate and urea treatments. Meanwhile, PCPC and PCU interaction increased lint yields by 11.16–26.44% and 14.17–32.11% in comparison with potassium sulfate and urea in 2014 and 2015, respectively, and the maximum lint yield was achieved by the combination of 70% PCPC and 50% PCU. Besides, the boll number and boll weight were improved 5.2–18.2% and 4.75–10.29% by the PCPC and PCU treatments compared to both potassium sulfate and urea treatments, respectively. The potassium recovery efficiency (KRE) and nitrogen recovery efficiency (NRE) of PCPC and PCU treatments were significantly raised by 24.34–33.77% and 19.68–36.25%, respectively, compared with potassium sulfate and urea treatments in 2014 and 2015. PCPC owned the great potential to alter the current application of potassium fertilizer due to its ubiquitous traits. The interaction of PCPC and PCU at optimal dose was significant on cotton growth in saline soil. Consequently, the application of 70% PCPC in combination with 50% PCU is recommended to increase cotton yield and fertilizer use efficiency, and to improve the fiber quality and leaf photosynthesis properties in the Yellow River Delta area of China.

The study was to determine the long-term effects of subtropical monoculture and rotational cropping systems and fertilization on soil enzyme activities and soil C, N, and P levels. Cropping systems included continuous sorghum ( Sorghum bicolor L.), cotton ( Gossypium hirsutum L.), corn ( Zea mays L.), and cotton/sorghum rotations after 26 years of treatment imposition. Soil under continuous sorghum and continuous corn had 15% and 11%, respectively, greater C concentrations than soil under continuous cotton. Organic C was 10% higher at 0–7.5 cm than at 7.5–15 cm. Total N followed similar trends with soil depth as organic C. Continuous sorghum had 19% higher total N than other crop species and rotations. With fertilization, continuous cotton had the highest total P at 0–7.5 cm and sorghum had the highest at 7.5–15 cm. Soil total P was 14% higher at 0–7.5 than at 7.5–15 cm, and fertilization increased 15% total P compared to unfertilized soil. Arylsulfatase, alkaline phosphatase, and β-d-glucosidase activity were the highest for sorghum and the lowest for cotton. Rotation increased enzyme activities compared to continuous cotton but not for continuous sorghum. Of all crop species and rotations, continuous cotton generally showed the lowest levels of organic matter and enzyme activities after 26 years. Fertilization significantly increased the yields for all cropping systems, but rotation had no significant effect on either sorghum or cotton lint yield compared to each crop grown in monoculture. Long-term cropping did not increase soil organic matter levels beyond short-term gains, indicating the difficulty in promoting C sequestration in subtropical soils.

A non-contact near infrared imaging technique was investigated to classify cotton foreign matter.A total of 11 botanical and 5 non-botanical foreign matter materials were studied.Linear discriminant analysis achieved more than 95% accuracy in cross-validation tests.Support vector machine achieved satisfactory classification results at the pixel level on images.The non-contact hyperspectral imaging technique is promising for online classification. Cotton contaminants seriously reduce the commercial value of cotton lint and further degrade the quality of textile products. This research aims to investigate the potential of a non-contact technique, i.e., liquid crystal tunable filter (LCTF) hyperspectral imaging, to inspect foreign matter on the surface of cotton lint. The foreign matter samples used in this study included 11 types of botanical foreign matter and 5 types of non-botanical foreign matter. Hyperspectral images of the foreign matter were acquired using a LCTF hyperspectral imaging system with a spectral range from 900 to 1700nm. The mean spectra of the foreign matter and lint samples were extracted manually from the images. Linear discriminant analysis was applied to classify different types of foreign matter and cotton lint according to their spectral features. Classification accuracies of 96.5% and 95.1% were achieved with leave-one-out and four fold cross-validation, respectively. For pixel-level image classification, a majority of the pixels for different types of foreign matter were classified correctly by a support vector machine, using the top features of the minimum noise fraction transformation. The results demonstrate that non-contact liquid crystal tunable filter hyperspectral imaging is a promising method to discriminate foreign matter materials from cotton lint.

Climate change is threatening the viability of cotton production in one of the world's leading cotton regions but we do not know the magnitude of the threat and how effective the common management options are in responding to the threat. This study aims to answer these two questions by using a system modelling approach under various climate change and management scenarios. To construct local climate change scenarios (CCSs) for key cotton production areas in eastern Australia daily outputs from the CSIRO Conformal Cubic Atmospheric Model driven by four general circulation models (GCMs) were used in a stochastic weather generator, LARS-WG. These CCSs were then linked to a process-oriented cotton model (CSIRO OZCOT) to quantify the effect of changing planting times and irrigation scheduling triggers on cotton lint yield, water use, and water use efficiency (WUE) in 2030. We considered four planting times: normal planting, 15 days early, and 15 and 30 days later in both irrigated and rain-fed cotton. For irrigated cotton, we considered two soil water deficits (50 and 70 mm) below which an irrigation event was triggered in nine cotton production areas (Emerald, Dalby, St George, Goondiwindi, Moree, Bourke, Narrabri, Warren and Hillston). For rain-fed cotton, we considered three row configurations (solid, single skip and double skip) in four production areas: Emerald, Dalby, Moree and Narrabri. Simulations for irrigated cotton (access to full water, no nitrogen limitation), when compared with baseline (current climate and atmospheric CO 2 concentration with normal planting), show that lint yield, water use and WUE decreased in 2030 in the majority of study locations with both irrigation triggers under normal planting. The impact of planting time could not offset the negative impact of future climate change on cotton lint yield in 2030 across both irrigation triggers at all locations except for Dalby. The 30 day late planting and irrigation at 50 mm deficit performed better than their respective counterpart(s). Simulating rain-fed cotton (assuming full soil water profile at planting), when compared with baseline, lint yield and water use increased at Emerald and Narrabri and decreased at Dalby and Moree across row configurations in 2030 with normal planting; and WUE increased by 15.5% under future climate scenarios with normal planting. Early planting decreased lint yield by 8 to 18% at Dalby and Moree while late planting increased lint yield by up to 30%; the later the planting, the greater increase in lint yield at Emerald, Dalby and Moree. The simulation results indicate that the response of cotton to climate change is variable and region specific, which suggests that different management strategies may be required for each situation. Cotton growers will need to consider which management options best suit their circumstances.

Trees are the dominant species in agroforestry systems, profoundly affecting the performance of understory crops. Proximity to trees is a key factor in crop performance, but rather little information is available on the spatial distribution of yield and yield components of crop species under the influence of trees in agroforestry systems. Also, little information is available on how crop density may be exploited to optimize the yield in such systems. Here we studied the performance of cotton in jujube/cotton agroforestry. Field experiments were conducted in 2012 and 2013 in Hetian, Xinjiang, China. Cotton was grown at a row distance of 60 cm in three densities, 13.5, 18.0 and 22.5 plants m−2 in six m wide paths between tree lines in a jujube plantation. Plant density affected both cotton aboveground dry matter and yield significantly. The highest yield was attained at the intermediate density of 18.0 plants m−2 (20.0 plants m−2 corresponding in sole cotton), lower than the optimal density in sole cotton (25.0 plants m−2). Yield at the lower density was constrained by the low number of bolls per m2 as a direct consequence of the low density, whereas at the high plant density yield was constrained by a lower allocation of assimilates to cotton seed and lint, as a consequence of intraspecific and interspecific competitions. There were strong gradients in yield and yield components in relation to the distance from the tree rows. Leaf area and total dry matter of cotton in rows close to the tree lines were reduced, especially in the rows next to the trees. Moreover, biomass allocation to cotton fruits was reduced in these rows. Competitive influences from the trees on cotton performance extended two rows deep in a six-year old jujube stand, and even three rows deep in a seven-year old stand. Shading effects on cotton yield were compensated by increasing plant density as a result of greater boll numbers per unit ground area. Data from this study help guide the design of optimal plant density of cotton in jujube plantations and give insight in the spatial distribution and dynamics of competitive effects in agroforestry systems in general.

Cotton may suffer from waterlogging from seedling to boll-setting stage, but little is known of how it responds to temporal waterlogging. In this study, cotton was grown in a rain-shelter and subjected to 0 (control)-, 10-, 15- and 20-d waterlogging at squaring (WLS), flowering (WLF) and boll-setting (WLB) stages. The effects of timing (growth stage) and duration of waterlogging on the growth, yield and yield components as well as some physiological and molecular features of cotton were examined. The lint yield was significantly affected by timing and duration of waterlogging as well as their interaction. On average, the 10-, 15-, and 20-d waterlogging reduced lint yield by 53, 59 and 63% at squaring; 27, 37 and 55% at flowering, and 13, 15 and 24% at boll-setting. The more pronounced yield reduction under WLS than later waterlogging (under WLF and WLB) was attributed to greater reductions in biological yield, harvest index, and the resulting boll density and boll weight. Variations in yield loss due to temporal waterlogging was associated with some physiological and molecular changes: a) the chlorophyll synthesis associated gene (GhLHCB) in the main-stem leaves was down-regulated under WLS to a larger extent, leading to lower leaf photosynthesis than that under WLF or WLB; b) cotton alcohol dehydrogenase (GhADH) and pyruvate decarboxylase (PDC) genes were better up-regulated, resulting to greater activity of lactate dehydrogenase (LDH), alcohol dehydrogenase (ADH) and PDC plus lower activity of SOD, POD and CAT and higher accumulation of malondialdehyde (MDA) and H2O2 under WLS than under WLF and WLB; c) more pronounced reductions in GA and IAA content were observed under WLS than WLF and WLB. Higher sensitivity to earlier waterlogging than later waterlogging in cotton was attributed to the greater reductions in biological yield and harvest index resulting from differences in physiological and molecular adjustments of the plants.

Seed mass and oil content of the quiescent cotton seed are positively associated with seedling vigor. In contrast, seed size has been negatively associated with lint yield due to selection for cultivars with greater lint percent. The current study addressed the hypothesis that planting seed mass and total oil + protein calorie content of the quiescent cotton seed would be strongly predictive of seedling vigor across most field conditions and that the impact of seed traits on yield would be dependent upon yield environment. When considered in each yield environment, seedling vigor was positively associated with seed size and the total oil + protein calorie content per seed in four out five environments tested. Regression analysis of cultivar mean oil + protein kcal content per seed versus seedling vigor across all environments indicated a strong, positive relationship between the two parameters (r2 = 0.65). Although lint percent was positively correlated with lint yield in every environment, planting seed mass and calorie content were not correlated with lint yield in four of the five environments tested or when cultivar means for lint yield and seed characteristics were averaged across all environments. Thus, it is concluded that individual planting seed mass and total energy content for oil + protein are strong predictors of early seedling vigor. Furthermore, selecting commercially available cultivars with characteristics indicative of seedling vigor does not appear to limit lint yield in most environments tested.

The aim of this work was to study the physiological, yield and quality responses of two upland cotton cultivars (Greek and Australian), grown on light-textured soil under irrigated, Mediterranean conditions, to three potassium levels (0, 80, 160 kg K2O ha−1). Despite its pivotal role in plant physiology and growth, K supplementation is often neglected by growers due to high cost and complexity with identifying optimal K levels. A rate of 80 kg K2O ha−1 was adequate to increase both seedcotton and lint yield and improve fiber length. This was despite the absence of any response of leaf cation concentrations (K, Na, Ca, Mg, their sum and ratios) to K fertilization. On a contrary, K application affected leaf gas exchange physiology by increasing CO2 assimilation rate and stomatal conductance thus leading to reduced leaf temperature and higher leaf water potential and carbon isotope discrimination (Δ). Cultivars did not differ in the leaf gas exchange characteristics and yield but the Australian (Carmen) had markedly better fiber quality, was water conservative and sustained higher leaf K concentrations compared to Greek (Elina). Growth stage (first open flower, full bloom, first open bolls) impacted significantly leaf gas exchange physiology and cation concentrations resulting in reductions of CO2 assimilation rate, stomatal conductance, leaf water potential, specific leaf area (SLA) and N and K concentrations through the growing season. Regardless the growth stage, the lint yield was negatively correlated with Δ, Na and Na/Mg ratio highlighting the importance of the conservative use of water on cotton yield and the detrimental role of Na despite the theoretical cotton’s tolerance. Fiber length was closely correlated to leaf K at the first open boll stage indicating a putative deficiency of K which possibly accelerates cotton maturity. Overall, results of the present work emphasize the essentiality of adequate K supply for cotton physiology, growth, yield and quality, highlight the interactions of K with other nutrients and stress the cultivar selection as a means to encounter soil K inadequacy.

Novel site-specific water production functions (WPFs) were developed and tested.New zoning procedures for variable rate irrigation were established.The k-NN WPF accurately predicted cotton yield under supplemental irrigation.Sector zoning was predicted to enhance cotton yield under supplemental irrigation. Irrigation management has evolved into a top priority issue since available fresh water resources are limited. Water production functions (WPFs), mathematical relationships between applied water and crop yield, are useful tools for irrigation management and economic analysis of yield reduction due to deficit irrigation. This study aimed at (i) designing and evaluating site-specific WPFs (using k nearest neighbors (k-NN), multiple linear regression, and neural networks), (ii) simulating yield maps for uniform, sector control VRI, and zone control VRI center pivot systems using the site-specific WPFs, (iii) using the best WPF to investigate different cotton irrigation and zoning strategies using integer linear programming, and (iv) comparing soil-based and WPF-based zones for sector control VRI systems. A two-year cotton irrigation experiment (2013-2014) was implemented to study irrigation-cotton lint yield relationship across different soil types. The site-specific k-NN WPFs showed the highest performance with root mean square error equal to 0.131Mgha-1 and 0.194Mgha-1 in 2013 and 2014, respectively. The result indicated that variable rate irrigation with limited sector control capability could enhance cotton lint yield under supplemental irrigation when field-level spatial soil heterogeneity is significant. The temporal changes in climate and rainfall patterns, however, had a great impact on cotton response to irrigation in west Tennessee, a moderately humid region with short season environment. We believe site-specific WPFs are useful empirical tools for on-farm irrigation research.