Cotton Lint Research Articles

Cotton yield response to fertilizer phosphorus under a range of nitrogen management tactics

Long term crop nutrient removal is leading to decline in available phosphorus (P) in Vertisols. To improve the efficiency of P fertilizer applied for cotton production it is important to understand its interaction with other applied nutrients, particularly nitrogen (N). Four experiments were conducted to investigate the cotton lint yield response to applied P fertilizer (dispersed throughout the beds) under (i) three different N rates, (ii) various split-N application timing treatments, (iii) additional late N application and (iv) two water-run urea application strategies. Cotton lint yield response to applied P fertilizer was influenced by split-N application ratio and timing, but not N rates or water run N strategies. Additional late N application reduced lint yield and P response. Applying all the N fertilizer pre-plant along with P increased cotton lint yield by 37.2% (with 32.5% greater seed yield), compared with applying P before planting and all N fertilizer in-crop. Phosphorus application improved lint turnout by increasing cotton lint and reducing trash. These results indicate improved agronomic efficiency of applied P fertilizer dispersed throughout the beds can be possible by supplying crops with optimum N earlier in the season. The P dispersion throughout the plant beds potentially improved the P acquisition by cotton roots—where more N was applied pre-plant than in-crop. Future research needs to focus on greater understanding of the N-priming effect on cotton root growth and its impact on response to applied P.

Simulating productivity of dryland cotton using APSIM, climate scenario analysis, and remote sensing

Assessing the potential of using process-based models combined with remote sensing and climate change scenarios to understand potential climate change impacts on rainfed cotton (Gossypium hirsutum L.) productivity is crucial for major production areas, such as the East-Central Texas. This study incorporated these methods to study the impacts of future climate on biomass production, crop development, lint yield, and water use efficiency in a Texas rainfed cotton system. Based on two-years of field data obtained from a rainfed cotton field (12 ha), APSIM accurately predicted cotton biomass and lint yield during the calibration (NRMSE: biomass, 17.6%; lint, 10.8%) and validation (NRMSE: biomass, 18.8%; lint, 13.1%) processes. The deviation between simulated and observed development stages as days after sowing was less than 6 days across squaring, flowering, and boll maturity stages. A partial least square model was constructed based on satellite NDVI data and development stage accurately predicted cotton biomass (R2 = 0.93, P < 0.05), and the results agreed well with the predicted values of APSIM (R2 = 0.96, P < 0.05), which was calibrated by the cotton biomass derived from NDVI. Decreased yield was detected in almost all RCP scenarios, with the greater reductions in end-century (29.9–82.4%) scenarios than mid-century (16.2–46.7%) scenarios. For precipitation productivity, 14–80.3% of reduction was found across all future scenarios. A great reduction in reliable yield (45.0–92.0%) and reliable precipitation productivity (37.6–84.7%) were projected by future scenarios. Slight differences were detected in model validation between the two dominant soil types present at the study location; however these differences were much greater under future projections (P < 0.05), largely caused by differences in water holding capacity during critical growth stages. The results from this study suggest that future managerial and breeding efforts that focus on water use efficiency enhancement should be promoted in the future.

The Effect of Cotton Lint from Agribusiness in Diets on Intake, Digestibility, Nitrogen Balance, Blood Metabolites and Ingestive Behaviour of Rams

This study aimed to evaluate intake, digestibility, nitrogen balance, ingestive behavior, and blood parameters of sheep fed with cotton lint levels. Twenty rams weighing 30.2 ± 3.7 kg and aged 12 ± 1.3 months were distributed in a completely randomized design, with four treatments and five repetitions. Diets consisted of 50% roughage and 50% concentrate. The treatments consisted of replacing corn with cotton lint at levels of 0, 70, 140, and 210 g/kg of dry matter (DM) of the diets. The animals’ feeding behavior was determined in the last three days of the experimental period. Data were subjected to regression analysis. Decreased linear effect (p &lt; 0.05) was observed for the nutritional fraction’s intake. However, neutral detergent fibre (NDF) intake and plasma urea-N were not affected (p &gt; 0.05) by lint levels. Apparent digestibility of DM, crude protein (CP), ethereal extract (EE), and non-fibrous carbohydrate (NFC) were affected (p &lt; 0.05), except for total carbohydrate. There was a decreased linear effect (p &lt; 0.05) for the intake efficiency of DM and NDF in g/h. The nitrogen balance (g/day) and glucose levels (mg/dL) were reduced with the addition of lint in the diet. The addition of cotton lint up to 70 g/kg in DM can be used over a short-term period.

Seleção de genótipos de algodoeiro sob estresse hídrico para produtividade e qualidade de fibra

ABSTRACT The objective of this work was to select a cotton line tolerant to water stress, based on yield and fiber quality characteristics. A total of nine cotton genotypes were evaluated (six breeding lines and three commercial cultivars) in two field experiments conducted in Quixeramobim - CE without water supplementation in 2018 and 2019, respectively. Traits related to cotton lint yield and intrinsic fiber quality were measured. Data were submitted to individual and joint analysis of variance, and selection by the selection index. The genetic variability among the materials demonstrates the possibility of significant gains in the cotton selection process. The genotypes CNPA 2013 - 2235 RF FL, CNPA 2013 - 2064 RF FL and CNPA 2012 - 160 RF FL, as well as the cultivar FM 944 GL, had higher production and better fiber quality under rainfed conditions.

Optimal irrigation amount can increase cotton lint yield by improving canopy structure and microenvironment under non-film deep drip irrigation

In the arid region of Northwest China, exploring the feasibility of using non-film deep drip irrigation (DDI) instead of film drip irrigation to solve the problem of residual film pollution is an urgent task. Therefore, in this study, we hypothesized that efficient and clean production can be achieved by optimizing the irrigation amount of non-film cotton, thus improving the canopy environment and increasing the accumulation and distribution of biomass. A 2-year field experiment was performed to compare the cotton canopy microenvironment, biomass accumulation, lint cotton yield and fibre quality attributes under various irrigation levels. The experiment was arranged in a randomized complete block design with five irrigation amount treatments (m3 ha−1): 2649 (W1); 2925 (W2); 3201 (W3); 3477 (W4); and 3753 (W5). The results revealed that an increase in the irrigation amount decreased the transmittance of canopy photosynthetically active radiation (PAR) by 4.1–18.7%, while the cotton plant biomass (CPB) and reproductive organ biomass (ROB) were significantly increased by 7.6–5.9% and 22.0–54.1%, respectively. The fibre quality did not differ significantly among treatments. Moreover, under the W4 treatment, the leaf area index (LAI), mean tilt angle (MTA), canopy humidity and cotton lint yield were increased by 1.4–22.3%, 0.3–8.7%, 0.6–2.9% and 4.4–18.7%, respectively, and the canopy temperature was decreased by 0.2–2.2% as compared to the other treatments. The lint cotton yield was negatively correlated with the canopy humidity from the initial squaring stage to the full boll stage. This comprehensive evaluative analysis suggests that the optimal irrigation amount of non-film cotton is 3477 m3 ha−1 under the studied conditions, and this irrigation method is recommended as an alternative to film drip irrigation as it allows cotton to be planted without worrying about plastic pollution in irrigated agricultural areas. This study enriches the high-efficiency cotton planting technologies of non-film DDI and provides scientific guidance for the further popularization and application of non-film cotton.

Structure, Composition, and Properties of Lint Cotton Samples in Dependence of Carbonization Methods

Structure, Composition, and Properties of Lint Cotton Samples in Dependence of Carbonization Methods

Economic penalties associated with irrigation during high rainfall years in the southeastern United States

Although cotton is a drought-tolerant crop, irrigation is still needed to ensure productivity, even in the humid Southeastern United States. Irrigation must be carefully managed to limit unnecessary water use while ensuring maximum economic productivity. To better understand the costs and net returns of irrigation and cultivar selection, field experiments were conducted in 2016 and 2017 to compare cotton lint yield and fiber quality in dryland plots and plots irrigated using the University of Georgia checkbook method (UGA Checkbook) at a field site near Camilla, Georgia. Results showed cultivar differences in fiber quality parameters of micronaire and uniformity in 2016, but there was no cultivar difference in fiber quality in 2017. Cultivar differences were not observed in yield or net returns for both years. However, stoplight chart analysis of net returns indicated differences in cultivar selection for irrigated or dryland production. ST 6182 GLB2 would be a better option for a producer to minimize downside risk under dryland conditions, and PHY 333 WRF would be a better option under irrigated production. Results also indicated that broadly applying simplistic water balance approaches could decrease yield, water productivity, and net returns, especially in environments where rainfall is sufficient yet unpredictable. Overirrigation affected some fiber quality parameters but did not impact the overall market price for cotton. In 2016, irrigating according to the UGA Checkbook method negatively impacted yield and net returns. In 2017, irrigation did not affect yield but negatively impacted net returns. Average losses in net returns associated with excessive irrigation in these two wet years were $336 per hectare for net return over irrigation variable costs, and $645 per hectare for net return over irrigation total costs. Implementing robust, efficient irrigation strategies is necessary to achieve high cotton yields, reduce water usage, and improve economic returns.

Predicting and interpreting cotton yield and its determinants under long-term conservation management practices using machine learning

Accurate predictions of crop yield are an integral part of effective agricultural tactical and strategic management decisions to sustain yield without adversely impacting the environment. Process-based simulation models are widely used to predict crop yields, but their application remains limited by the requirements of substantial expertise, intensive data, and extensive calibration. Therefore, greater attention is currently being devoted to machine learning (ML) methods that are more computationally expedient. We evaluated six ML algorithms (linear regression, ridge regression, lasso regression, random forest, XGboost, and artificial neural network (ANN)) to predict cotton (Gossypium spp.) yield and determine the yield response to critical determinants using long-term (1986–2018) data on management, climate, historical yield, and point measurement of soil organic carbon (SOC) from continuous no-till (NT) cotton cropping system in west Tennessee. Data from 1986 to 2015 were used for model training, hyper-parameterization and testing, while data from 2016 to 2018 were used for independent model validation. Results showed that tree-based models (random forest and XGboost) outperformed other models in predicting lint yield. The variable importance scores, predicted by random forest model, indicated that cotton yield was more responsive to management variables (nitrogen (N) fertilization rate, cover crop, and years since NT establishment) followed by soil (SOC) and climate variables at the study site. The model identified optimal N application at 60 kg ha-1N rate for cotton lint yield, and also highlighted that the benefits of NT in enhancing yield can be achieved after 15 years of practice. The model predicted that the long-term adoption of hairy vetch (Vicia villosa), a legume cover crop, has the potential to increase cotton yield. Among the climate variables, cotton lint yield was most impacted by average maximum temperature and precipitation during flowering to open boll period. While random forest and XGboost proved to be the most effective ML models in this study, multi-site data is needed to build a more robust model with greater generalization and interpretation capabilities under a wider prediction domain.

Soil Water Dynamics and Cotton Production Following Cover Crop Use in a Semi-Arid Ecoregion

Conservation management practices such as no-tillage and cover crops can decrease soil’s susceptibility to wind erosion, but adoption of these practices has been limited on the Texas High Plains (THP) where producers are concerned with cover crop water usage. The objective of this study was to evaluate the impact of no-tillage and cover crops on cotton (Gossypium hirsutum L.) lint yield and soil water content in a deficit irrigated cropping system. Soil water was observed bi-weekly in long-term, continuous cotton systems established in 1998 that included (1) conventional tillage, winter fallow, (2) no-tillage with rye (Secale cereale L.) cover, and (3) no-tillage with mixed species cover located in Lamesa, TX, USA. Results include observations from 2018–2020 (years 21–23 of the study period). The adoption of conservation practices did not significantly reduce cotton lint yield compared to conventionally tilled, winter fallow cotton. Soil water was initially depleted with cover crops but was greater throughout the growing season following cover crop termination. Throughout the soil profile, water depletion and recharge were more dynamic with conservation practices compared to the conventionally tilled control. There were no differences in cotton water use efficiency between treatments. Results from this study indicate cover crop water usage is likely not the cause of cotton lint yield decline in this deficit irrigated semi-arid production system.

Impact of Plant Spacing and Nitrogen Rates on Growth Characteristics and Yield Attributes of Egyptian Cotton (Gossypium barbadense L.).

This current study was performed to determine the influences of plant spacing, Nitrogen (N) fertilization rate and their effect, on growth traits, yield, and yield components of cotton (Gossypium barbadense L.) cv. Giza 97 during the 2019 and 2020 seasons. A split plot experiment in three replicates was utilized whereas the cotton seeds were planted at 20, 30, and 40 cm, as main plots and nitrogen at 75, 100, and 125%, was in subplots. The results revealed that the planting spacing at 40 cm significantly (p ≤ 0.01) increased plant height, number of fruiting branches per plant, number of bolls per plant, boll weight (BW), lint percentage (L%), seed cotton yield (SCY), lint cotton yield (LCY), seed index and lint index by 165.68 cm, 20.92, 23.93, 3.75 g, 42.01%, 4.24 ton/ha, 5.16 ton/ha, 12.05, 7.86, respectively, as average in both seasons. The application of N fertilizer rate at 125% caused a maximum increase in growth and yield parameters i.e., plant height (169.08 cm), number of vegetative branches (2.67), number of fruiting branches per plant (20.82), number bolls per fruiting branch (1.39), number of bolls per plant (23.73), boll weight (4.1 g), lint percent (41.9%), seed index (11.8 g), and lint index (8.2), while the plants treated with 100% N rates exhibited highest seed cotton yield (4.3 ton/ha) and lint cotton yield (5.6 ton/ha), as average in both seasons. Combining plant spacing at 40 cm between plants with a 100% N fertilizer rate recorded the highest lint cotton yield (5.67 ton/ha), while the highest seed cotton yield (4.43 and 4.50 ton/ha) was obtained from 125% N fertilizer rate under planting spacing 20 and 40 cm, respectively. Conclusively, a wide density (40 cm) with 125% N is a promising option for improved biomass, cotton growth, yield, physiological traits, and fiber quality.

The Potential Role of Plastome Copy Number as a Quality Biomarker for Plant Products using Real-time Quantitative Polymerase Chain Reaction.

Background: Plastids are plant-specific semi-autonomous self-replicating organelles, containing circular DNA molecules called plastomes. Plastids perform crucial functions, including photosynthesis, stress perception and response, synthesis of metabolites, and storage. The plastome and plastid numbers have been shown to be modulated by developmental stage and environmental stimuli and have been used as a biomarker (identification of plant species) and biosensor (an indicator of abiotic and biotic stresses). However, the determination of plastome sequence and plastid number is a laborious process requiring sophisticated equipment. Methods: This study proposes using plastome copy number (PCN), which can be determined rapidly by real-time quantitative polymerase chain reaction (RT-qPCR) as a plant product quality biomarker. This study shows that the PCN log10 and range PCN log10 values calculated from RT-qPCR data, which was obtained for two years from leaves and lint samples of cotton and seed samples of cotton, rice, soybean, maize, and sesame can be used for assessing the quality of the samples. Results: Observation of lower range PCN log10 values for CS (0.31) and CR (0.58) indicated that the PCN showed little variance from the mean PCN log10 values for CS (3.81) and CR (3.85), suggesting that these samples might have encountered ambient environmental conditions during growth and/ or post-harvest storage and processing. This conclusion was further supported by observation of higher range PCN log10 values for RS (3.09) versus RP (0.05), where rice seeds in the RP group had protective hull covering compared to broken hull-less seeds in the RS group. To further support that PCN is affected by external factors, rice seeds treated with high temperatures and pathogens exhibited lower PCN values when compared to untreated seeds. Furthermore, the range PCN log10 values were found to be high for cotton leaf (CL) and lint (Clt) sample groups, 4.11 and 3.63, respectively, where leaf and lint samples were of different sizes, indicating that leaf samples might be of different developmental stage and lint samples might have been processed differently, supporting that the PCN is affected by both internal and external factors, respectively. Moreover, PCN log10 values were found to be plant specific, with oil containing seeds such as SeS (6.49) and MS (5.05) exhibiting high PCN log10 values compared to non-oil seeds such as SS (1.96). Conclusion: In conclusion, it was observed that PCN log10 values calculated from RT-qPCR assays were specific to plant species and the range of PCN log10 values can be directly correlated to the internal and external factors and, therefore might be used as a potential biomarker for assessing the quality of plant products.

Improving nitrogen use efficiency in irrigated cotton production

Irrigated cotton in Australia is mainly grown on heavy textured soils which are prone to waterlogging, resulting in significant losses of nitrogen (N) via denitrification and surface run-off. This study investigated fertiliser nitrogen use efficiency (fNUE) over three seasons on five commercial cotton farms using the 15N tracer technique. Fertiliser NUE was consistently low across all fertilised treatments, with on average 47% of the applied fertiliser lost and only 17% of the N taken up by the crop derived from fertiliser. There was no significant effect of different N fertiliser products and rates on cotton lint yield. High lint yields (0.9–3.6 Mg ha−1) could be achieved even without the application of N fertiliser, demonstrating mineralisation of soil organic N, residual fertiliser, or N returned with crop residues, as key source of N in these cropping systems. Using the nitrification inhibitor DMPP and overhead instead of furrow irrigation showed potential to reduce N fertiliser losses. The results demonstrate that under current on-farm management fNUE is low on irrigated cotton farms in Australia and highlight the need to account for soil N stocks and mineralisation rates when assessing optimized fertiliser rates. There is substantial scope to improve fNUE and reduce N losses without any impact on lint yield, by adjusting N fertiliser application rates, in particular in combination with the use of the nitrification inhibitor DMPP. Using overhead instead of furrow irrigation is a promising approach to improve not only water use efficiency, but also fNUE in irrigated cotton systems.

Effect of inorganic and organic sources and levels of boron on growth, yield and quality of cotton (Gossypium hirsutum) under salt stress condition

Therefore, a simple, completely factorial randomized pot experiment was conducted during 2018 at pot culture yard, Department of Soil Science and Agricultural Chemistry, Annamalai University to evaluate the effect of organic and inorganic sources and levels of boron on growth and yield, quality attributes and uptake by cotton under salt stress condition. The experiment was conducted with four levels of boron (0, 0.5, 1.0 and 1.5 mg//kg of soil) through three sources viz., borox, solubar and magnesium borohumate complexes. The cotton variety LRA5166 was used as test variety. The results revealed that application of 1.5 kg of B through magnesium borohumate (MBH) complex recorded the higher plant height (124.6 cm), leaf area index (4.82), DMP (216 g/pot), yield components like number of bolls per plant (18.20), and mean boll weight (3.92) of cotton in saline sodic soil. Furthermore, higher seed cotton yield (93.51 g/pot), seed yield (54.72 g/pot) and lint yield (33.53 72 g/pot) were also recorded. This was on par with application of 1.0 kg of B through magnesium borohumate and recorded the plant height (122.81 cm), leaf area index (4.7), DMP (213 g/pot), yield components like number of bolls per plant (17.4), and mean boll weight (3.83 g), seed cotton yield (92.71 g/pot), seed yield (54.1 g/pot) and lint yield (32.96 g/pot) and followed by S2L4 (1.5 kg of B through solubar). The conclusion made from this study is the application of boron through 1.0 kg of B through magnesium borohumate will sustainably increase the cotton yield in saline sodic soil.

Sap velocity, transpiration and water use efficiency of drip-irrigated cotton in response to chemical topping and row spacing

Directly measuring plant transpiration of field crops and determining water use efficiency are difficult but essential to understand plant-water relations. In this study, we aimed to quantify plant transpiration and water use efficiency at diurnal and daily bases using sap flow measurements in cotton growing under plastic film cover and drip irrigation in relation to row configurations and chemical topping. Field experiment was carried out in 2020–2021 in Xinjiang, China. The experiment included two topping treatments: chemical topping using heavy amount of mepiquat chloride and traditional manual topping; and two typical row spacing for machine-harvesting: equal row spacing (76 cm) and narrow-wide row spacing (10 cm + 66 cm). Sap flow was measured using a heat ratio method after cotton first flowering stage and then calculated to transpiration per plant and per unit ground area. Chemical topping increased cotton plant height by 12%, leaf area index by 13%, and stem diameter by 9% but did not affect cotton lint yield compared with manual topping across two years and row configurations. The sap velocity of drip-irrigated cotton ranged overall from 20 to 45 cm hr−1 at the daytime and close to zero at nighttime. Across two years, the daily transpiration in chemical topping after flowering was 5.57 mm d−1 and 14.8% higher than in manual topping. That in narrow-wide row spacing was higher than in equal rows. However, the water use efficiency did not differ between topping and row spacing treatments, being 5.64 kg m−3 on average for aboveground dry matter. This knowledge would be useful to optimize cotton irrigation managements and to improve crop models by knowing exact plant transpiration at both plant and system levels.

Integration of chitosan and NPK nonparticles to enhance the yield, fiber and yarn quality of Egyptian cotton

The purpose of the current study is to compare among traditional fertilizers (mineral fertilizers); N, P and K and untraditional fertilizers (nano-fertilizers); chitosan, integration of chitosan and N, P or K nano-particles with different doses of 10, 20 and 30mg/l. Mineral fertilizers were obtained from the chemical store of Soils and Water Research Institute, ARC. Nano-fertilizers were prepared in National Institute of Laser Enhanced Science (NILES), Cairo University. The studied cotton variety was Giza 94 (G94). All used cotton samples were collected from 2017 and 2018 cotton growing seasons. Cotton fiber properties was conducted at Egyptian &amp; International Cotton Classification Center (EICCC) using Fiber Classifying System (FCS), (ARC). Almost of cotton properties such as seed cotton yield, boll weight, lint percentage and lint cotton yield, cotton fiber properties; uniformity index, upper half mean, strength, elongation, reflectance percentage, yarn strength and yellowness gave a significant contribution towards final product. The conclusion of results was that nano-fertilize doses of chitosan+K 30mg/l was the best for almost studied properties followed by other nano-fertilizers chitosan+K 10 or 20mg/l, chitosan+P10,20 or 30mg/l, chitosan+N 10,20 and 30mg/l, chitosan and finally traditional fertilizers; mineral fertilizers.

Simulation of Spatiotemporal Variations in Cotton Lint Yield in the Texas High Plains

This study aimed to simulate the spatiotemporal variation in cotton (Gossypium hirsutum L.) growth and lint yield using a remote sensing-integrated crop model (RSCM) for cotton. The developed modeling scheme incorporated proximal sensing data and satellite imagery. We formulated this model and evaluated its accuracy using field datasets obtained in Lamesa in 1999, Halfway in 2002 and 2004, and Lubbock in 2003–2005 in the Texas High Plains in the USA. We found that RSCM cotton could reproduce the cotton leaf area index and lint yield across different locations and irrigation systems with a statistically significant degree of accuracy. RSCM cotton was also used to simulate cotton lint yield for the field circles in Halfway. The RSCM system could accurately reproduce the spatiotemporal variations in cotton lint yield when integrated with satellite images. From the results of this study, we predict that the proposed crop-modeling approach will be applicable for the practical monitoring of cotton growth and productivity by farmers. Furthermore, a user can operate the modeling system with minimal input data, owing to the integration of proximal and remote sensing information.

Mitigating greenhouse gas emissions and ammonia volatilization from cotton fields by integrating cover crops with reduced use of nitrogen fertilizer

Winter cover crop cultivation during the fallow season has been strongly recommended in single crop cropping systems to improve soil quality, but its impact on the soil greenhouse gas (GHG) emissions of the soil has not been extensively studied. This study aimed to investigate the effects of replacing traditional winter fallow with a cover crop combined with a reduced amount of nitrogen (N) fertilizer on ammonia (NH3) volatilization, GHG emissions, and cotton production yield. A field experiment was performed with two cropping systems (a single cotton system and February orchid (Orychophragmus violaceus L.) incorporated into a single cotton cropping system) and four N levels (0, 112.5, 168.75 and 225.0 kg N ha−1). The results showed that the incorporation of February orchid increased cotton yield, nitrous oxide (N2O) emission, NH3 volatilization, global warming potential (GWP), and net ecosystem carbon budget (NECB) under the same N application rate. Moreover, the NH3, N2O, GWP, yield GWP, and NECB increased with an increasing N application rate. Furthermore, the correlation and redundancy analysis (RDA) results indicated that N2O emissions and NH3 volatilization were positively affected by soil NO3- -N, total nitrogen (TN) and lint cotton yield. Overall, compared with the single cropping of cotton with conventional fertilization, the incorporation of February orchid with a 25% reduction in the N application rate decreased NH3 volatilization by 1.05 kg NH3-N ha−1 and N2O losses by 0.34 kg N2O-N ha−1 and resulted in a favorable cotton yield. Our results demonstrate that replacing traditional winter fallow with a cover crop combined with a N fertilizer reduction may help to mitigate soil GHG emissions and NH3 volatilization while ensuring yield in cotton production. In future studies, the evaluation of cropping system GHG emissions should be considered from a life-cycle perspective, and attention should be given to the legacy impacts of N.

The influence of country of origin effect on export marketing performance in the cotton industry of Zimbabwe

The purpose of this paper was to investigate the influence of country of origin effect on export marketing performance in the cotton industry of Zimbabwe. Specific variables studied were brand image, customer attitude, customer product evaluation and export market performance. There is little research on the influence of country of origin effect on export marketing performance in the cotton industry of Zimbabwe, hence, the need to carry out this study. The research was conducted through a survey where pre-coded structured questionnaires were administered to respondents from the 5 cotton trading companies. A total of 80 questionnaires were sent to the respondents in the cotton industry. The main data analysis method used was factor analysis using inferential statistics which are total variance explained and rotated component matrix. Hypotheses were tested using one sample T test. Cronbach’s alpha proved that the data obtained from the sample was adequate and reliable. Results from the study showed that cotton buyers consider the image of the country when evaluating products; Despite country image organizations prefer cotton lint from Zimbabwe; A positive word of mouth is spread about cotton lint from Zimbabwe; I have or would recommend Zimbabwean produced lint to other organisations; Your organizational perception of a country portrays the reputation of organisations within that country; There will always be continuous purchase of cotton lint from Zimbabwe; There is guarantee you would recommend lint from Zimbabwe. The study brought significant contribution in understanding the concept of country of origin effect in the cotton industry. The study recommended that brand image can be made positive by organizations through unique marketing strategies which can separate the perception customers have about a country to the image of the product; Organizations must ensure customer attitude is positive about the organization; The product must be of high quality so that cotton lint from can be competitive on the global market. Beside the findings, this study had limitations, including a smaller sample size. So, future studies can be done researching the same topic but using a sample which is bigger in size and a geographical delimitation which is wider.

HPPD-resistant cotton response to isoxaflutole applied preemergence and postemergence

AbstractStudies were conducted in 2019 and 2020 in Lewiston, NC, to determine the crop response of 4-hydroxyphenylpyrivate dioxygenase (HPPD)-resistant cotton to isoxaflutole (IFT) and other cotton herbicides as part of a cotton weed management program that included herbicides applied preemergence, early postemergence (EPOST), and mid-postemergence (MPOST). IFT was applied PRE at 105 g ha−1 alone and in various combinations with acetochlor, diuron, fluometuron, fluridone, fomesafen, pendimethalin, and pyrithiobac. EPOST treatments included IFT at 53 or 105 g ha−1 alone or in combination with glyphosate or glufosinate, or dimethenamid-P + glufosinate. Glyphosate + glufosinate was applied MPOST to all treatments except the nontreated control. Cotton injury from IFT applied PRE was minimal (0% to 3%). Injury following EPOST application of dimethenamid-P + glufosinate ranged from 3% to 5% and 6% to 9% in 2019 and 2020, respectively. In both years, injury from IFT applied PRE followed by IFT applied EPOST never exceeded injury from IFT applied PRE followed by dimethenamid-P + glufosinate. Isoxaflutole applied PRE followed by IFT applied EPOST at 105 g ha−1 resulted in 0% to 2% cotton injury, indicating that IFT can be applied either PRE or EPOST with minimal risk to cotton. Late-season cotton height and cotton lint yield were not affected by any herbicide treatment. The experimental HPPD-resistant cotton cultivar was minimally injured by IFT applied PRE and EPOST, it tolerated standard cotton herbicides, and yield loss was not observed. Given these results, HPPD-resistant cotton and IFT may be integrated into cotton weed management systems with minimal risk for cotton injury and provide an additional effective mechanism of action for managing troublesome weeds in cotton.

Physiological Characteristics of Cotton Subtending Leaf Are Associated With Yield in Contrasting Nitrogen-Efficient Cotton Genotypes.

Nitrogen (N) plays an important role in various plant physiological processes, but studies on the photosynthetic efficiency and enzymatic activities in the cotton subtending leaves and their contribution to yield are still lacking. This study explored the influence of low, moderate, and high N levels on the growth, photosynthesis, carbon (C) and N metabolizing enzymes, and their contribution to yield in CCRI-69 (N-efficient) and XLZ-30 (N-inefficient). The results showed that moderate to high N levels had significantly improved growth, photosynthesis, and sucrose content of CCRI-69 as compared to XLZ-30. The seed cotton yield and lint yield of CCRI-69 were similar under moderate and high N levels but higher than XLZ-30. Similarly, moderate to high N levels improved the C/N metabolizing enzymatic activities in the subtending leaf of CCRI-69 than XLZ-30. A strong correlation was found between subtending leaf N concentration with C/N metabolizing enzymes, photosynthesis, sucrose contents, boll weight, and seed cotton yield of N-efficient cotton genotype. These findings suggest that subtending leaf N concentration regulates the enzymatic activities and has a key role in improving the yield. These parameters may be considered for breeding N-efficient cotton genotypes, which might help to reduce fertilizer loss and improve crop productivity.