Cotton Research Articles

The Influence of Textile Type, Textile Weight, and Detergent Dosage on Microfiber Emissions from Top-Loading Washing Machines.

The use of washing machines to wash textiles gradually breaks down synthetic fibers like polyethylene terephthalate (PET) or polyester (PES) in diverse clothing materials, a process that is growing in notoriety because it generates microplastics (MPs). In this study, we investigated the emission of microfibers, including both microplastic fibers (MPFs) and natural fibers (MFs), from top-loading washing machines. Our investigation focused on four popular textiles with prevalent weave structures (plain, satin, and twill): (i) PES, (ii) tetron cotton (TC), (iii) chief value cotton (CVC), and (iv) cotton (CO) fabrics. This study also examined the effects of textile weight and detergent dosage on MF emissions. After washing, MFs were collected through filtration, and their concentrations were determined using micro-Fourier Transform Interferometry (μFTIR). The results showed varying concentrations of MFs in the washing effluent depending on the type of textile. Specifically, CVC exhibited the highest emission at 4022 particles/L, followed by TC, PES, and CO at 2844 particles/L, 2382 particles/L, and 2279 particles/L, respectively. The hydrophobic nature of PES makes this type of textile prone to rapid degradation in detergent-rich environments, leading to high MF emissions. Additionally, the mechanical properties of textiles, such as tensile and bending strengths, may play a crucial role in the generation of MFs in washing machines. Textiles made of CO with twill weaves demonstrated superior strength and correlated with lower emissions of MFs. In comparison, textiles made of CVC and satin weave exhibited lower mechanical properties, which could explain their high emissions of MFs. Finally, the MF emissions of textiles composed of PES and TC, which are plain weaved, could be attributed to their intermediate mechanical properties compared with those of CVC and CO.

Optimizing the Bacillus thuringiensis (Bt) protein concentration in cotton: Coordinated application of exogenous amino acids and EDTA to reduce spatiotemporal variability in boll and leaf toxins

During the boll formation stage, cotton bolls exhibit the lowest expression of Bacillus thuringiensis (Bt) insecticidal proteins. Resistance to insects varies notably among different organs, which poses challenges for controlling cotton bollworms. Consequently, an experimental strategy was designed in the 2020–2021 cotton growing season to coordinate the enhancement of protein synthesis and the attenuation of degradation. Two Bt cultivars of Gossypium hirsutum, namely the hybrid Sikang 3 and the conventional Sikang 1, were used as test materials. Three treatments were applied at the peak flowering period: CK (the control), T1 (amino acids), and T2 (amino acids and EDTA). The results show that, in comparison to the CK group, the Bt protein contents were significantly increased in both cotton bolls and their subtending leaves under the T1 and T2 treatments. The maximum levels of increase observed were 67.5% in cotton bolls and 21.7% in leaves. Moreover, the disparity in Bt protein content between cotton bolls and their subtending leaves notably decreased by 31.2%. Correlation analysis suggested that the primary physiological mechanisms for augmenting Bt protein content involve increased protein synthesis and reduced protein catabolism, which are independent of Bt gene expression levels. Stepwise regression and path analysis revealed that elevating the soluble protein content and transaminase activity, while reducing the catabolic enzyme activities, are instrumental in enhancing the Bt protein content. Consequently, the coordinated application of amino acids and EDTA emerges as a strategy that can improve the overall resistance of Bt cotton and mitigate the spatiotemporal variations in Bt toxin concentrations in both cotton bolls and leaves.

Improving performance of bamboo fluff pulp by liquid hot water pretreatment and combination with longer fibers

Bamboo has several disadvantages as a raw material for the preparation of fluff pulp, including short fiber length, a high proportion of hemicellulose and high levels of fines and non-fibrous cells. Here, the proportion of hemicellulose was reduced by liquid hot water (LHW) pretreatment. The bamboo was then kraft cooked, screened through a 100 mesh screen plate to remove fines and non-fibrous cells, and bleached to prepare bamboo pulp fibers. Changes in the functional groups and crystallinity after LHW pretreatment were investigated by Fourier-transform infrared spectroscopy and X-ray diffraction. Analysis of the cross-sectional and surface morphology of the bamboo before and after pretreatment and of the surface morphology of the fluff pulp by field emission scanning electron microscopy showed that LHW pretreatment effectively removes hemicellulose from the bamboo. Combination of the bamboo pulp fibers with softwood fiber or cotton linter fiber produced a fluff pulp fiber with improved strength and water absorption. The new bamboo-cotton and bamboo-wood mixed fiber fluff pulps outperformed a branded commercial fluff pulp.

Estimation model of potassium content in cotton leaves based on hyperspectral information of multileaf position

Potassium (K) is a highly mobile nutrient element that continuously adjusts its demand strategy among and within cotton leaves through redistribution. This indirectly leads to variations in the leaf potassium content (LKC, %) at different leaf positions. However, owing to the interaction between light and leaf age, leaf sensitivity at different positions to this change varies, including the reflection and absorption of the spectrum. How to selecting the optimal monitoring leaf position is an important factor in quickly and accurately evaluation of cotton LKC using spectral remote sensing technology. Therefore, this study proposes a comprehensive multileaf position estimation model based on the vertical distribution characteristics of LKC from top to bottom. This is aimed at achieving an accurate estimation of cotton LKC and optimizing the strategy for selecting the monitored leaf position. Between 2020 and 2021, we collected hyperspectral imaging data of the main stem leaves at different positions from top to bottom (Li, i=1, 2, 3, …, n), during the cotton budding, flowering, and boll setting stages. Vertical distribution characteristics, sensitivity differences, and spectral correlations of LKC at different leaf positions were investigated. Additionally, the optimal range of the dominant leaf position for monitoring was determined. Partial least squares regression (PLSR), random forest regression (RFR), support vector machine regression (SVR), and the entropy weight method (EWM) were used to establish LKC estimation models for single leaf and multileaf positions. The results showed a vertical heterogeneous distribution of cotton LKC, with LKC initially increasing and then gradually decreasing from top to bottom, and the average LKC of cotton reaches its maximum value at flowering stage. The upper leaf position demonstrated greater sensitivity to K and exhibited a stronger correlation with the spectrum. The selected dominant leaf positions for the three growth stages were L1–L5, L1–L4, and L1–L2, respectively. Based on the dominant leaf position monitoring range, the optimal single leaf position models for estimating LKC during the three growth stages were PLSR-L4, PLSR-L1, and SVR-L2, with The coefficient of determination of the validation set (R2val) of 0.786, 0.580, and 0.768, and the root-mean-square error of the validation set (RMSEval) of 0.168, 0.197, and 0.191, respectively. The multileaf position LKC estimation model was constructed by EWM with R2val of 0.887, 0.728, and 0.703, and RMSEval of 0.134, 0.172, and 0.209, respectively. In contrast, the newly developed multileaf position comprehensive estimation model yielded superior results, improving the stability of the model on the basis of high accuracy, especially during the budding and flowering stages. These findings hold significant importance for investigating cotton LKC spectral models and selecting suitable leaf positions for field monitoring.

Alleviation of cotton growth suppression caused by salinity through biochar is strongly linked to the microbial metabolic potential in saline-alkali soil

Biochar is a typical soil organic amendment; however, there is limited understanding of its impact on the metabolic characteristics of microorganisms in saline-alkaline soil microenvironment, as well as the advantages and disadvantages of plant-microorganism interactions. To elucidate the mechanisms underlying the impact of saline-alkali stress on cotton, a 6-month pot experiment was conducted, involving the sowing of cotton seedlings in saline-alkali soil. Three different biochar application levels were established: 0 % (C0), 1 % (C1), and 2 % (C2). Results indicated that biochar addition improved the biomass of cotton plants, especially under C2 treatment; the dry weight of cotton bolls were 8.15 times that of C0. Biochar application led to a rise in the accumulation of photosynthetic pigments by 8.30–51.89 % and carbohydrates by 7.4–10.7 times, respectively. Moreover, peroxidase (POD) activity, the content of glutathione (GSH), and ascorbic acid (ASA) were elevated by 23.97 %, 118.39 %, and 48.30 % under C2 treatment, respectively. Biochar caused a reduction in Na+ uptake by 8.21–39.47 %, relative electrical conductivity (REC) of plants, and improved K+/Na+ and Ca2+/Na+ ratio indicating that biochar alleviated salinity-caused growth reduction. Additionally, the application of biochar enhanced the absorption intensity of polysaccharide fingerprints in cotton leaves and roots. Two-factor co-occurrence analysis indicated that the key differential metabolites connected to several metabolic pathways were L-phenylalanine, piperidine, L-tryptophan, and allysine. Interestingly, biochar altered the metabolic characteristics of saline-alkali soil, especially related to the biosynthesis and metabolism of amino acids and purine metabolism. In conclusion, this study demonstrates that biochar may be advantageous in saline soil microenvironment; it has a favorable impact on how plants and soil microbial metabolism interact.

Impact of numerous larval diets on the biology of pink bollworm Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae) under laboratory conditions

BackgroundPink bollworm, Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae) has become a potential pest of cotton by causing substantial yield losses around the world including Pakistan. Keeping in view the facts like limited research investigations, unavailability, and high cost of artificial diet’s constituents and their premixes, the present research investigations on the dietary aspect of P. gossypiella were conducted. The larvae of P. gossypiella were reared on different diets that were prepared using indigenous elements. The standard/laboratory diet comprised of wheat germ meal 34.5 g, casein 30.0 g, agar–agar 20.0 g, sucrose 10.0 g, brewer’s yeast 5.0 g, α-cellulose 1.0 g, potassium-sorbate1.5 g, niplagin 0.5 g, decavitamin 0.01 g, choline-chloride 0.06 g, maize-oil 3.30 g, honey 2.0 g, and water 730.0 mL. Alternatives to cotton bolls and wheat germ meal were okra seed sprouts, okra fruit, cottonseed meal, and okra seed meals, which were included in the study to introduce an efficient and economic mass-rearing system.ResultsThe larval development completed in 19.68 d ± 0.05 d with a weight of 20.18 mg ± 0.20 mg at the fourth instar fed on the cottonseed meal-based diet instead of wheat germ meal based diet. On the same diet, 84.00% ± 4.00%, 17.24 mg ± 0.03 mg, and 7.76 d ± 0.06 d were recorded as pupae formation, pupal weight, and pupal duration, respectively. Adult emergence, 76.00% ± 1.00% was recorded from pupae collected from larvae raised on cottonseed meal-based diet. These male and female moths lived for 40.25 d ± 0.10 d, and 44.34 d ± 0.11 d, respectively. Females deposited 21.28 ± 0.04 eggs per day with the viability of 65.78% ± 0.14%. The larval mortality at the fourth instar was 37.20% ± 1.36% and malformed pupation of 12.00% ± 1.41% was recorded. Replacement of wheat germ meal with that of local meals (cottonseed and okra seed) in the standard laboratory diet has saved 463.80 to 467.10 PKR with 1.62 to 1.63 cost economic returns, respectively.ConclusionThis research is of novel nature as it provides a concise and workable system for the economic and successful rearing of P. gossypiella under laboratory conditions.

Self-Healing and Wide Temperature-Tolerant Cellulose-Based Eutectogels for Reversible Humidity Detection.

A kind of ionic conductive gel (also named eutectogel) is developed from an inorganic salt (ZnCl2)-based deep eutectic solvent (DES). The ternary DES consists of ZnCl2, acrylic acid, and water, and cotton linter cellulose is introduced into the DES system to tailor its mechanical and conductive properties. Enabled by the extensive hydrogen bonds and ion-dipole interactions, the obtained eutectogel displays superior ionic conductivity (0.33 S/m), high stretchability (up to 2050%), large tensile strength (1.82 MPa), and wide temperature tolerance (-40 to 60 °C). In particular, the water-induced coordination interactions can tune the strength of hydrogen/ionic bonds in the eutectogels, imparting them with appealing humidity sensing ability in complex and extreme conditions.

Activated carbon fibers from recycled acrylic and cotton for carbon dioxide capture

AbstractIn this study, activated carbon fibers (ACFs) were produced from mechanically recycled acrylic (PAN) and cotton (CO) fibers and their blend (PAN/CO) in felt form as an adsorbent for carbon dioxide capture. For this purpose, stabilization, carbonization, and chemical activation processes were applied consecutively. The effects of recycled fiber type, carbonization temperature, and activation agent impregnation ratio were investigated. The resultant ACFs were characterized by elemental analysis, SEM, FTIR, XPS, and BET analyses, and carbon dioxide adsorption capacity was tested. It was observed that the fibrous structure of all samples was preserved at all stages, although the fiber diameters were reduced. The maximum quantity of adsorbed CO2 was found to be 3.79, 3.47, and 3.28 mmol CO2/g for recycled PAN, CO, and PAN/CO based samples, respectively, at 298 K at a relative pressure of 0.989. It was conducted that the carbon dioxide adsorption performance was affected by both the ACF surface area and the nitrogen content in the structure. It was concluded that recycled fiber‐based ACFs as CO2 adsorbents could be successfully produced with reasonable adsorption performance as a sustainable alternative.Highlights Activated carbon fibers were produced from recycled acrylic and cotton fibers Fibrous structure was preserved, but fiber diameters decreased Reasonable carbon dioxide adsorption capacity was attained Recycled fiber‐based ACFs could be a sustainable alternative to CO2 adsorbents

INSECTICIDAL IMPACTS ON FECUNDITY AND LARVAL DAMAGE POTENTIALS OF PINK BOLLWORM Pectinophora gossypiella

Pink bollworm (Pectinophora gossypiella) is one of the most notorious insects causing severe damage to cotton crops thought the world. A huge amount of different chemical formulations has been used for the control of P. gossypiella population that affects its biology. The present research was executed to determine the influence of insecticides on adult fecundity and boll damage potentials by the larvae. The results elucidated that a mixture of Deltamethrin+Triazophos had a maximum impact in fecundity reduction and boll damage by the larva when tested at one, three and twenty-four hours of post-application intervals (PAI). The damage to cotton bolls was in the ranges of 27.50±0.57 to 57.50±1.44 at 3 to 144-hours PAIs respectively. Damage to cotton bolls and reduction in fecundity was at the highest 82.50±1.34, and 49.65±1.51% when a mixture of Deltamethrin+Triazophos and Alpha-Cypermethrin were applied at 144-hours PAI respectively. The experimental results highlighted the critical efficacy of the test insecticide for the control of P. gossypiella by reducing the boll damage and oviposition at different intervals of application.

Zinc Finger Protein8 (GhZFP8) Regulates the Initiation of Trichomes in Arabidopsis and the Development of Fiber in Cotton.

Cotton is one of the most important natural fibers used in the textile industry worldwide. It is important to identify the key factors involved in cotton fiber development. In this study, zinc finger protein8 (GhZFP8) encoding a C2H2 transcription factor (TF) was cloned from cotton. qPCR showed that the transcripts of GhZFP8 in cotton were detected in the leaves and fibers at 3, 6, and 30 days post-anthesis (DPA), but not in the roots, stems, or flowers. The overexpression of GhZFP8 increased the trichome number on the siliques, leaves, and inflorescence, but inhibited the growth. The expression of trichome development and cell-elongation-related genes decreased obviously in GhZFP8 overexpressor Arabidopsis. Indole-3-acetic acid (IAA) and 1-Aminocyclopropanecarboxylic acid (ACC) contents were much higher in GhZFP8 overexpressors than that found in the wild type, but the gibberellin (GA) content was lower. The interference of GhZFP8 in cotton caused smaller bolls and shorter fibers than that of the control. The results of DNA affinity purification (DAP)-seq showed that GhZFP8 could bind to the promoter, exon, intron, and intergenic region of the target genes, which are involved in photosynthesis, signal transduction, synthesis of biomass, etc. Our findings implied that GhZFP8 processed multiple biological functions and regulated the development of cotton fiber.

3D reconstruction and characterization of cotton bolls in situ based on UAV technology

Phenotypic traits at the organ scale hold significant importance in the realm of plant breeding, notably in evaluating genetic diversity, selecting innovative cultivars, and forecasting potential yield. Ground platforms, despite delivering accurate results in organ-scale phenotypic studies, frequently exhibit limitations concerning efficiency and adaptability, and can adversely affect the soil. The Unmanned Aerial Vehicle (UAV) platform emerges as an innovative medium, distinguished by its high-throughput and adaptability, thus offering immense prospects in phenotypic research. Nonetheless, its precision within the organ scale warrants further investigation. As a notable economic plant species, cotton (Gossypium spp.) provides the textile industry with its essential raw material through the fruit it bears, the cotton boll. This study, employing the characterization of cotton boll breeding materials as an example, scrutinizes the capability of UAV platforms in executing precise enumeration and yield estimation of three-dimensional (3D) cotton bolls in agricultural fields. An innovative route, the Cross-circling oblique (CCO) route, was employed in conjunction with lightweight UAVs for reconstructing a 3D point cloud of cotton bolls in the field, and juxtaposed against the traditional nadir route. A comprehensive process was also developed for characterizing the quantity, volume, and spatial distribution of cotton bolls, further facilitating yield estimation. The CCO-produced point cloud demonstrated a superior completeness compared to the nadir-produced point cloud, proving capable of effectively mitigating occlusion in the middle and lower sections, thereby procuring a more comprehensive 3D cotton boll. In terms of cotton boll counting (R2 = 0.92 vs R2 = 0.73) and yield estimation (seed cotton: R2 = 0.7 vs R2 = 0.62, lint cotton: R2 = 0.75 vs R2 = 0.55), the precision of the CCO-derived point cloud surpassed that of the nadir-derived point cloud considerably. Notably, yield estimations were more precise when based on cotton boll count for seed cotton, and on boll volume for lint cotton. Utilizing the high-precision CCO-produced cotton boll point cloud, an analysis was conducted on the spatial distribution of cotton bolls for all breeding materials, and the yield was subsequently projected. The contribution of this study lies in the high-throughput capture of organ-scale traits of field cotton bolls using the UAV-based CCO route, enabling accurate yield estimation. This approach may also be applicable to extracting organ-scale traits of other field crops. It demonstrates the immense potential of combining UAV platforms with the CCO route for high-throughput acquisition of crop organ-scale traits, which could become a powerful tool in plant breeding.

Disentangling social impacts in global value chains through structural path analysis: Investigating forced labor in the cotton industry

AbstractThis analysis proposes an analytical method to trace the precise pathways through which impacts from a specific origin are disseminated worldwide and embodied in high‐income nations' consumption. Our methodological approach is based on a multi‐regional input–output model developed using EXIOBASE data for 2019. The model is extended with the structural path analysis (SPA) methodology, which allows us to trace and quantify the critical interactions in the impacts' dissemination process from their origin until reaching their destination as final demand in a specific industry and region. The SPA method is explored both in gross and net terms as complementary perspectives to disentangle the complexity of global value chains, which is the main contribution of our approach. The net assessment accounts just for interindustry transactions, whereas the gross analysis considers all steps of the value chain, even those occurring at an intraindustry level. In this work, we analyze a case study to expose the features of this proposal, which focuses on assessing the global reach of forced labor in the cotton industry in the two leading worldwide cotton producers. Textile global value chains are intricate and complex, making it hard to trace the negative social impacts linked to them. Therefore, a deeper understanding of how forced labor is disseminated worldwide until reaching developed nations is necessary to shed light on the social sustainability debate. Although this kind of forced labor seems to be a regional affair, our results show that more than 13% of the estimated forced workers are attributed to the European Union and the United States consumption, respectively, with apparel, footwear, and textiles as key goods embodying these workers. After analyzing the specific paths of dissemination linked to the fashion demand of the European Union and the United States, our key findings show the predominant role of the Chinese and Indian textile industries in most paths given the high number of intrasectoral transformations inside this sector. We also show that forced labor in the Chinese cotton industry is even more distant to the final consumer than usual unskilled labor, which is an additional obstacle to its traceability.

Laboratory evaluation of toxicity of selected insecticides against egg and larval stages of cotton pink bollworm, Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae)

BackgroundThe cryptic nature of pink bollworm Pectinophora gossypiella (Saunders) larvae enables its reduced vulnerability to insecticidal control. Further, the development of resistance against Bacillus thuringiensis (Bt) toxins posed a serious threat to transgenic cotton cultivation. This necessitated determining the critical timing of spray applications on the control effectiveness. This study assessed the influence of egg age (freshly laid vs. three-day-old) and the location of larvae (directly exposed to the insecticide residues on the boll rind vs. burrowed inside the bolls) on insecticide control efficacy.ResultsThe results revealed a significant decrease in the ovicidal activity of tested insecticides with an increase in the age of eggs from one day old to three days old (paired t-test, P < 0.05). The larvae directly exposed to the insecticide residues on the boll rind were more susceptible (> 80% mortality) than the larvae exposed after they had burrowed inside the bolls (< 49% mortality). The inhibitory effects of tested insecticides on developmental biology were more pronounced in the experiment on pre-larval release insecticide treatment compared with insecticide treatment given post-larval release and entry inside the bolls.ConclusionEgg age influences the insecticide susceptibility, as does the larval location, directly exposed vs burrowed inside the bolls. Older eggs and the larvae that had burrowed inside the green bolls of cotton were relatively less susceptible to the insecticide treatments. The toxic effects of insecticides on egg and larval stages were primarily ephemeral. These findings are significant for devising a comprehensive strategy for pink bollworm management on a sustainable basis.

Optimizing cotton yield through appropriate irrigation water salinity: Coordinating above- and below-ground growth and enhancing photosynthetic capacity

The employment of brackish water for irrigation holds considerable potential for addressing the shortfall of freshwater resources in arid regions. It is crucial to discern the impact of salinity on agricultural output and its mechanisms when irrigating with brackish water. Here, a two-year field experiment (2021–2022) was undertaken in Xinjiang, China to assess the effects of water salinity (0.85 g L−1, CK; 3 g L−1, S1; 5 g L−1, S2; and 8 g L−1, S3) on the growth, photosynthesis, carbon accumulation, and cotton yield under mulched drip irrigation. Results showed that, compared to CK, the S1 treatment led to increased biomass, the boll capacity of the root system (BCR), and a reduced root-to-shoot ratio (R/S). In addition, the S1 treatment enhanced the net photosynthetic rate (Pn) and chlorophyll content (Chl) of cotton, enhancing the total carbon accumulation of boll (Cboll) and consequently, the seed cotton yield. However, the higher salinity treatments, S2 and S3, demonstrated a detrimental impact on these indicators. In comparison to CK, the S1 treatment showed a yield increase of 5.92% and 4.76% in the respective two years, yet the S2 and S3 treatments showed a yield decrease of 5.55–15.77% and 5.06–16.74%. The application of a structural equation model (SEM) elucidated a direct effect of photosynthetic parameters (Pn and Chl) and biomass characteristics (total biomass, R/S, and BCR) on yield. These factors also indirectly modulated seed cotton yield through the Cboll/Croot ratio. These results suggest that irrigation with brackish water of 3 g L−1 optimizes cotton production by coordinating crop growth of aboveground and underground parts. This study offers practical strategies for the cotton industry to enhance yields under brackish water irrigation.

Genome-wide identification of the key Kinesin genes during fiber and boll development in upland cotton (Gossypium hirsutum L).

Kinesin is a kind of motor protein, which interacts with microtubule filaments and regulates cellulose synthesis. Cotton fiber is a natural model for studying the cellular development and cellulose synthesis. Therefore, a systematic research of Kinesin gene family in cotton (Gossypium spp.) will be beneficial for both understanding the function of Kinesin protein and assisting the fiber improvement. Here, we aimed to identify the key Kinesin genes present in cotton by combining genome-wide expression profile data, association mapping, and public quantitative trait loci (QTLs) in upland cotton (Gossypium hirsutum L.). Results showed that 159 Kinesin genes, including 15 genes of the Kinesin-13 gene subfamily, were identified in upland cotton; of which 157 Kinesin genes can be traced back to the diploid ancestors, G. raimondii and G. arboreum. Using a combined analysis of public QTLs and genome-wide expression profile information, there were 29 QTLs co-localized together with 28 Kinesin genes in upland cotton, including 10 Kinesin-13 subfamily genes. Genome-wide expression profile data indicated that, among the 28 co-localized genes, seven Kinesin genes were predominantly expressed in fibers or ovules. By association mapping analysis, 30 Kinesin genes were significantly associated with three fiber traits, among which a Kinesin-13 gene, Ghir_A11G028430, was found to be associated with both cotton boll length and lint weight, and one Kinesin-7 gene, Ghir_D04G017880 (Gh_Kinesin7), was significantly associated with fiber strength. In addition, two missense mutations were identified in the motor domain of the Gh_Kinesin7 protein. Overall, the Kinesin gene family seemingly plays an important role in cotton fiber and boll development. The exploited Kinesin genes will be beneficial for the genetic improvement of fiber quality and yield.

The Creation of a Gendered Division of Labor in Mule Spinning: Evidence from Samuel Oldknow, 1788–1792

The spinning mule was one of the most important innovations in the rise of the British cotton industry during the Industrial Revolution. First introduced in 1780, the mule’s diffusion overturned the traditional division of labor in spinning from women to men. This article produces new insights on this process by examining the business records of Samuel Oldknow, a pioneer of fine cotton manufacturing and an early adopter of the technology during the understudied transition period of the late 1780s and early 1790s, when the machine was still hand powered before the factory system. It demonstrates that strength was the most important factor in shaping the gendered division of labor in mule spinning. Although no direct gender-pay discrimination is evident, men’s earnings were higher because of the physical effort required to operate the larger mules that more easily produced the finest yarns that secured the highest piece rates. Crucially, this shift of the gender division of labor predated factory mule spinning.

Ntuma - the Cotton Village of Nagaland, North East India

India is believed to be the original home of the cotton plant. Cotton occupies about 4.7 per cent of the total cropped area in the country. Cotton is the most important fibre crop of the entire world. It provides the basic raw material to the cotton textile industry. The article is based on the practice of organic cotton cultivation in Nagaland, a tribal State in India.&#x0D; Ntuma, a village in Nagaland, also called Cotton village, this research work is on Ntuma and its contiguous villages. These tribal villages, especially Entuma used to cultivate organic cotton decades back for hundreds of livelihoods. People don’t always think about organic when it comes to the clothes we wear, the sheets we sleep on, the personal care items we depend on, and the mattresses in our bedrooms. But organic cotton is one of the most important choices people can make for the environment, because it supports a healthy ecosystem and prevents the use of toxic synthetic chemicals.&#x0D; A deep dive into the environmental benefits of organic cotton production, the importance of avoiding synthetic chemicals, the role of organic cotton when it comes to climate change mitigation, and the benefits of organic cotton to water and biodiversity is admirable. The craft people everywhere use their hands and soul to make the world a better place. In this context, artisans of Ntuma, it’s contiguous villages in Peren district or for so the entire Nagaland is an example. Years back people of these villages, especially the women, used to cultivate organic cotton and make fabulous tribal textile from that which with the passage of time got eroded. With imagination, and subtle intensity, the weaving of Nagaland pays homage to the indomitable spirit of its creators. &#x0D; May be in a small way organic cotton cultivation and its further value additions may help closing the SDG gap, an appreciation for Tough-To-Decarbonize Industries, accelerating gender parity, youth perspectives, defeating the climate and health nexus and promoting agricultural growth.

Fractionation and Lability of Phosphorus Species in Cottonseed Meal-Derived Biochars as Influenced by Pyrolysis Temperature.

Defatted cottonseed meal (CSM), the residue of cottonseeds after oil extraction, is a major byproduct of the cotton industry. Converting CSM to biochar and utilizing the goods in agricultural and environmental applications may be a value-added, sustainable approach to recycling this byproduct. In this study, raw CSM was transformed into biochar via complete batch slow pyrolysis at 300, 350, 400, 450, 500, 550, and 600 °C. Thermochemical transformation of phosphorus (P) in CSM during pyrolysis was explored. Fractionation, lability, and potential bioavailability of total P (TP) in CSM-derived biochars were evaluated using sequential and batch chemical extraction techniques. The recovery of feed P in biochar was nearly 100% at ≤550 °C and was reduced to <88% at 600 °C. During pyrolysis, the organic P (OP) molecules predominant in CSM were transformed into inorganic P (IP) forms, first to polyphosphates and subsequently to orthophosphates as promoted by a higher pyrolysis temperature. Conversion to biochar greatly reduced the mobility, lability, and bioavailability of TP in CSM. The biochar TP consisted of 9.3-17.9% of readily labile (water-extractable) P, 10.3-24.1% of generally labile (sequentially NaHCO3-extractable) P, 0.5-2.8% of moderately labile (sequentially NaOH-extractable) P, 17.0-53.8% of low labile (sequentially HCl-extractable) P, and 17.8-47.5% of residual (unextractable) P. Mehlich-3 and 1 M HCl were effective batch extraction reagents for estimating the "readily to mid-term" available and the "overall" available P pools of CSM-derived biochars, respectively. The biochar generated at 450 °C exhibited the lowest proportions of readily labile P and residual P compounds, suggesting 450 °C as the optimal pyrolysis temperature to convert CSM to biochar with maximal P bioavailability and minimal runoff risk.

Production of filter material from various natural fibers

In this study, a composite filter paper was fabricated using cellulose derived from Flax and cotton linters, along with the incorporation of basalt fiber. The aim was to develop a filter paper with enhanced filtration performance and mechanical strength.The composition and properties of the mineral filler employed in the preparation of the filter paper were thoroughly investigated. The mineral filler, which played a crucial role in influencing the properties of the composite, was carefully selected and characterized. Its particle size, surface area, and chemical composition were analyzed to understand its impact on the filtration efficiency and mechanical integrity of the filter paper.To evaluate the performance of the composite filter paper, comprehensive testing methods were employed. The filtration efficiency, pressure drop across the filter, and mechanical strength properties such as tensile strength and burst strength were assessed. These tests provided quantitative data to determine the effectiveness of the composite filter paper in capturing particles of varying sizes and its structural stability during the experimental investigation were presented in graphical form to provide a clear visual representation of the data. These graphs allowed for easy interpretation and comparison of the properties and performance of the composite filter paper under different conditions.

YOLO SSPD: a small target cotton boll detection model during the boll-spitting period based on space-to-depth convolution.

Cotton yield estimation is crucial in the agricultural process, where the accuracy of boll detection during the flocculation period significantly influences yield estimations in cotton fields. Unmanned Aerial Vehicles (UAVs) are frequently employed for plant detection and counting due to their cost-effectiveness and adaptability. Addressing the challenges of small target cotton bolls and low resolution of UAVs, this paper introduces a method based on the YOLO v8 framework for transfer learning, named YOLO small-scale pyramid depth-aware detection (SSPD). The method combines space-to-depth and non-strided convolution (SPD-Conv) and a small target detector head, and also integrates a simple, parameter-free attentional mechanism (SimAM) that significantly improves target boll detection accuracy. The YOLO SSPD achieved a boll detection accuracy of 0.874 on UAV-scale imagery. It also recorded a coefficient of determination (R2) of 0.86, with a root mean square error (RMSE) of 12.38 and a relative root mean square error (RRMSE) of 11.19% for boll counts. The findings indicate that YOLO SSPD can significantly improve the accuracy of cotton boll detection on UAV imagery, thereby supporting the cotton production process. This method offers a robust solution for high-precision cotton monitoring, enhancing the reliability of cotton yield estimates.