Effects of planting dates and shading on carbohydrate content,yield,and fiber quality in cotton with respect to fruiting positions

Two cotton（Gossypium hirsutum L.） cultivars, Kemian 1（cool temperature-tolerant） and Sumian 15（cool temperaturesensitive） 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.

THE ISSUES & RESEARCH TOPICS ON COTTON PLANTING IN XINJIANG, CHINA

In this article , the present state of cotton production in Xinjiang is introduced. The strong points and problems in cotton production are discussed in detail. In addition, cotton research advances are reviewed in a comprehensive manner. In consideration of all this, the authors expound some monographic topics and disciplinary projects regarding Xinjiang cotton research which are to be implemented in the years to come.

Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images

Leaf population chlorophyll content in a population of crops, if obtained in a timely manner, served as a key indicator for growth management and diseases diagnosis. In this paper, a three-layer multilayer perceptron （MLP） artificial neural network （ANN） based prediction system was presented for predicting the leaf population chlorophyll content from the cotton plant images. As the training of this prediction system relied heavily on how well those leaf green pixels were separated from background noises in cotton plant images, a global thresholding algorithm and an omnidirectional scan noise filtering coupled with the hue histogram statistic method were designed for leaf green pixel extraction. With the obtained leaf green pixels, the system training was carried out by applying a back propagation algorithm. The proposed system was tested to predict the chlorophyll content from the cotton plant images. The results using the proposed system were in sound agreement with those obtained by the destructive method. The average prediction relative error for the chlorophyll density （μg cm^-2） in the 17 testing images was 8.41%.

Advances in Cotton Tolerance to Heavy Metal Stress and Applications to Remediate Heavy Metal-Contaminated Farmland Soil

Heavy metal-contaminated soil is one of the major environmental pollution problems of agricultural production and human health in the world.Remediation of heavy metals in soil is one of the most popular research subjects.Different remediation strategies have been reported to remove heavy metals from contaminated soil,among which phytoremediation is the most important one.Compared with other major crops,cotton shows the strongest and most widespread resistance to abiotic stresses,such as heavy metals.Although heavy metal stress adversely affects the growth and development of cotton,cotton possesses a set of sophisticated stress-resistance strategies.As the main product of cotton is nonedible fibers,which have a large biomass and strong heavy metal absorption and enrichment capacities,cotton is an ideal crop to restore heavy metal-contaminated soils and has unique advantages in terms of both ecological and economic benefits,with great application prospects.In this review,based on domestic and foreign research results in recent years,the effects of heavy metals on cotton growth and product quality were analyzed,the heavy metal absorption,accumulation,translocation and enrichment characteristics of cotton plants were summarized,and the adaptation and tolerance mechanisms of cotton to heavy metals were explored.Furthermore,the view that cotton is an effective crop to remediate heavy metal pollution in farmland soil has been proposed,and popularization and application suggestions for planting cotton to repair heavy metal pollution have been put forward to provide a reference for the comprehensive evaluation of the economic feasibility of cotton to repair heavy metal pollution in farmland soil.

Impact of <i>Amegilla calens</i>and <i>Apis mellifera</i>Pollination on <i>Gossypium hirsutum</i>var. QR₁302 Flowers at Tchabbal-Mounguel (Ngaoundéré, Cameroon)

The investigations were carried out from September 10 through October 13, 2017 at Tchabbal-Mounguel. On Gossypium hirsutum flowers, investigations were done on many aspects of the pollination services of Amegilla calens and Apis mellifera. G. hirsutum flowers were observed to study the activity of A. calens and A. mellifera and to evaluate their impacts on fruits and seed yields of this Malvaceae. The treatments consisted of 120 flowers left for free pollination, 120 flowers protected from insects using gauze bag nets, 200 protected flowers and visited exclusively by A. calens and A. mellifera and 100 protected flowers then opened and closed without any visit of insects or any other organisms. The results show that on cotton flowers, foragers of A. calens and A. mellifera highly collect nectar and pollen on its flowers. The highest mean number of individuals simultaneously active per 1000 flowers is 587 for A. calens and 526 for A. mellifera. Through their pollinating efficiency, A. calens and A. mellifera caused a significant increase in the fruiting rate by 7.00% and 17.33%, the number of seeds per fruit by 44.20% and 18.32% and the normal seeds by 47.78% and 5.66% respectively. Therefore, the conservation of the nests of A. calens and colonies of A. mellifera around G. hirsutum plantations are to be recommended to improve the fruit and seed yields of this Malvaceae.

Functional Analysis of Nodulin-like Promoter in Transgenic Cotton Plants

For the first time, a nodulin-like gene promoter was isolated from Gossypium hirsutum L. Guo Y 18 by means of inverse PCR. Three plant expression vectors were constructed for functional identification of the promoter. These vectors were different only in promoter regions; three truncations of the nodulinlike promoter took the place of the CaMV35S promoter in the pBI 121 plant expression vector. Then, the three vectors were introduced into cotton plants via the pollen tube pathway. The expression patterns of the gus gene driven by nodulin-like promoter truncations were investigated in the offspring of transgenic cotton plants. Histochemical GUS staining and fluorescence quantitative analysis were performed to achieve this goal. The results showed that the nodulin-like promoter was a strong, highly reproductive organspecific promoter, which demonstrated a much higher driver activity than the CaMV35S promoter did in cotton reproductive organs, but relatively lower activity in vegetation. Identification of the speciality and strength-determining regions of the nodulin-like promoter was also undertaken.

Integration and inheritance stability of foreign Bt toxin gene in the bivalent insect-resistant transgenic cotton plants

Genetic and expressional stability of Bt toxin gene is crucial for the breeding of insect-resistant transgenic cotton varieties and their commercialization. Genomic Southern blot analysis of R3, R4 and R5 generations of bivalent transgenic insect-resistant cotton plants was done in order to determine the integration, the copy number and the inheritance stability of Bt toxin gene in the transgenic cotton plants. The results indicated that there was a 4.7 kb positive band in the Southern blot when the genomic DNA of the bivalent transgenic insect-resistant cotton plants and the positive control (the plasmid) were digested with HindⅢ respectively. This result proved that the Bt toxin gene had been integrated into the genome of the cotton in full length. There is only one XhoⅠ restriction site in the Bt toxin gene. Southern blot analysis indicated that many copies of Bt toxin gene had been integrated into the genome of the cotton when the genomic DNA of transgenic plants was digested with XhoⅠ. Among them, there were four copies (about 17.7, 8, 5.5 and 4.7 kb in size) existing in all the tested plants of R3, R4 and R5 generations. The preliminary conclusion was that there were more than four copies of Bt toxin gene integrated into the genome of the cotton, among them, more than one copy can express and inherit steadily. This result provides a scientific basis for the breeding of the bivalent insect-resis- tant transgenic cotton plants and its commercialization.

Influences of elevated CO2 and pest damage on the allocation of plant defense compounds in Bt-transgenic cotton and enzymatic activity of cotton aphid

Plant allocation to defensive compounds by elevated CO2-grown nontransgenic and transgenic Bt cotton in response to infestation by cotton aphid, Aphis gossypii （Glover） in open-top chambers under elevated CO2 were studied. The results showed that significantly lower foliar nitrogen concentration and Bt toxin protein occurred in transgenic Bt cotton with and without cotton aphid infestation under elevated CO2. However, significantly higher carbon/nitrogen ratio, condensed tannin and gossypol were observed in transgenic Bt cotton ＂GK-12＂ and non-transgenic Bt cotton ＇Simian-3＇ under elevated CO2. The CO2 level and cotton variety significantly influenced the foliar nitrogen, condensed tannin and gossypol concentrations in the plant leaves after feeding by A. gossypii. The interaction between CO2 level x infestation time （24 h, 48 h and 72 h） showed a significant increase in cotton condensed tannin concentrations, while the interaction between CO2 level x cotton variety significantly decreased the true choline esterase （TChE） concentration in the body ofA. gossypi. This study exemplified the complexities of predicting how transgenic and non-transgenic plants will allocate defensive compounds in response to herbivorous insects under differing climatic conditions. Plant defensive compound allocation patterns and aphid enzyme changes observed in this study appear to be broadly applicable across a range of plant and herbivorous insect interactions as CO2 atmosphere rises.

Spectral response of spider mite infested cotton:Mite density and miticide rate study

Two-spotted spider mites are important pests in many agricultural systems.Spider mites(Acari:Tetranychidae)have been found to cause economic damage in corn,cotton,and sorghum.Adult glass vial bioassays indicate that Temprano™(abamectin)is the most toxic technical miticide for adult two-spotted spider mite.From an aerial application standpoint,additional research is needed to identify aerial application parameters for this miticide.The objective of this study was to investigate spectral response of spider mite-infested cotton plants with different density levels of mites and treated with different rates of miticide.Results showed significantly different spectral signatures of cotton plants infested with different density levels of mites.By treating mite-infested cotton plants with five different Temprano rate treatments(control,one-eighth,one-fourth,one-half,and full rates),spectral reflectance curves were found to be significantly different.Four wavelengths of 550 nm,560 nm,680 nm and 740 nm were important for detecting the spectral differences among mite infested cotton plants treated with various rate of Temprano.Normalized Difference Vegetative Index imagery was able to detect different levels of cotton plant damage.Half-rate application of Temprano controlled mite-infested plants as effectively as the full-rate application.These findings may lead to reduced cost and quantity of miticides used to maintain effective crop production and protection.

Assessing the performance of YOLOv5 algorithm for detecting volunteer cotton plants in corn fields at three different growth stages

The feral or volunteer cotton(VC)plants when reach the pinhead squaring phase(5–6 leaf stage)can act as hosts for the boll weevil(Anthonomus grandis L.)pests.The Texas Boll Weevil Eradication Program(TBWEP)employs people to locate and eliminate VC plants growing by the side of roads or fields with rotation crops but the ones growing in the middle of fields remain undetected.In this paper,we demonstrate the application of computer vision(CV)algorithm based on You Only Look Once version 5(YOLOv5)for detecting VC plants growing in the middle of corn fields at three different growth stages(V3,V6 and VT)using unmanned aircraft systems(UAS)remote sensing imagery.All the four variants of YOLOv5(s,m,l,and x)were used and their performances were compared based on classification accuracy,mean average precision(mAP)and F1-score.It was found that YOLOv5s could detect VC plants with maximum classification accuracy of 98%and mAP of 96.3%at V6 stage of corn while YOLOv5s and YOLOv5m resulted in the lowest classification accuracy of 85%and YOLOv5m and YOLOv5l had the least mAP of 86.5%at VT stage on images of size 416×416 pixels.The developed CV algorithm has the potential to effectively detect and locate VC plants growing in the middle of corn fields as well as expedite the management aspects of TBWEP.