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[学术文献 ] MYB regulation of GST/GT mediates red petal spot development in cotton 进入全文
CROP JOURNAL
Red petal spots are beneficial for attracting cotton pollinators and producing hybrid seeds, and the anthocyanin pathway is generally regarded as a metabolic cause of petal coloration. The current study identified an MYB-encoding gene (Gar07G09390, GaMYB) as a candidate gene involved in cotton coloration by map-based cloning, and this MYB could positively regulate a candidate glutathione S transferase gene (Gar07G08900, GaGST). To unveil potentially involved genes within the GaMYB-regulating-GaGST route, color metabolites of both GaMYB- and GaGST-virus-induced gene silencing (VIGS) petals were investigated, revealing that they were largely glycosyl-decorated flavonoids. Accordingly, a transcriptomic survey of both VIGS petals identified a glycosyl-transferase gene (GaGT, Gar02G15390). Notably, this GaGT is adjacent to one of the genome-wide association study loci concerning petal spots in Gossypium arboreum, and it is also positively regulated by GaMYB. This new regulatory route including both GST and GT regulated by MYB is conserved among the three cotton species examined in this study (Gossypium arboreum, Gossypium hirsutum, and Gossypium barbadense). Accordingly, comprehensively evaluating the influence of these candidates and their homologs on cotton coloration may provide a more in-depth understanding of cotton coloration, ultimately facilitating the breeding of more colorful cotton.
[前沿资讯 ] How will the “water footprint” of Xinjiang cotton change under climate change? 进入全文
EurekAlert!
According to the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), human activities have significantly intensified global warming, leading to more frequent, intense, and prolonged extreme weather events, which pose a major threat to agricultural production. Xinjiang, as one of the driest regions in China, has an average annual precipitation of less than 270 mm and an evaporation rate exceeding 1000 mm, yet it produces 25% of the world’s cotton, contributing 91.0% of the national cotton production and 35% of farmers’ income. Cotton cultivation in this region heavily relies on irrigation, and climate change is likely to exacerbate aridity in Xinjiang. In this context, how will the water use structure of cotton production in Xinjiang change? How can the water-saving potential of different irrigation technologies be assessed? A study conducted by Dr. La Zhuo and colleagues from the Institute of Soil and Water Conservation at Northwest A&F University, published in Frontiers of Agricultural Science and Engineering, provides the answers to these questions (DOI: 10.15302/J-FASE-2024585). This study focuses on the “water footprint” of cotton production in Xinjiang—specifically, the amount of freshwater consumed to produce one ton of cotton, divided into “blue water footprint” (relying on groundwater or surface water) and “green water footprint” (relying on precipitation). Unlike previous studies that primarily focused on food crops or single irrigation methods, this research innovatively simulates three mainstream irrigation technologies—furrow irrigation, micro-irrigation (drip irrigation), and sprinkler irrigation—at a fine grid scale of 5 arcminutes (approximately 9 km × 9 km), analyzing the spatiotemporal changes in cotton’s water footprint under two climate change scenarios for the 2050s and 2090s (SSP2-4.5 moderate emissions and SSP5-8.5 high emissions). The study first reveals the future climate trends in Xinjiang: compared to the baseline period of 2000–2018 (with a reference crop evapotranspiration ET0 of 1080 mm), evaporation demand in Xinjiang significantly increases under both scenarios. In the SSP5-8.5 scenario of the 2090s, ET0 increases by 14.3% annually, with the largest increases occurring in January and November, while the summer increase is only about 8%. Annual precipitation decreases by 15.1% overall, with only July to September slightly exceeding the baseline period. This indicates that Xinjiang will become increasingly arid in the future, and the pressure on agricultural water use may further intensify. However, a key finding is that the total water footprint of cotton shows a downward trend. The total water footprint for cotton in Xinjiang during the baseline period is 4264 m3·t-1, of which blue water accounts for 83% (3560 m3·t-1). By the 2090s, the total water footprint is expected to decrease by 19.3% under the SSP2-4.5 scenario, and by 35.7% under the SSP5-8.5 high emissions scenario. This is mainly attributed to the effects of increased atmospheric CO2 concentration—under the SSP5-8.5 scenario, CO2 concentration is significantly higher than under SSP2-4.5, and higher CO2 levels can enhance the photosynthetic efficiency of cotton while reducing transpiration water loss. It is noteworthy that the structure of the water footprint is changing: the proportion of blue water in the total water footprint is expected to increase slightly. Although the total amount of blue water is also decreasing—by 16.5% and 33.4% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively—the contribution of green water declines due to reduced precipitation, leading to an increased proportion of blue water. The decline in green water footprint is more pronounced, decreasing by 33.7% and 47.2% under the SSP2-4.5 and SSP5-8.5 scenarios, with only a few areas experiencing slight increases due to minor precipitation increases. There are significant differences in the water-saving potential of the three irrigation technologies: sprinkler irrigation shows a reduction in water footprint of 24.8% and 40.1% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively, demonstrating the most notable water-saving effects; furrow and micro-irrigation show relatively smaller reductions. This indicates that sprinkler irrigation technology has higher water-saving potential for future cotton cultivation in Xinjiang. The cotton industry in Xinjiang is crucial for the regional economy, but water resource scarcity is a long-term challenge. This study not only quantifies the dynamic patterns of cotton water consumption under climate change but also clarifies the adaptive differences among various irrigation technologies, providing scientific support for optimizing water resource allocation and promoting water-saving measures. In the future, combined with variety improvement and agronomic upgrades, Xinjiang cotton is expected to achieve more efficient water resource utilization in an increasingly arid environment.
[前沿资讯 ] Cotton virus circulated undetected for nearly 20 years, study finds：Discovery reshapes understanding of disease emergence and highlights new opportunities for virus surveillance in U.S. agriculture 进入全文
EurekAlert!
A virus responsible for damaging cotton crops across the southern United States has been lurking in U.S. fields for nearly 20 years – undetected. According to new research, cotton leafroll dwarf virus (CLRDV), long believed to be a recent arrival, was infecting plants in cotton-growing states as early as 2006. The findings, published in Plant Disease by USDA Agricultural Research Service researchers and cooperators at Cornell University, challenge long-standing assumptions about when and how the virus emerged in U.S. cotton. They also demonstrate how modern data-mining tools can uncover hidden threats in samples collected well before the virus was on anyone’s radar. “CLRDV was officially detected in 2017, so the assumption was that it had only recently entered the U.S.,” said Alejandro Olmedo-Velarde, formerly a Cornell postdoctoral associate and now Assistant Professor in the Department of Plant Pathology, Entomology, and Microbiology at Iowa State. “Our study shows that this virus was actually present in the country’s Cotton Belt long before that. We found clear evidence of the virus in samples from 2006 in Mississippi, 2015 in Louisiana, and 2018 in California.” To confirm the findings, the team conducted field surveys in 2023, collecting fresh cotton samples in Southern California. Lab testing confirmed that CLRDV is currently present in California—marking the state’s first official report of the virus. The team’s approach relied heavily on reanalyzing existing data in public genetic databases. By mining these datasets, the researchers uncovered viral sequences that closely matched current U.S. strains, offering a more complete picture of CLRDV’s spread over time and geography. The study underscores the importance of maintaining easily accessible, publicly available databases for improving future disease surveillance and preparedness. In an unexpected twist, the researchers also identified traces of the virus in an unusual location: a sample from the gut of a cow studied by researchers in California. Their data are consistent with the hypothesis that the cow ingested CLRDV-infected plant-based animal feed. While this does not suggest that animals are infected, it adds a new dimension to understanding the timeline and extent of CLRDV infection in the U.S. prior to the official first report. The study also reignites interest in an unresolved issue in cotton pathology: bronze wilt. The researchers propose a potential connection between CLRDV and bronze wilt symptoms, a topic that has sparked debate in the past. “Now, as more studies align with our findings, the idea is gaining traction,” said Olmedo-Velarde. “It could help explain long-standing crop losses and inform virus monitoring strategies moving forward.” Agricultural Research Service Scientist Dr. Michelle Heck explains, “For growers, the findings offer both a caution and a call to action. CLRDV has been in U.S. fields far longer than anyone realized, and it may be more widespread than current reports suggest. Understanding how and why the virus remained under the radar for so long – and why it’s becoming more of a problem now – will be critical for developing effective management strategies.” The research highlights the growing role of bioinformatics, plant pathology, and cross-disciplinary collaboration in modern agriculture – and shows that existing data may already contain the clues we need to detect emerging threats earlier.
[学术文献 ] Exploring the Dual Effects of Jasmonic Acid on Cotton Plants and Management of Aphis gossypii Infestations 进入全文
RUSSIAN JOURNAL OF PLANT PHYSIOLOGY
Cotton serves as the primary source of renewable fiber worldwide, primarily utilized in textile manufacturing. However, the cotton aphid, Aphis gossypii Glover, represents a significant risk to cotton cultivation. This study investigated the jasmonic acid (JA) effects at 0.25 mg/L on promoting cotton plant growth, enhancing productivity, and mitigating aphid populations. The findings indicated that JA treatment positively impacted important growth parameters i.e. plant height, leaf area, fruiting branches number/plant, plant dry weight and chlorophyll pigments (Chl a, b, total) content, antioxidant enzymes activity (CAT and POD) and polyphenoloxidase (PPO) as well as leaf total phenols content. Moreover, JA led to increased seed cotton yield, average boll weight, lint%, and improved fiber quality i.e. fiber length, strength, micronaire value. Both JA (0.25 mg/L) and acetamiprid (at 0.25 g/L) significantly lowered aphid populations. Ten days after application, acetamiprid resulted in the most significant reductions in aphid populations, with a 99.73% decrease in 2021 and a 99.34% decrease in 2022. Jasmonic acid also contributed to reductions of 81.28 and 76.56% in aphid populations ten days after treatment in the 2021 and 2022 seasons. Therefore, JA can be effectively used at a concentration of 0.25 mg to promote cotton growth and yield while reducing aphid population density in an eco-friendly manner.
[学术文献 ] Effect of cumin intercropping density on cotton growth and system economic benefits under subsurface drip irrigation 进入全文
JOURNAL OF COTTON RESEARCH
BackgroundThe mulch-free subsurface drip irrigation system demonstrated water-saving potential as an alternative to traditional mulch-based drip irrigation while also eliminating residual film pollution at source. However, delayed sowing is unavoidable in mulch-free cultivation in ecological regions with a short frost-free period. Intercropping with cumin, which has a shorter growth period, served as an effective strategy to improve land use efficiency during the early growth stages of cotton. Therefore, a two-year field experiment was conducted to study the effects of intercropping cumin at the seeding rate of 2.5 (ID1), 3.85 (ID2), and 5.2 (ID3) kg<middle dot>hm-2 on cotton growth, interspecies competition, fiber quality, and water use efficiency (WUE), as well as system economic benefits under subsurface drip irrigation. Monocropping cotton was used as the control (CK) treatment.ResultsAt the initial flowering (IF) stage (the end of the co-growth period of cotton and cumin), cotton plant height in ID2 and ID3 treatments decreased by 5.93%-16.53% and 10.87%-31.11%, respectively, cotton stem diameter by 11.41%-14.25% and 3.37%-26.49%, respectively, and vegetative biomass by 14.46%-30.65% and 22.59%-49.91%, respectively, compared with CK treatment. With the increase in cumin density, the crop growth rate (CGR) and compensation effect in cotton tended to significantly decrease at the IF stage regardless of organs considered. For the non-co-growth period (after harvesting cumin), cotton reproductive organ biomass in ID2 and ID3 treatments increased by 4.09%-14.61% at the boll opening stage, crop growth rate in reproductive organs by 20.74% and 74.26% from peak boll to boll opening stages compared with CK treatment, due to an enhancement of 19.09% and 49.30% in the compensation effect. Compared with ID1, the aggressivity treated by ID2 and ID3 decreased by 12.82%-46.34% and 17.95%-31.71%, respectively. However, owing to a greater number of green bolls in the upper canopy at the harvest stages in the ID3 treatment, the system production value (closely related to yield) treated by ID2 was 11.69%-16.89%, 6.56%-20.02%, and 16.48%-59.83% greater than that of the ID1, ID3, and CK treatments, respectively. This also led to the highest WUE and net profit under the ID2 treatment.ConclusionIntercropping cumin with medium density improved the cotton biomass accumulation characteristics and increased resources such as land and water utilization efficiency and economic benefits through a stronger compensation effect after harvesting cumin under subsurface drip irrigation without mulch. This study not only provides alternatives to residual film pollution in arid cotton fields but also establishes a sustainable agro-ecological-economic planting paradigm by reducing plastic use and enhancing water and fertilizer use efficiency, holding significant implications for advancing resource-efficient agricultural systems.
[学术文献 ] Heatmap clustering and performance analysis of cotton genotypes in response to environmental conditions 进入全文
SCIENTIFIC REPORTS
Cotton (Gossypium hirsutum) is a crucial cash crop in China, with yield performance influenced by genotype, environmental conditions, and management practices. The aim of this study was to assess the yield performance, biomass accumulation, and growth of nine cotton genotypes in Henan Province during three growing seasons (2017-2019) with different climates. Field experiments were conducted using a randomized complete block design (RCBD) at the Institute of Cotton Research, Chinese Academy of Agricultural Sciences (CAAS), Anyang, China. Plant height, true leaf number, and boll number per plant were among the morphological characteristics that showed the most variance across years and genotypes. Reproductive biomass, leaf area index (LAI), and biomass accumulation followed distinct seasonal trends, with LAI rising during boll formation and flowering. Yield parameters such as seed cotton yield, lint percentage, and boll weight vary by genotype and year, with the highest yields recorded in 2019. According to correlation study, temperature and precipitation had a negative impact on seed cotton production and final biomass, whereas climatic parameters had a favorable correlation with the harvest index. The genotypes were divided into distinct categories according to growth and yield characteristics using heatmap clustering. These findings provide insight into the best cotton genotypes for increased productivity and resilience in a variety of climates, allowing breeders and farmers to make more informed cultivar selections.
