This study is part of a coordinated research program conducted on the same experimental plots, investigating the effects of nitrogen fertilization on cotton under varying salinity levels. Parallel studies focus on growth parameters, physiological traits, biomass accumulation, yield components, providing a comprehensive assessment of crop responses to nutrient management in saline environments. This study presents a large-scale field investigation of the interaction between soil salinity and precision nitrogen fertilization on key yield components of cotton (Gossypium hirsutum L.). Within the framework of precision agriculture and specific crop management, the study evaluates nutrient optimization under abiotic stress to improve reproductive development and resource use efficiency. Field experiments were conducted on irrigated meadow-alluvial soils classified into four salinity levels based on electrical conductivity. A randomized complete block design with nitrogen application rates ranging from 0 to 350 kg/ha allowed for detailed biometric assessment. Yield-related traits, including sympodial branches, buds, flowers, and bolls, were measured at three phenological stages. Analysis of variance results showed that increasing salinity significantly reduced all yield components, while precise nitrogen application mitigated these effects. The optimal nitrogen application rate was 250 kg/ha, maximizing yield components under non-saline conditions and maintaining productivity under high salinity. These results highlight the importance of data-driven variable-rate fertilizer application for increasing cotton yields in saline soils and contribute to decision support systems for sustainable production on marginal lands. The outcomes have practical implications for developing efficient fertilizer strategies and improving crop tolerance to salinity stress, particularly in arid and semi-arid zones.
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Sanjar Khozhiev
Barno Davronov
Feruza Xamidova
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Khozhiev et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69df2b49e4eeef8a2a6b04ab — DOI: https://doi.org/10.1051/bioconf/202623100018/pdf