ArticleFrontiers in plant science2024
Quantitative relationship model between soil profile salinity and soil depth in cotton fields based on data assimilation algorithm: forecasting cotton field yields and profits.
Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Soil salinization seriously affects the efficiency of crops in absorbing soil nutrients, and the cotton production in southern Xinjiang accounts for more than 60% of China's total. Therefore, it is crucial to monitor the dynamic changes in the salinity of the soil profile in cotton fields in southern Xinjiang, understand the status of soil salinization, and implement effective prevention and control measures. The drip-irrigated cotton fields in Alaer Reclamation Area were taken as the research objects. The multivariate linear regression model was used to study the relationship between soil salinity and soil depth in different periods, and the Kalman filter algorithm was used to improve the model accuracy. The results showed that the month with the highest improvement in model accuracy was July, with the model accuracy R
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