Accumulation of Na+ in cotton field under mulched drip irrigation of brackish water in arid areas

Abstract

In arid areas, the disordered accumulation of Na+ in cotton fields under mulched drip irrigation seriously affects the normal growth and development of cotton. To reveal the process and mechanism of Na+ accumulation, in-situ field tests were conducted in typical cotton planting bases in the south of Xinjiang, China. Eight experimental scenarios were set up to use brackish and fresh water for drip irrigation under mulch during the whole growth period of cotton according to the drip irrigation system. By monitoring the weather, groundwater level, and soil moisture before and after irrigation, and testing the soil salinity and Na+ concentration, the temporal and spatial distribution and transport characteristics of Na+ were compared and studied. The results showed that: (1) owing to the strong spatial variation of soil permeability, soil water and salt dynamics exhibited significant differences after irrigation in all experimental scenarios in the study area, especially at a depth of 0–60 cm. (2) The Na+ profile exhibited a “thin waist”, whose depth depended on the climate and lithology of the soil; however, this phenomenon was not observed in the salt profile. (3) The accumulation of Na+ in cotton fields is an extremely complex dynamic process that is influenced by both natural and human activities. This process is controlled by the dynamic characteristics of soil water and salt, but it is different from the distribution of soil salt in time and space. This study provides necessary technical support for the formulation of drip irrigation systems under brackish water film, and provides a scientific basis for fine agricultural planting and water resources management in arid areas.

A cotton leaf nitrogen monitoring model based on spectral-fluorescence data fusion

“…In this study, the fluorescence parameters Fv/Fm, Fv'/Fm', Fv/F0 and Yield of L3 cotton leaves showed decreasing trends with the growth period, consistent with the results of existing studies Li et al, 2020;Ding et al, 2020). Under different levels of nitrogen application, the fluorescence parameters Fv/Fm, Fv'/Fm', and Fv/F0 were greater in the high nitrogen application groups (N3, N4) and lesser in the low nitrogen application groups.…”

“…Among these, SVR-GRA in the budding period had the best performance. However, the accuracy for the flowering period and full boll period was lower than the canopy spectral models employed in previous studies (Wen et al, 2016;Ma et al, 2020), a result that may be due to differences in the data collection environment. The human and meteorological factors were more complicated in this study, and these may have affected the model accuracy.…”

“…Due to redundancy, how to extract characteristic spectral bands has always been a key research topic in crop remote sensing monitoring (Blackburn, 1998;Hansen et al, 2003;Zhu et al, 2007). In conventional multispectral data, researchers usually perform regression on individual bands one by one in order to obtain characteristic bands that are sensitive to crop physiological and biochemical characteristics (Niu et al, 2000;Ma et al, 2020). However, for hyperspectral information, it is necessary to use algorithms to effectively and accurately extract characteristic information that is highly correlated with the target.…”