TAN Yuping, WANG Zhiqiang, LIU Ruoxuan. Spatial distribution and influencing factors of soybean yield in a small watershed in the black soil region of Northeastern China[J]. Journal of Beijing Normal University(Natural Science), 2024, 60(4): 529-540. DOI: 10.12202/j.0476-0301.2024030
Citation: TAN Yuping, WANG Zhiqiang, LIU Ruoxuan. Spatial distribution and influencing factors of soybean yield in a small watershed in the black soil region of Northeastern China[J]. Journal of Beijing Normal University(Natural Science), 2024, 60(4): 529-540. DOI: 10.12202/j.0476-0301.2024030

Spatial distribution and influencing factors of soybean yield in a small watershed in the black soil region of Northeastern China

  • To study spatial distribution of crop yield and influencing factors in small watersheds in the black soil region of Northeast China is not only important to realize dynamic monitoring of soil productivity in the black soil region of Northeast China, but also to realize the evaluation of soil productivity in small watersheds and accurate land management. It is of great significance. In this study, in Heshan Farm, Nenjiang city was selected for a typical small watershed, a typical black soil area in Northeast China, and where 43 sampling points were set up in the cultivated land for yield measurement. Thickness of black soil layer, and physical and chemical properties of soil were determined. The spatial distribution characteristics and influencing factors of soybean growth and yield index in small watershed were analyzed. The results showed that: 1) The soybean yield in this small watershed was found to vary from 950.4 to 3782.4 kg·hm−2, averaging at 3014.5 kg·hm−2.2) High soybean yield area is distributed in low terrain and flat terrain, but low yield area correlated to high sand content. 3) Soybean yield significantly correlated with black soil thickness, mechanical composition, bulk density, total porosity, water constant, total nutrient and alkali-hydrolyzable nitrogen.4) A total of 4 principal components were extracted. The first principal component mainly reflected ammonium nitrogen, total nitrogen and bulk density. The second principal component was a comprehensive index composed of water constant. The third principal component comprehensively reflects the information of slope, total potassium and gravel ratio. In the fourth principal component, clay, total phosphorus and sand are the main evaluation indexes.
  • loading

Catalog

    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return
    Baidu
    map