东北粮食主产区县域耕地产能核算及其影响因子分析

为科学确定粮食主产区耕地产能大小，阐明各种因子对产能影响的作用强度及方向，该文以东北粮食主产区典型粮食大县巴彦县为研究区，采用潜力衰减法核算耕地产能大小，揭示其空间分异特征，运用遗传算法对神经网络模型进行修正和改进的因子降维法、通径分析和回归分析法，分析主要因子单一作用和因子间协同作用对耕地产能影响的作用强度及方向。结果表明：1）以玉米为基准作物，2009年研究区耕地理论单产、可实现单产和实际单产分别为2.33、1.58和1.08 kg/m2；理论产能、可实现产能和实际产能分别为547、372和254万t；理论利用潜力和可实现利用潜力分别为0.74和0.50 kg/m2；理论利用强度和可实现利用强度均为0.68；在空间分布上耕地理论单产、可实现单产及实际单产呈现出由西南向东北逐渐降低的分布特征，理论产能、可实现产能及实际产能呈现出由西北向东南逐渐降低的分布特征。2）差值植被指数、地貌类型、坡度、黑土层厚度、有机质、机械化程度、灌溉潜力7个主要因子的单一作用对耕地产能影响很大，其中机械化程度作用强度最大，黑土层厚度最小，除坡度对耕地产能有负向作用外，其他6个因子对研究区耕地产能有正向作用；主要因子间协同作用对研究区耕地产能的影响较大，其他主要因子与地貌类型的协同作用对耕地产能影响强度最大，方向为正；其他因子与主要因子形成的5组相关因子间协同作用对研究区耕地产能的影响同样也不容忽视，化肥施用量等因子与机械化程度协同作用对耕地产能的影响强度最大，方向为正。研究表明，主要因子的单一作用和因子间协同作用对研究区耕地产能具有重要影响。

Calculation of county cultivated land productivity and its analysis of influential factors of grain main production area in Northeast China

Abstract: The northeastern area is the production area of commercial grain, playing an important role in protecting national food security. To determine the size of cultivated land productivity and to clarify effect intensity and direction of various factors to the cultivated land productivity, the northeastern grain main production area Bayan county is used as the study area, digital topographic map and SPOT5 images from 2009 are used as the basic information source, and land detailed survey database and other statistics are used as the basic data source to analyze in the study. Based on the mechanism of formation of grain production capacity, synthesizing natural ecology, and socio-economic factors affecting cultivated land productivity, potential attenuation method is used to calculate cultivated land production capacity and analyze its spatial distribution pattern in the study area. While improved dimensionality reduction that backs propagation neural network is improved by genetic algorithm, path analysis and regression analysis methods are adopted to analyze single effects of each major factor and synergistic effects among factors to effect intensity and direction of cultivated land production capacity was also studied, which breaking the Agricultural Land Classification accounting methods, focused on natural factors in the past. The results show that: 1) taking the corn crop as the basis in 2009, its theoretical, achievable, and actual cultivated land productivity per unit area in study area are respectively 2.33 kg/m2, 1.58 kg/m2, and 1.08 kg/m2; the theoretical, achievable, and actual total cultivated land productivity are respectively 5.47, 3.72, and 2.54 million tons. In addition, theoretical usage potentiality is 0.74 kg/m2, and achievable usage potentiality is 0.50 kg/m2, while theoretical usage intensity and achievable usage intensity both are 0.68. As for the spatial distribution of cultivated land productivity, the theoretical, achievable, and actual cultivated land productivity per unit area show the decreasing trend from the southwest to northeast, and the total theoretical, achievable, and actual cultivated land productivity show the decreasing distribution trend from northwest to southeast. 2) The single effects of 7 main factors including difference vegetation index (DVI), slope, geomorphic type, black soil thickness, organic matter, mechanization degree, and irrigation potential are great; the strongest action intensity to productivity is mechanization degree, and the weakest is black soil thickness. Except for the slope that has a negative effect, the other six factors have a positive effect to cultivated land productivity in the study area. The synergistic effects intensity among the 7 main factors to cultivated land productivity are strong, and the synergistic effect intensity between the other 6 main factors and geomorphological type is the strongest, while the synergistic effect intensity between the other 6 main factors and organic matter is the weakest. Besides, only the synergy action intensity between the main influential factors and slope to cultivated land productivity is negative and synergistic effects among the other 6 main factors all are positive. Meanwhile, according to the total 25 influential factors of cultivated land productivity, synergistic effects of 5-group-relative factors formed from the 7 main factors and the rest of the 18 influential factors (non-main factors) also play a significant part in the cultivated land productivity. Synergistic effects intensity between chemical fertilizer application and mechanization degree is the strongest, which is positive, while synergistic effects intensity between elevation and slope is the weakest and is negative. The effect mechanisms of influential factors show that single effects of main factors and synergistic effects of factors play an important role in the cultivated land productivity.