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Effect of tree canopy management in agroforestry system on soil quality in central India

机译:树冠管理对印度中部土壤质量的农业剧系统

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The present study dealt with the effect of canopy management of Albizia procera (planted at 8 m x 4 m spacing) in a 10-years old agroforestry system on soil quality indicators. Study comprised of five treatments viz., control (pure crop i.e. wheat), pure tree (without intercropping), zero pruning + intercropping, 50% pruning + intercropping and 75% pruning + intercropping. Soil samples were taken from all treatment plots and analyzed for 15 physical, chemical and biological properties. The quality of the soil was assessed by using two approaches viz., linear score function (LSF) and principal component analysis (PCA). Based on nature of land-use and management goal, minimum data set was identified. Soil properties which play important role in soil quality and soil functions in hot semi-arid region of northern plains were identified. The indicator values were converted into unit-less scores (0 to 1), based on critical values; and these scores were integrated into a single soil quality index (SQI) with the help of PCA. Tree pruning significantly affected most of the soil quality indicators. Maximum SQI was observed from 50% pruning plot (0.489) and minimum from pure crop (0.356). The improvement in SQI over experimental control ranged from 17.42 to 37.36%. The PCA revealed that soil organic carbon, microbial biomass carbon, porosity, water holding capacity and bulk density of soil were important contributing indicators in soil quality. The SQls based on LSF and PCA were found highly correlated with biomass yield and had sensitivity of 1.38 and 2.00, respectively.
机译:本研究涉及在土壤质量指标的10岁的农业遗传学系统中,对阿尔比亚亚植物(Albizia Procera的冠层管理(种植在8米×4米间距)的影响。研究由五个治疗方法组成,控制(纯作物I.E.小麦),纯树(无间隙),零修剪+间作,50%修剪+间作和75%修剪+间作。从所有治疗图中取出土壤样品,并分析15个物理,化学和生物学性质。通过使用两个方法Viz来评估土壤的质量,线性得分函数(LSF)和主成分分析(PCA)。基于土地利用和管理目标的性质,确定了最低数据集。鉴定了北平原热半干旱地区土壤质量和土壤功能重要作用的土壤性质。基于临界值,将指示值转换为单位分数(0至1);在PCA的帮助下,这些分数被整合到单一土壤质量指数(SQI)中。树修剪显着影响了大部分土壤质量指标。从50%的修剪图(0.489)和纯作物最小值(0.356),观察到最大SQI。通过实验控制的SQI改善从17.42%到37.36%。 PCA显示土壤有机碳,微生物碳,孔隙率,水持续容量和散装土壤密度是土壤质量的重要贡献指标。发现基于LSF和PCA的SQLS与生物质产量高度相关,分别具有1.38和2.00的灵敏度。

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