影响板蓝根生物燃料作物谷物产量和含油量的土壤化学性质

Araceli Ciotti de Marins, Deonir Secco, Guilherme Gabriel Ruffato, Doglas Bassegio, Gizachew Ayalew Tiruneh, José Miguel Reichert
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引用次数: 0

摘要

巴西莓(Crambe abyssinica Hochst)是生产生物柴油的重要粮食作物。本研究的目的是评估土壤特性的空间分布如何影响木豆的产量和含油量。我们分析了六种不同的取样密度,取样点之间的距离从 5.5 米到 44 米不等,以确定土壤和作物变量之间的相关性以及最佳空间分布。板蓝根含油量与任何理化性质都不相关,而板蓝根谷物产量则与总孔隙度、可交换的铝和钙、有效阳离子交换容量、可利用的磷、钾、铜和锌以及铝和碱饱和度相关,其中磷和钾以及铜和锌的相关性非常显著(p < 0.001)。大多数土壤特性的空间依赖程度由弱到强,并以球形或指数半变量图建模。空间数据显示,谷物产量低与种子含油量高有关,而在第一年(2012 年),板蓝根谷物产量与土壤中磷的可用性更相关,在第二年(2013 年),则与钙、镁和土壤有机质更相关。土壤养分的空间变化归因于肥料分布不均和地表径流。结果表明,必须提高采样密度,才能绘制出更精确的影响板蓝根的土壤化学性质图。建议在 625 平方米的土地上使用 25 个点的网格,这样谷物产量估算的准确率超过 60%,大多数化学特性估算的准确率超过 40%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soil chemical properties affecting grain yield and oil content of crambe biofuel crop

Crambe (Crambe abyssinica Hochst) is an important grain crop for biodiesel production. The objective of this study was to evaluate how spatial distribution of soil properties affects crambe grain yield and oil content. We analyzed six different sampling densities, with a distance between sampling points ranging from 5.5 to 44 m, to identify correlations among soil and crop variables, and the best spatial distribution. Crambe oil content was not correlated to any of the physicochemical properties, whereas crambe grain yield was correlated with total porosity and exchangeable Al and Ca, effective cation exchange capacity, available P, K, Cu, and Zn, and aluminum and base saturation, with highly significant correlation (p < 0.001) for P and K and Cu and Zn. Most soil properties had spatial dependence degrees from weak to strong, and were modeled by spherical or exponential semi-variograms. Spatial data showed that low grain yield is associated with high seed oil content, while crambe grain yield was more correlated with phosphorous availability in soil in the first year (2012) and with Ca, Mg, and soil organic matter in the second year (2013). Spatial variability in soil nutrients is attributed to uneven distribution of fertilizers and surface runoff. The results demonstrate sampling density must be increased to generate more accurate maps for soil chemical properties affecting crambe. The use of a grid of 25 points in a 625 m2 of land is suggested, providing more than 60% accuracy for grain yield estimation and more than 40% for most chemical properties’ estimation.

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