Chen Hungyen, Yamagishi Junko, Kishino Hirohisa
Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.
Institute for Sustainable Agro-ecosystem Services, The University of Tokyo, Tokyo, Japan.
PLoS One. 2014 Nov 18;9(11):e112785. doi: 10.1371/journal.pone.0112785. eCollection 2014.
To effectively manage soil fertility, knowledge is needed of how a crop uses nutrients from fertilizer applied to the soil. Soil quality is a combination of biological, chemical and physical properties and is hard to assess directly because of collective and multiple functional effects. In this paper, we focus on the application of these concepts to agriculture. We define the baseline fertility of soil as the level of fertility that a crop can acquire for growth from the soil. With this strict definition, we propose a new crop yield-fertility model that enables quantification of the process of improving baseline fertility and the effects of treatments solely from the time series of crop yields. The model was modified from Michaelis-Menten kinetics and measured the additional effects of the treatments given the baseline fertility. Using more than 30 years of experimental data, we used the Bayesian framework to estimate the improvements in baseline fertility and the effects of fertilizer and farmyard manure (FYM) on maize (Zea mays), barley (Hordeum vulgare), and soybean (Glycine max) yields. Fertilizer contributed the most to the barley yield and FYM contributed the most to the soybean yield among the three crops. The baseline fertility of the subsurface soil was very low for maize and barley prior to fertilization. In contrast, the baseline fertility in this soil approximated half-saturated fertility for the soybean crop. The long-term soil fertility was increased by adding FYM, but the effect of FYM addition was reduced by the addition of fertilizer. Our results provide evidence that long-term soil fertility under continuous farming was maintained, or increased, by the application of natural nutrients compared with the application of synthetic fertilizer.
为了有效管理土壤肥力，需要了解作物如何利用施用于土壤的肥料中的养分。土壤质量是生物、化学和物理性质的综合体现，由于其具有综合和多重功能效应，很难直接评估。在本文中，我们重点关注这些概念在农业中的应用。我们将土壤的基线肥力定义为作物从土壤中获取生长所需的肥力水平。基于这一严格定义，我们提出了一种新的作物产量-肥力模型，该模型能够仅从作物产量的时间序列中量化提高基线肥力的过程以及处理措施的效果。该模型是从米氏动力学修改而来的，用于测量在给定基线肥力的情况下处理措施的额外效果。利用30多年的实验数据，我们使用贝叶斯框架来估计基线肥力的提高以及肥料和农家肥（FYM）对玉米（Zea mays）、大麦（Hordeum vulgare）和大豆（Glycine max）产量的影响。在这三种作物中，肥料对大麦产量的贡献最大，农家肥对大豆产量的贡献最大。施肥前，玉米和大麦的表层土壤基线肥力非常低。相比之下，这种土壤中大豆作物的基线肥力接近半饱和肥力。添加农家肥提高了长期土壤肥力，但添加肥料降低了农家肥的效果。我们的结果提供了证据，表明与施用合成肥料相比，通过施用天然养分可以维持或提高连续耕作下的长期土壤肥力。
