Clarifying factors involved in historical soybean yield suppression in Japan using national statistics and a crop model

IF 8.2 1区 农林科学 Q1 AGRONOMY
Sohei Kobayashi, Yoji Kunimitsu, Satoshi Nakano
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Abstract

Soybean yields have remained below 2.0 t ha−1 for over 30 years in Asian countries; however, few studies have analyzed national statistical data in detail to explore the underlying factors. This is the first study to analyze precisely and comprehensively factors involved in the historical soybean yield suppression in Japan by using national production-cost and other statistics, coupled with a crop model. Panel data of 5–6 land-size sections for 1987–2018 were prepared to analyze the regression of actual yield against 13 production input-related variables, model-predicted potential yield, and agricultural social capital score by each data class for the whole country (i.e., Japan), two climatic regions (temperate and subarctic), and two field types (converted paddy and upland). Although potential yield rose by 8% for the studied 32 years at the country/national level, actual yield declined by 18%, and this was primarily attributed to trends in converted paddy fields in the temperate region. Panel regression analyses showed that for this field type and region, a total of 14–21% actual yield reduction occurred with decreased water management input, as well as increases in weed control failure and converted paddy fields, resulting in a 16% reduction at the country level. In contrast, the increased potential yield, mainly due to climatic changes (warming), contributed to improving actual yields by 7–8% in the region and country, thereby partially offsetting the above yield reduction. Against our expectation, no actual yield improvement was observed with increased agricultural social capital score, but rather a 19% reduction for the country. Implications of the results for policymakers and scientists aiming to improve country-level soybean yields in Japan were discussed, as well as the importance of potential yield as an explanatory variable and that of spatial error model for panel data of land-size sections.

利用国家统计数据和作物模型澄清日本历史大豆产量抑制的因素
30多年来,亚洲国家的大豆产量一直保持在2.0吨/公顷以下;然而,很少有研究对国家统计数据进行详细分析,以探讨其潜在因素。这是第一个利用国家生产成本等统计数据,结合作物模型,精确、全面地分析日本大豆历史减产因素的研究。准备了1987-2018年5-6个土地面积区段的面板数据,分析了全国(即日本)、两个气候区(温带和亚北极)和两种田型(转耕水田和旱地)的实际产量与13个生产投入相关变量、模型预测潜在产量和农业社会资本得分的回归。在研究的32年中,虽然潜在产量在国家/国家一级增加了8%,但实际产量下降了18%,这主要归因于温带地区转化稻田的趋势。面板回归分析显示,对于该类型和区域,随着水管理投入的减少,以及杂草控制失败和水田改造的增加,实际产量减少了14-21%,导致国家一级的产量减少了16%。相比之下,主要由于气候变化(变暖)而增加的潜在产量使该地区和国家的实际产量提高了7-8%,从而部分抵消了上述减产。与我们的预期相反,农业社会资本得分的增加并没有实际提高产量,反而使该国的产量下降了19%。研究结果对旨在提高日本国家级大豆产量的政策制定者和科学家的意义进行了讨论,并讨论了潜在产量作为解释变量的重要性,以及土地大小断面面板数据的空间误差模型的重要性。
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来源期刊
Agronomy for Sustainable Development
Agronomy for Sustainable Development 农林科学-农艺学
CiteScore
10.70
自引率
8.20%
发文量
108
审稿时长
3 months
期刊介绍: Agronomy for Sustainable Development (ASD) is a peer-reviewed scientific journal of international scope, dedicated to publishing original research articles, review articles, and meta-analyses aimed at improving sustainability in agricultural and food systems. The journal serves as a bridge between agronomy, cropping, and farming system research and various other disciplines including ecology, genetics, economics, and social sciences. ASD encourages studies in agroecology, participatory research, and interdisciplinary approaches, with a focus on systems thinking applied at different scales from field to global levels. Research articles published in ASD should present significant scientific advancements compared to existing knowledge, within an international context. Review articles should critically evaluate emerging topics, and opinion papers may also be submitted as reviews. Meta-analysis articles should provide clear contributions to resolving widely debated scientific questions.
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