Revisiting yield gaps and the scope for sustainable intensification for irrigated lowland rice in Southeast Asia,Agricultural Systems

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Revisiting yield gaps and the scope for sustainable intensification for irrigated lowland rice in Southeast Asia
Agricultural Systems ( IF 6.1 ) Pub Date : 2022-02-19 , DOI: 10.1016/j.agsy.2022.103383
João Vasco Silva _{1,

2} , Valerien O. Pede ₃ , Ando M. Radanielson _{3,

4} , Wataru Kodama ₃ , Ary Duarte _{3,

5} , Annalyn H. de Guia ₃ , Arelene Julia B. Malabayabas ₃ , Arlyna Budi Pustika ₆ , Nuning Argosubekti ₆ , Duangporn Vithoonjit ₇ , Pham Thi Minh Hieu ₈ , Anny Ruth P. Pame ₃ , Grant R. Singleton ₃ , Alexander M. Stuart ₃

Affiliation

CONTEXT

Recent studies on yield gap analysis for rice in Southeast Asia revealed different levels of intensification across the main ‘rice bowls’ in the region. Identifying the key crop management and biophysical drivers of rice yield gaps across different ‘rice bowls’ provides opportunities for comparative analyses, which are crucial to better understand the scope to narrow yield gaps and increase resource-use efficiencies across the region.

OBJECTIVE

The objective of this study was to decompose rice yield gaps into their efficiency, resource, and technology components and to map the scope to sustainably increase rice production across four lowland irrigated rice areas in Southeast Asia through improved crop management.

METHODS

A novel framework for yield gap decomposition accounting for the main genotype, management, and environmental factors explaining crop yield in intensive rice irrigated systems was developed. A combination of crop simulation modelling at field-level and stochastic frontier analysis was applied to household survey data to identify the drivers of yield variability and to disentangle efficiency, resource, and technology yield gaps, including decomposing the latter into its sowing date and genotype components.

RESULTS AND CONCLUSION

The yield gap was greatest in Bago, Myanmar (75% of Yp), intermediate in Yogyakarta, Indonesia (57% of Yp) and in Nakhon Sawan, Thailand (47% of Yp), and lowest in Can Tho, Vietnam (44% of Yp). The yield gap in Myanmar was largely attributed to the resource yield gap, reflecting a large scope to sustainably intensify rice production through increases in fertilizer use and proper weed control (i.e., more output with more inputs). In Vietnam, the yield gap was mostly attributed to the technology yield gap and to resource and efficiency yield gaps in the dry season and wet season, respectively. Yet, sustainability aspects associated with inefficient use of fertilizer and low profitability from high input levels should also be considered alongside precision agriculture technologies for site-specific management (i.e., more output with the same or less inputs). The same is true in Thailand, where the yield gap was equally explained by the technology, resource, and efficiency yield gaps. The yield gap in Indonesia was mostly attributed to efficiency and technology yield gaps and yield response curves to N based on farmer field data in this site suggest it is possible to reduce its use while increasing rice yield (i.e., more output with less inputs).

SIGNIFICANCE

This study provides a novel approach to decomposing rice yield gaps in Southeast Asia's main rice producing areas. By breaking down the yield gap into different components, context-specific opportunities to narrow yield gaps were identified to target sustainable intensification of rice production in the region.

中文翻译：

重新审视东南亚灌溉低地水稻的产量差距和可持续集约化的范围

语境

最近对东南亚水稻产量差距分析的研究表明，该地区主要“饭碗”的集约化程度不同。确定不同“饭碗”之间水稻产量差距的关键作物管理和生物物理驱动因素为比较分析提供了机会，这对于更好地了解缩小产量差距和提高整个地区资源利用效率的范围至关重要。

客观的

本研究的目的是将水稻产量差距分解为效率、资源和技术组成部分，并绘制出通过改进作物管理在东南亚四个低地灌溉水稻区可持续增加水稻产量的范围。

方法

开发了一种用于解释集约化水稻灌溉系统中作物产量的主要基因型、管理和环境因素的产量差距分解新框架。将田间作物模拟模型和随机前沿分析相结合，应用于家庭调查数据，以确定产量变化的驱动因素，并解开效率、资源和技术的产量差距，包括将后者分解为其播种日期和基因型组成部分.

结果与结论

单产差距最大的是缅甸勃固（75% Yp），中间是印度尼西亚日惹（57% Yp）和泰国那空沙旺（47% Yp），最低的是越南芹苴（44%） Yp)。缅甸的单产差距主要归因于资源单产差距，这反映了通过增加化肥使用和适当控制杂草（即更多投入产出更多产出）可持续集约化水稻生产的巨大空间）。在越南，产量差距主要归因于技术产量差距以及旱季和雨季的资源和效率产量差距。然而，与肥料使用效率低下和高投入水平的低利润率相关的可持续性方面也应与针对特定地点管理的精准农业技术一起考虑（即，以相同或更少的投入获得更多产出）。泰国的情况也是如此，技术、资源和效率的产量差距同样可以解释产量差距。印度尼西亚的产量差距主要归因于效率和技术产量差距以及基于该站点农民田间数据的 N 产量响应曲线表明，在增加水稻产量的同时减少其使用是可能的（即，以更少的投入获得更多的产出）。