Chivenge P, Zingore S, Ezui K S, Njoroge S, Bunquin M A, Dobermann A, Saito K
African Plant Nutrition Institute, UM6P Experimental Farm, Benguérir 41350, Morocco.
African Plant Nutrition Institute, ICIPE Campus, Duduville - Kasarani, Thika Road, Nairobi, Kenya.
Field Crops Res. 2022 May 15;281:108503. doi: 10.1016/j.fcr.2022.108503.
Increasing fertilizer access and use is an essential component for improving crop production and food security in sub-Saharan Africa (SSA). However, given the heterogeneous nature of smallholder farms, fertilizer application needs to be tailored to specific farming conditions to increase yield, profitability, and nutrient use efficiency. The site-specific nutrient management (SSNM) approach initially developed in the 1990 s for generating field-specific fertilizer recommendations for rice in Asia, has also been introduced to rice, maize and cassava cropping systems in SSA. The SSNM approach has been shown to increase yield, profitability, and nutrient use efficiency. Yield gains of rice and maize with SSNM in SSA were on average 24% and 69% when compared to the farmer practice, respectively, or 11% and 4% when compared to local blanket fertilizer recommendations. However, there is need for more extensive field evaluation to quantify the broader benefits of the SSNM approach in diverse farming systems and environments. Especially for rice, the SSNM approach should be expanded to rainfed systems, which are dominant in SSA and further developed to take into account soil texture and soil water availability. Digital decision support tools such as RiceAdvice and Nutrient Expert can enable wider dissemination of locally relevant SSNM recommendations to reach large numbers of farmers at scale. One of the major limitations of the currently available SSNM decision support tools is the requirement of acquiring a significant amount of farm-specific information needed to formulate SSNM recommendations. The scaling potential of SSNM will be greatly enhanced by integration with other agronomic advisory platforms and seamless integration of digital soil, climate and crop information to improve predictions of SSNM recommendations with reduced need for on-farm data collection. Uncertainty should also be included in future solutions, primarily to also better account for varying prices and economic outcomes.
增加肥料的获取和使用是提高撒哈拉以南非洲(SSA)作物产量和粮食安全的重要组成部分。然而,鉴于小农户农场的异质性,肥料施用需要根据特定的种植条件进行调整,以提高产量、盈利能力和养分利用效率。特定地点养分管理(SSNM)方法最初于20世纪90年代开发,用于为亚洲的水稻生成特定田间的肥料推荐,目前也已引入到SSA的水稻、玉米和木薯种植系统中。研究表明,SSNM方法可提高产量、盈利能力和养分利用效率。与农民的常规做法相比,SSA地区采用SSNM方法种植水稻和玉米的产量平均分别提高了24%和69%;与当地统一的肥料推荐相比,产量分别提高了11%和4%。然而,需要进行更广泛的田间评估,以量化SSNM方法在不同种植系统和环境中的更广泛效益。特别是对于水稻,SSNM方法应扩展到SSA地区占主导地位的雨养系统,并进一步改进,以考虑土壤质地和土壤水分供应情况。诸如RiceAdvice和Nutrient Expert等数字决策支持工具能够更广泛地传播与当地相关的SSNM推荐,从而大规模惠及大量农民。目前可用的SSNM决策支持工具的主要局限性之一是,制定SSNM推荐需要获取大量特定农场的信息。通过与其他农艺咨询平台整合,并将数字土壤、气候和作物信息无缝集成,以改进SSNM推荐的预测,减少对农场数据收集的需求,将大大增强SSNM的推广潜力。未来的解决方案还应纳入不确定性因素,主要是为了更好地考虑价格和经济结果的变化。