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Dose-response models to guide site-specific nutrient management and lessons for fertiliser trial design in sub-Saharan Africa

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EXPERIMENTAL AGRICULTURE
卷 58, 期 -, 页码 -

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CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0014479721000193

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Liebig's law; Mitscherlich's law; Plateau function

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Optimisation of fertiliser use and site-specific nutrient management are increasingly critical in balancing agricultural productivity with the growing demand for food and environmental concerns. Trials in sub-Saharan Africa have focused on developing economically optimum rates (EORs) for crops, but estimation of nutrient-response parameters and EORs is challenging. Recommendations include using factorial designs and response surface models, using a minimum of six nutrient levels, and considering Reference Soil Groups and cropping history for site-specific EORs.
Optimisation of fertiliser use and site-specific nutrient management are increasingly becoming critical because of the growing need to balance agricultural productivity with the growing demand for food and environmental concerns. Trials to determine responses of crops to fertilisers have been widely conducted in sub-Saharan Africa (SSA) with increasing emphasis on the development of economically optimum rates (EORs). Computation of EORs depends on accurate estimation of both the optimum nutrient rate and the agronomic maximum yield response; however, estimation of nutrient-response parameters and EORs is beset by a number of problems. Therefore, the objectives of this paper were to (1) point out common problems in the development and use of nutrient dose-response models and (2) provide corrective measures to facilitate future trial design and data analysis. This review outlines the underlying assumptions, strengths and limitations of the various response functions in order to facilitate informed choices by practitioners. Using specific examples, it also shows that (1) the commonly used trial designs do not allow examination of interactions between two or more nutrients and (2) trial designs with <= 5 nutrient levels and wide spacing between the levels result in large uncertainty in dose-response parameters. The key recommendations emerging from the review are as follows: (1) factorial designs and response surface models should be used more widely to address interactions between nutrients; (2) a minimum of six carefully spaced nutrient levels should be used to correctly estimate dose-response parameters; and (3) when locating field trials, Reference Soil Groups and cropping history should be carefully considered to produce site-specific EORs.

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