Fertilizer response and nitrogen use efficiency in African smallholder maize farms

被引:57
|
作者
Ichami, Stephen M. [1 ,2 ,3 ,4 ,5 ]
Shepherd, Keith D. [2 ]
Sila, Andrew M. [2 ]
Stoorvogel, Jetse J. [5 ]
Hoffland, Ellis [4 ]
机构
[1] Univ Nairobi, Dept Land Resource Management & Agr Technol, Coll Agr & Vet Sci, Fac Agr, POB 29053-00625, Nairobi, Kenya
[2] World Agroforestry Ctr ICRAF, United Nations Ave,POB 30677-00100, Nairobi, Kenya
[3] Int Ctr Trop Agr CIAT Kenya, DuduVille Lane Off Kasarani Rd,POB 823-00621, Nairobi, Kenya
[4] Wageningen Univ, Soil Biol Grp, POB 47, NL-6700 AA Wageningen, Netherlands
[5] Wageningen Univ, Soil Geog & Landscape Grp, POB 47, NL-6700 AA Wageningen, Netherlands
关键词
Kenya; Meta-analysis; Nitrogen; Soil responsiveness; Spatial variability; VARIABLE SELECTION METHODS; NUTRIENT USE EFFICIENCIES; CROP PRODUCTIVITY; PUBLICATION BIAS; WESTERN KENYA; YIELD GAPS; METAANALYSIS; MANAGEMENT; HETEROGENEITY; REGRESSION;
D O I
10.1007/s10705-018-9958-y
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Improving fertilizer recommendations for farmers is essential to increase food security in smallholder landscapes. Currently, blanket recommendations are provided across agro-ecological zones, although fertilizer response and nutrient use efficiency by maize crop are spatially variable. We aimed to identify factors that could help to refine fertilizer recommendation by analyzing the variability in fertilizer response (FR) and the agronomic nitrogen use efficiency (N-AE). A literature search for on-farm studies across Kenya and Sub-Sahara Africa (SSA), excluding Kenya, yielded 71 publications. The variability in FR was studied using a meta-analysis whereas key factors that influence FR and N-AE were studied with linear regression models. On average, the FR was 2, but it varied considerably from 1 to 28.5 (excluding outliers). In SSA, 18% of the plots were non-responsive plots with an FR < 1. The main factors affecting N-AE for Kenya were P-Olsen, silt content, soil pH, clay and rainfall, whereas only soil pH, exchangeable K and texture were important for SSA. However, our study indicates that available data on soil, climate and management factors could explain only a small part (< 33%) of the variation in FR and N-AE. Soil pH, P-Olsen, silt content, and rainfall had significant but low levels of power in explaining variation in FR and N-AE. Our findings indicate that strategies to refine fertilizer recommendation should include information on soil types and soil properties.
引用
收藏
页码:1 / 19
页数:19
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