Determining and managing maize yield gaps in Rwanda
Autor: | Philip J. Smethurst, Athanase R. Cyamweshi, Alain Ndoli, Leon N. Nabahungu, Athanase Mukuralinda, Charles Bucagu |
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Rok vydání: | 2020 |
Předmět: |
Food security
010504 meteorology & atmospheric sciences business.industry Yield (finance) Yield gap 04 agricultural and veterinary sciences Agricultural engineering Development engineering.material 01 natural sciences Normalized Difference Vegetation Index Nutrient Agriculture 040103 agronomy & agriculture engineering 0401 agriculture forestry and fisheries Fertilizer Soil fertility business Agronomy and Crop Science 0105 earth and related environmental sciences Food Science Mathematics |
Zdroj: | Food Security. 12:1269-1282 |
ISSN: | 1876-4525 1876-4517 |
DOI: | 10.1007/s12571-020-01059-2 |
Popis: | Smallholder maize growers are experiencing significant yield gaps due to sub-optimal agricultural practices. Adequate agricultural inputs, particularly nutrient amendments and best management practices, are essential to reverse this trend. There is a need to understand the cause of variations in maize yield, provide reliable early estimates of yields, and make necessary recommendations for fertilizer applications. Maize yield prediction and estimates of yield gaps using objective and spatial analytical tools could provide accurate and objective information that underpin decision support. A study was conducted in Rwanda at Nyakiliba sector and Gashora sector located in Birunga and Central Bugesera agro-ecological zones, with the objectives of (1) determining factors influencing maize yield, (2) predicting maize yield (using the Normalized Difference Vegetation Index (NDVI) approach), and (3) assessing the maize yield gaps and the impact on food security. Maize grain yield was significantly higher at Nyakiliba (1.74 t ha−1) than at Gashora (0.6 t ha−1). NDVI values correlated positively with maize grain yield at both sites (R2 = 0.50 to 0.65) and soil fertility indicators (R2 = 0.55 to 0.70). Maize yield was highest at 40 kg P ha−1 and response to N fertilizer was adequately simulated at Nyakiliba (R2 = 0.85, maximum yield 3.3 t ha−1). Yield gap was 4.6 t ha−1 in Nyakiliba and 5.1 t ha−1 in Gashora. Soil variables were more important determinants of social class than family size. Knowledge that low nutrient inputs are a major cause of yield gaps in Rwanda should prioritize increasing the rate of fertilizer use in these agricultural systems. |
Databáze: | OpenAIRE |
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