Agro-Ecological Distribution of Legumes in Farming Systems and Identification of Biophysical Niches for Legumes Growth

Nandwa, S.M.; Obanyi, S.; Mafongoya, Paramu

doi:10.1007/978-94-007-1536-3_1

Cited by 3 publications

(2 citation statements)

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“…Green manure legumes closed only between 20 and 50% of the exploitable yield gap. In addition, both the ecological and the social niches for farmers adopting green manure technologies in sub-Sahara Africa are limited and widely constrain their adoption [57]. Conversely, Kwesiga et al [34] this issue highlighted the suitability of both the pre-and the post-rice niches for growing leguminous green manures in Kilombero floodplain.…”

Section: Disentangling the Exploitable Yield Gapmentioning

confidence: 99%

Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

et al. 2020

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To meet the growing rice demand in Africa, gaps between actual and attainable yields have to be reduced. In Tanzania, this particularly concerns smallholder rain-fed production systems in the floodplains. After quantifying the existing yield gaps, key contributing factors need to be analyzed to improve site-specific management. Field experiments were conducted for three years and in three pedo-hydrological environments (fringe, middle, and center positions) of the Kilombero floodplain to evaluate: (1) The grain yield under farmers’ management (actual yield), (2) yield with the best-recommended management (attainable yield), and (3) the non-limited yield simulated by the APSIM model (potential yield). In the field, we additionally assessed incremental effects of (1) field bunding and soil levelling, (2 and 3) additionally applying of 60 kg N ha−1, as urea or as farmyard manure (FYM), and (4 and 5) incorporating in-situ-grown leguminous green manures. Attainable yields were determined with mineral N application at 120 kg ha−1, additional PK fertilizer and supplemental irrigation. On average across years and positions, the potential, the attainable, and farmers’ actual yields were 11.5, 8.5, and 2.8 t ha−1 indicating a high total yield gap. About 16–38%, 11–20%, and 28–42% of this gap could be attributed to non-controllable yield-reducing (i.e., pest and diseases), yield-limiting (i.e., water and nutrient deficiencies), and yield-defining factors (i.e., poor soil and crop management), respectively. Results indicate a closure of the exploitable yield gap (differences between attainable and farmers’ actual yields) by up to 6.5 t ha−1 (nearly 60% of the potential yield). This exploitable yield gap was larger in 2016 than in 2017. Also, the gap was larger in the water-limited fringe and middle than in the frequently submerged center positions. Simple field bunds combined with land levelling could close 15–35% of the exploitable yield gap, depending on field positions and year. FYM or green manures were less effective than mineral N; however, in 2017 and in the wetter middle and center positions, they reduced the yield gap by >50%. We conclude that yield gaps in rainfed rice in Kilombero floodplain are large, but that a site- and system-specific adaptation of crop management can close much of the exploitable yield gap and increase grain yields by 0.7–4.8 t ha−1. Similar benefits may be obtained in other hydrologically variable floodplain environments of the region and beyond.

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Section: Disentangling the Exploitable Yield Gapmentioning

confidence: 99%

Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

et al. 2020

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“…Barriers to their implementation are costs (seeds) and lost harvest of a catch crop income. So, farmers often prefer intercropping of, or rotation with, grain legume crops rather than GMCC (Nandwa et al 2011).…”

Section: Mulching Strategies and Green Manure Cover Cropsmentioning

confidence: 99%

Resetting the African Smallholder Farming System: Potentials to Cope with Climate Change

Freyer

Bingen

2021

African Handbook of Climate Change Adaptation

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Agricultural production systems, for example, conservation agriculture, climate smart agriculture, organic agriculture, sustainable landuse management, and others, summarized under the term “sustainable intensification,” have been introduced in African countries to increase productivity and to adapt/mitigate CC (CCAM). But the productivity of smallholder farming systems in Africa remains low. High erosion, contaminated water, threatened human health, reduced soil water, and natural resources functionality, that is, ecosystems services, and decreased biodiversity dominate. Low support in the farm environment is also responsible for this situation.It is hypothesized, based on the huge body of literature on CCAM, that the implementation of already existing arable and plant cultivation methods like crop diversity, alley crops, forage legume-based crop rotations, mulching, organic matter recycling, and reduced tillage intensity will increase CCAM performance and also farm productivity and income. Based on a brief analysis of CCAM relevant arable and plant cultivation methods and agricultural production systems potentials and challenges, this chapter offers guidance for further transforming climate robust African farming systems.

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Fertilizer recommendations for optimal soybean production in North and Center Benin

Chabi¹,

Dagbénonbakin²,

Agbangba³

et al. 2021

J. Soil Sci. Environ. Manage.

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In the traditional cropping systems of Benin Republic, soybean is mostly cultivated with no mineral fertilizer supply, despite the decrease of soil fertility. Furthermore, there is no specific fertilizer available for the crop, in spite of its cash crop character. This leads to weak crop yield in the farmers' fields. The present study aims to determine the optimal doses of each N, P, K, Mg and Zn nutrient to improve soybean production in the Sudano-Guinean and Sudanian zones of Benin Republic. Two years (2018 and 2019) experiment has been carried out in Ouessè district (Sudano-Guinean zone) and Bembèrèkè district (Sudanian zone). Box and Behnken rotating design was used to define N, P, K, Mg and Zn dose combinations leading to 46 combinations. A completely randomized block design was set up considering farmers as replication. In total four farmers' fields are selected. A one-way analysis of variance is made on the yield data, using the linear mixed-effect model. Response surface analyses are used to determine the optimal dose for each N, P, K, Mg and Zn. The supply of macronutrients combined with Zn, significantly (p = 0.001) improved the soybean grain and above biomass yields as well as the harvest index. The quadratic models were efficient (R² > 0.7) to estimate soybean grain yields considering the nutrient dose variation. The optimal N, P, K, Mg and Zn doses of 15.46, 23.20, 28.6, 16.8 and 6.9 kg.ha -1 , respectively (for the Sudano-Guinean zone) and 14.02, 23.89, 17.82, 11.45 and 4.26 kg.ha -1 , respectively (for the Sudanian zone) lead to an optimal seed yield of 2 t.ha -1 (that is, almost 2.2 times the yield in the farmers' field). The development of fertilizer formulas using these determined optimal doses would constitute a suitable technology helping to increase soybean production in both areas.

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Agro-Ecological Distribution of Legumes in Farming Systems and Identification of Biophysical Niches for Legumes Growth

Cited by 3 publications

References 6 publications

Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

Resetting the African Smallholder Farming System: Potentials to Cope with Climate Change

Fertilizer recommendations for optimal soybean production in North and Center Benin

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