Bio-agroeconomic returns in beet-cowpea intercropping by optimization of population densities and spatial arrangements
ABSTRACT. One of the great challenges of the beet and cowpea cultivation in crop association is to maintain their productivity as that of their sole counterparts in semi-arid environment. In this context, the objective of this work is to assess whether there is bio-agroeconomic return in associations of beet-cowpea by the optimization of population densities and spatial arrangements of the component crops. Experiments were performed in randomised complete block designs with treatments arranged in a 4 × 3 factorial scheme, with four replications. The first factor was the population densities of cowpea (100, 80, 60, and 40% of the recommended population in single crop - RPSC) in association with beet, and the second factor was the spatial arrangements (2:2, 3:3, and 4:4), formed by beet (B) rows alternating with cowpea (C) rows. The competition and agronomic indices evaluated were aggressiveness, competitive ratio, land equivalent ratio, actual yield loss, intercropping advantage and the productive efficiency index. The economic indicators evaluated were gross income, net income, rate of return and profit margin. High agro-economic efficiency can be obtained in the cultivation of beet and cowpea intercropping when well-managing the factors of production, population densities and spatial arrangement of the component crops. The greatest agro-economic return of the cowpea and beet intercropping was obtained in the population densities of 40 and 100% of RPSC for cowpea and beet, respectively. The 2:2 spatial arrangement between beet and cowpea crops was the one with the best productive performance and higher indicators of economic return. The cowpea was the dominant crop while the beet was dominated.
Main Authors: | , , , , , , |
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Format: | Digital revista |
Language: | English |
Published: |
Editora da Universidade Estadual de Maringá - EDUEM
2022
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Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-86212022000105026 |
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