Assessment of the level of compliance with good agricultural practices for cotton production in the different cotton-growing zones of Benin
Abstract
CONTEXT: Cotton is cultivated in Benin, making a significant contribution to the country's export earnings and the livelihoods of smallholder farmers. However, there have been some claims about poor agricultural practices that lead to a continuous decline in crop yields. To improve these inconsistencies, the application of cultivation practices recommended by research is necessary to boost cotton yield. OBJECTIVE: This study assessed the gaps between cotton farmers' practices and those recommended by research, and identified the causes of poor compliance by farmers with good agricultural practices in northern and southern cotton farming systems of Benin. METHODS: To this end, 360 cotton plots were monitored, from soil preparation to harvest, on 180 cotton farms in different cotton-growing zones of Benin. At the same time, management data were collected from cotton farmers through semi-structured interviews. Factorial Analysis of Mixed Data and Ascending Hierarchical Classification were performed to typify the farming system based on management and socioeconomic information. The envelope curve was used to estimate the optimal thresholds for nitrogen, phosphorus, and cotton planting date. A multinomial logistic regression model and a binary logistic regression model were used to estimate the determinants of poor compliance with good practices in cotton production by smallholders. RESULTS AND CONCLUSIONS: The results revealed five clusters of cotton farmer practices, with three from the north and two from the south of Benin. These practices were categorized as those that deviated from good cotton production practices (GCPP, 36.2% of plots monitored), those that were moderately close to GCPP (30.8%), and those that were closest to GCPP (33%). However, it was found that following the recommended practices did not systematically lead to better yields. The envelope curve revealed optimal thresholds for nitrogen, phosphorus, and planting date, beyond which seed cotton yield stabilized. Farm machinery ownership was a key factor in facilitating compliance with GCPP. The number of power tillers and oxen pulls had statistically significant effects on the level of compliance with GCPP. The same was true for hired labor and the area of cotton sown by the farmer. Agricultural policies must therefore prioritize these factors to improve cotton production. SIGNIFICANCE: This study will help reduce yield gaps, improve input use efficiency, and ultimately enhance the sustainability and profitability of cotton farming in Benin.
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BibTeX
@article{takpa2026assessment,
title = {{Assessment of the level of compliance with good agricultural practices for cotton production in the different cotton-growing zones of Benin}},
author = {O'Neil Gilchrist Takpa and Pierre Gnènoukpo Tovihoudji and Romain Loison and Isidore Amonmide and Benjamin Heuclin and Emmanuel Sêkloka and Pablo Tittonell and Rodrigue V. Cao Diogo},
journal = {Agricultural Systems},
year = {2026},
month = sep,
doi = {10.1016/j.agsy.2026.104807},
url = {https://hal.science/hal-05756386v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Assessment of the level of compliance with good agricultural practices for cotton production in the different cotton-growing zones of Benin
AU - O'Neil Gilchrist Takpa
AU - Pierre Gnènoukpo Tovihoudji
AU - Romain Loison
AU - Isidore Amonmide
AU - Benjamin Heuclin
AU - Emmanuel Sêkloka
AU - Pablo Tittonell
AU - Rodrigue V. Cao Diogo
PY - 2026
DA - 2026/09/21
JO - Agricultural Systems
DO - 10.1016/j.agsy.2026.104807
UR - https://hal.science/hal-05756386v1
AB - CONTEXT: Cotton is cultivated in Benin, making a significant contribution to the country's export earnings and the livelihoods of smallholder farmers. However, there have been some claims about poor agricultural practices that lead to a continuous decline in crop yields. To improve these inconsistencies, the application of cultivation practices recommended by research is necessary to boost cotton yield. OBJECTIVE: This study assessed the gaps between cotton farmers' practices and those recommended by research, and identified the causes of poor compliance by farmers with good agricultural practices in northern and southern cotton farming systems of Benin. METHODS: To this end, 360 cotton plots were monitored, from soil preparation to harvest, on 180 cotton farms in different cotton-growing zones of Benin. At the same time, management data were collected from cotton farmers through semi-structured interviews. Factorial Analysis of Mixed Data and Ascending Hierarchical Classification were performed to typify the farming system based on management and socioeconomic information. The envelope curve was used to estimate the optimal thresholds for nitrogen, phosphorus, and cotton planting date. A multinomial logistic regression model and a binary logistic regression model were used to estimate the determinants of poor compliance with good practices in cotton production by smallholders. RESULTS AND CONCLUSIONS: The results revealed five clusters of cotton farmer practices, with three from the north and two from the south of Benin. These practices were categorized as those that deviated from good cotton production practices (GCPP, 36.2% of plots monitored), those that were moderately close to GCPP (30.8%), and those that were closest to GCPP (33%). However, it was found that following the recommended practices did not systematically lead to better yields. The envelope curve revealed optimal thresholds for nitrogen, phosphorus, and planting date, beyond which seed cotton yield stabilized. Farm machinery ownership was a key factor in facilitating compliance with GCPP. The number of power tillers and oxen pulls had statistically significant effects on the level of compliance with GCPP. The same was true for hired labor and the area of cotton sown by the farmer. Agricultural policies must therefore prioritize these factors to improve cotton production. SIGNIFICANCE: This study will help reduce yield gaps, improve input use efficiency, and ultimately enhance the sustainability and profitability of cotton farming in Benin.
SN - 0308-521X
SN - 1873-2267
ER -