Allan Nyakora Masese, Lucia Mary Mbithi, N. Joshi, Samson Masese Machuka
Maize (Zea mays L.) is an essential crop in Kenya and its production has a direct implication on food and economic security. However, in Kenya, there is a gap between what is being produced and what is being consumed. This gap is growing and, hence, remains a policy concern. Under this backdrop, this study aimed to estimate thecombined contribution of maize area harvested, expenditure on fertilizers,number of tractors used, and maize seed quantity to national maize productionin Kenya using the Vector Error Correction Model (VECM) and Nerlove Model. The findings indicate that maize production in Kenya is negatively associated with maize area harvested, expenditure on fertilizers, and the number of tractors used. However, there is a positive relationship between maize production and maize seed quantity. The response of maize production depicted that the price of maize in the previous period determined the production levels in the current period positively; however, as we move further away, the price level in the fourth period depicted a negative relationship. This study recommended that the government provide an adequate quantity of maize seeds to boost maize production. It also recommended that farmers be educated on the proper use of fertilizers and the optimum use of tractors and land. Furthermore, the government needs to ensure a favorable and stable price for farmers to contribute to increased maize production.
{"title":"Determinants of Maize Production and Its Supply Response in Kenya","authors":"Allan Nyakora Masese, Lucia Mary Mbithi, N. Joshi, Samson Masese Machuka","doi":"10.1155/2022/2597283","DOIUrl":"https://doi.org/10.1155/2022/2597283","url":null,"abstract":"Maize (Zea mays L.) is an essential crop in Kenya and its production has a direct implication on food and economic security. However, in Kenya, there is a gap between what is being produced and what is being consumed. This gap is growing and, hence, remains a policy concern. Under this backdrop, this study aimed to estimate thecombined contribution of maize area harvested, expenditure on fertilizers,number of tractors used, and maize seed quantity to national maize productionin Kenya using the Vector Error Correction Model (VECM) and Nerlove Model. The findings indicate that maize production in Kenya is negatively associated with maize area harvested, expenditure on fertilizers, and the number of tractors used. However, there is a positive relationship between maize production and maize seed quantity. The response of maize production depicted that the price of maize in the previous period determined the production levels in the current period positively; however, as we move further away, the price level in the fourth period depicted a negative relationship. This study recommended that the government provide an adequate quantity of maize seeds to boost maize production. It also recommended that farmers be educated on the proper use of fertilizers and the optimum use of tractors and land. Furthermore, the government needs to ensure a favorable and stable price for farmers to contribute to increased maize production.","PeriodicalId":13844,"journal":{"name":"International Journal of Agronomy","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47656723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meseret Degefa, S. Alamerew, A. Mohammed, Adeba Gemechu
Coffee (Coffea arabica L.) provides several health benefits to users due to its strong medicinal and nutritional properties and caloric value. Green bean proximate composition diversity is unknown among the coffee genotypes now cultivated in southern Ethiopia. The study’s major goals are to determine the variability in green bean proximate composition among coffee genotypes and to see if there are any relationships between green bean proximate attributes. Therefore, a nutritional laboratory experiment was carried out at Jimma University College of Agriculture and Veterinary Medicine (JUCAVM). Using the augmented design, a total of 104 entries were examined, including 100 accessions from southern Ethiopia and four standard checks. Each accession had data on 07 proximate composition parameters of green beans. The presence of significant ( P <