Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices
Over the past five years, rice production in Bantaeng Regency has averaged 5.2 tons per hectare, considerably below Bantaeng Regency's 2020 goal of 10.0 tons. Low rice yield internationally and domestically has prompted many studies to assess the effect of farmer and farm characteristics, and i...
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Elsevier
2024-12-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024166650 |
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| author | Muslim Salam Nurul Auliyah Saadah A. Nixia Tenriawaru Pipi Diansari Rahmadanih Ahmad Imam Muslim Hamed Noralla Bakheet Ali Muhammad Ridwan |
| author_facet | Muslim Salam Nurul Auliyah Saadah A. Nixia Tenriawaru Pipi Diansari Rahmadanih Ahmad Imam Muslim Hamed Noralla Bakheet Ali Muhammad Ridwan |
| author_sort | Muslim Salam |
| collection | DOAJ |
| description | Over the past five years, rice production in Bantaeng Regency has averaged 5.2 tons per hectare, considerably below Bantaeng Regency's 2020 goal of 10.0 tons. Low rice yield internationally and domestically has prompted many studies to assess the effect of farmer and farm characteristics, and input factors on rice production. These include education, agricultural income, farmer cooperatives, production inputs, and financing. In response to this issue, the present study examined determinants of rice production in Bantaeng Regency, Indonesia. A representative sample of 185 rice farmers was randomly selected for structured interviews. The data analysis was carried out by employing the Binary Logistics Regression Analysis (BLRA). We used the BLRA to regress thirteen independent variables (land area, seed application, urea fertilizer, NPK fertilizer, insecticides, herbicides, farm labor, education length, education level, farmer age, experience in farming, landowner status, and farming distance) to examine their effects on rice production. As a result, all independent variables simultaneously had a statistically significant effect on rice yield. Then, the partial testing of thirteen variables revealed that five variables—urea fertilizer, NPK fertilizer, pesticide, labor, and farmer age—had a positive and significant impact on rice production. In contrast, the seed application variable has a statistically negative effect on rice yield, while the other variables do not. Based on the results of this study, we recommend five innovative rice farm management strategies to enhance rice production in the future. Firstly, the farmer should expand their cropped area and increase the use of urea fertilizer, insecticides, and herbicides, labor and seed reduction is expected to boost rice yield immediately. Secondly, governments must ensure farmers' access to urea and NPK fertilizers, pesticides, and certified seeds in the future. Thirdly, policymakers must regulate the high costs and limited availability of chemical fertilizers and pesticides, including insecticides and herbicides. The policymaker would guarantee farmers adequate access to these resources. Fourthly, the farmers should use certified seeds with great output potential and apply the right amount. Fifthly, the rural labor replacement policy regulates rural wages and pay to handle the expected farm labor shortage. |
| format | Article |
| id | doaj-art-f981dd64a5c84a70ba5f61c98dceb309 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-f981dd64a5c84a70ba5f61c98dceb3092024-12-13T10:59:18ZengElsevierHeliyon2405-84402024-12-011023e40634Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practicesMuslim Salam0Nurul Auliyah1 Saadah2A. Nixia Tenriawaru3Pipi Diansari4 Rahmadanih5Ahmad Imam Muslim6Hamed Noralla Bakheet Ali7Muhammad Ridwan8Laboratory of Farm Management and Agricultural Marketing, Department of Socio-economics of Agriculture, Faculty of Agriculture, Universitas Hasanuddin, Jl. Perintis Kemerdekaan Km, 10 Makassar, 90245, Indonesia; Corresponding author.Laboratory of Farm Management and Agricultural Marketing, Department of Socio-economics of Agriculture, Faculty of Agriculture, Universitas Hasanuddin, Jl. Perintis Kemerdekaan Km, 10 Makassar, 90245, IndonesiaLaboratory of Farm Management and Agricultural Marketing, Department of Socio-economics of Agriculture, Faculty of Agriculture, Universitas Hasanuddin, Jl. Perintis Kemerdekaan Km, 10 Makassar, 90245, IndonesiaLaboratory of Farm Management and Agricultural Marketing, Department of Socio-economics of Agriculture, Faculty of Agriculture, Universitas Hasanuddin, Jl. Perintis Kemerdekaan Km, 10 Makassar, 90245, IndonesiaLaboratory of Farm Management and Agricultural Marketing, Department of Socio-economics of Agriculture, Faculty of Agriculture, Universitas Hasanuddin, Jl. Perintis Kemerdekaan Km, 10 Makassar, 90245, IndonesiaLaboratory of Farm Management and Agricultural Marketing, Department of Socio-economics of Agriculture, Faculty of Agriculture, Universitas Hasanuddin, Jl. Perintis Kemerdekaan Km, 10 Makassar, 90245, IndonesiaThe United Graduate School of Agriculture Sciences, Kagoshima University, Kagoshima-shi, Korimoto-ichi-chome 21-ban 24-go, 890-0065, JapanOmdurman Islamic University, Omdurman Abuseeds, Main Campus, Khartoum, Al-Khartoum, P.O. Box 382, Postal Code, 14415, SudanAgricultural Information Institute (AII), Chinese Academy of Agricultural Sciences Haidian, Beijing, 100081, ChinaOver the past five years, rice production in Bantaeng Regency has averaged 5.2 tons per hectare, considerably below Bantaeng Regency's 2020 goal of 10.0 tons. Low rice yield internationally and domestically has prompted many studies to assess the effect of farmer and farm characteristics, and input factors on rice production. These include education, agricultural income, farmer cooperatives, production inputs, and financing. In response to this issue, the present study examined determinants of rice production in Bantaeng Regency, Indonesia. A representative sample of 185 rice farmers was randomly selected for structured interviews. The data analysis was carried out by employing the Binary Logistics Regression Analysis (BLRA). We used the BLRA to regress thirteen independent variables (land area, seed application, urea fertilizer, NPK fertilizer, insecticides, herbicides, farm labor, education length, education level, farmer age, experience in farming, landowner status, and farming distance) to examine their effects on rice production. As a result, all independent variables simultaneously had a statistically significant effect on rice yield. Then, the partial testing of thirteen variables revealed that five variables—urea fertilizer, NPK fertilizer, pesticide, labor, and farmer age—had a positive and significant impact on rice production. In contrast, the seed application variable has a statistically negative effect on rice yield, while the other variables do not. Based on the results of this study, we recommend five innovative rice farm management strategies to enhance rice production in the future. Firstly, the farmer should expand their cropped area and increase the use of urea fertilizer, insecticides, and herbicides, labor and seed reduction is expected to boost rice yield immediately. Secondly, governments must ensure farmers' access to urea and NPK fertilizers, pesticides, and certified seeds in the future. Thirdly, policymakers must regulate the high costs and limited availability of chemical fertilizers and pesticides, including insecticides and herbicides. The policymaker would guarantee farmers adequate access to these resources. Fourthly, the farmers should use certified seeds with great output potential and apply the right amount. Fifthly, the rural labor replacement policy regulates rural wages and pay to handle the expected farm labor shortage.http://www.sciencedirect.com/science/article/pii/S2405844024166650Resource allocationRice farmingRice productionBinary logistic regressionSustainable farming |
| spellingShingle | Muslim Salam Nurul Auliyah Saadah A. Nixia Tenriawaru Pipi Diansari Rahmadanih Ahmad Imam Muslim Hamed Noralla Bakheet Ali Muhammad Ridwan Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices Heliyon Resource allocation Rice farming Rice production Binary logistic regression Sustainable farming |
| title | Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices |
| title_full | Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices |
| title_fullStr | Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices |
| title_full_unstemmed | Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices |
| title_short | Determinants of rice production in Bantaeng Regency, Indonesia: In search of innovative sustainable farm management practices |
| title_sort | determinants of rice production in bantaeng regency indonesia in search of innovative sustainable farm management practices |
| topic | Resource allocation Rice farming Rice production Binary logistic regression Sustainable farming |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024166650 |
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