Determinants of crop diversification amongst agricultural co-operators in Dundwa agricultural camp, Choma district, Zambia

Dube, Lighton; Numbwa, Revaux; Guveya, Emmanuel

doi:10.18488/journal.1005/2016.6.1/1005.1.1.13

Cited by 8 publications

(4 citation statements)

References 16 publications

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“…This could be explained by the notion that having a higher number of agricultural implements facilitates farmers in cultivating a higher variety of crops during each period. These findings are consistent with those of existing empirical research (Dube et al, 2016; Kasem & Thapa, 2011). Furthermore, the positive coefficient of access to roads implies that farm households with road connectivity are more likely to adopt crop diversification.…”

Section: Econometric Resultssupporting

confidence: 92%

Analysis of Irrigation Enhancement, Crop Diversification and Farm Profits: Evidence from Telangana State

Peddi,

Reddy

2023

Review of Development and Change

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In this study, the impact of access to irrigation on crop diversification and farm-level profits in the state of Telangana was examined. This study comprised two primary aspects. First, the determinants of crop diversification in Telangana were investigated using the logit model. Second, various farm production models were developed to evaluate the impact of irrigation enhancement sources on the farm profit function. The findings of this study indicate that the agricultural implements index and market access variables play a role in determining crop diversification in the studied villages, whereas surface irrigation has a negative effect on crop diversification. The Cobb–Douglas production function with different specifications was used in this study, which showed that the logarithms of the fertiliser variable and access to new irrigation facilities that improve groundwater table significantly enhance farm profits in the villages studied. The inclusion of a dummy variable representing agro-climatic conditions also revealed a significant effect on farm profits, indicating that farmers in north-zone districts achieve higher profits than those in central-zone districts, likely due to differences in soil fertility and crop diversification. Understanding the factors influencing farm profits is crucial for policymakers and extension agents in the state for informed decision-making and policy formulation.

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Section: Econometric Resultssupporting

confidence: 92%

Analysis of Irrigation Enhancement, Crop Diversification and Farm Profits: Evidence from Telangana State

Peddi,

Reddy

2023

Review of Development and Change

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“…This was clearly supported by male farmers having greater access to agricultural production resources than female farmers which increased their level of diversification. This result was consistent with [26] in Zimbabwe having a male household head increased crop diversification.…”

Section: Factors Influencing Crop Diversification Of Perambalur Districtsupporting

confidence: 84%

“…Unlike herfindahl index, the entropy index increases as diversification increases. It is a direct measure of diversification with a logarithmic scale [23,24,25,26].It is defined as:…”

Section: Fig 1 Map Showing Selected Blocks Of Perambalur and Kanyakumari Districtmentioning

confidence: 99%

Determinants of Agricultural Production Diversification among Marginal and Small Farmers of Kanyakumari and Perambalur

Melba

Ashok

Vidhyavathi

et al. 2021

CJAST

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Aims: To assess the influence of agricultural production diversity of marginal and small farmers Study Design: Purposive Random Sampling Place and Duration of Study: Kanyakumari and Perambalur districts in Tamil Nadu were purposefully chosen for the survey, which was conducted through primary data collection from July to August 2020. Methodology: According to the Tamil Nadu state planning commission report 2017, Kanyakumari and Perambalur districts were chosen at random from the top five and bottom five districts of the food security index to analyze dietary diversity. The crop diversification index was calculated using the entropy index. The Tobit model is used to investigate the impact of diverse agriculture production among marginal and small farming households. Results: The findings clearly show that, of the two districts, Perambalur has diversified more than Kanyakumari. Farmers in Perambalur district cultivate agricultural crops, whereas farmers in Kanyakumari district selected block cultivate horticultural crops, particularly plantation crops. According to the Tobit results, the number of cattle, farm size, credit available, and distance from the market all had a positive and significant influence on crop diversification. Improving female-headed household decision-making, promoting household investment and infrastructure facilities, and suggesting crop development as crop diversification measures. Conclusion: The results conclude that farmers in Perambalur district have highly diversified cropping than Kanyakumari district.

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“…Household size has positive impact on crop diversification, education has negative impact on crop diversification, crop area group has a positive impact on crop diversification, FISP has a positive impact on crop diversification and age has a positive impact on crop diversification as shown on table 4.15 above. Dube (2016) points out that on a contrary, the age of household head, total farm size, access to agricultural markets and total area cultivated negatively influence crop diversification.…”

Section: Resultsmentioning

confidence: 99%

Assessing the Factors Affecting Crop Diversification in Masaiti District of the Copperbelt Province of Zambia

Sitali,

Musaba,

Kafumukache

et al. 2023

Int. J. Res. Publ. Rev.

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Crop diversification is an important issue in agriculture that has impact on both food security and farm incomes. The objective of this study was to assess the factors affecting crop diversification of smallholder farmers in Masaiti district. Data for the study were collected from a sample of 200 farmers selected using the clustered sampling method. A questionnaire administered by the researcher was used for data collection. Data were analysed using descriptive statistics and logistic regression. Crop diversification was estimated using the Simpson Diversification Index (SDI).The results of the logistic regression model revealed that, farming experience and age of the farmers significantly influence crop diversification. The other variable namely household size, gender, labour cost, household income, FISP, number of field plots had no significant effect on crop diversification.According to the findings of the study, age group, household size, extension contact, crop revenue, crop area group, FISP and monthly income had a positive influence towards crop diversification and crop production Education attainment, farming experience, and early supply of inputs have a negative impact on crop diversification and crop production. The research findings correlated with the reviewed literature and the research questions were answered. The mean crop diversification of 0.3650 showed that there was less diversification among the FISP beneficiaries and non-beneficiaries in Masaiti district.

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Determinants of crop diversification amongst agricultural co-operators in Dundwa agricultural camp, Choma district, Zambia

Cited by 8 publications

References 16 publications

Analysis of Irrigation Enhancement, Crop Diversification and Farm Profits: Evidence from Telangana State

Analysis of Irrigation Enhancement, Crop Diversification and Farm Profits: Evidence from Telangana State

Determinants of Agricultural Production Diversification among Marginal and Small Farmers of Kanyakumari and Perambalur

Assessing the Factors Affecting Crop Diversification in Masaiti District of the Copperbelt Province of Zambia

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