scholarly journals Farm typology of smallholders integrated farming systems in Southern Coastal Plains of Kerala, India

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Anitrosa Innazent ◽  
D. Jacob ◽  
J. S. Bindhu ◽  
Brigit Joseph ◽  
K. N. Anith ◽  
...  
Keyword(s):  
Farming Systems ◽  
Farming System ◽  
Farm Households ◽  
Farm Income ◽  
Coastal Plains ◽  
Constraint Analysis ◽  
Large Ruminant ◽  
Food Grain ◽  
On Farm ◽  
Farm Types

AbstractAdoption of an integrated farming system (IFS) is essential to achieve food and nutritional security in small and marginal holdings. Assessment of IFS to know the resource availability and socio-economic condition of the farm household, farm typology plays a critical role. In this regard, a sample survey of 200 marginal households practicing mixed crop-livestock agriculture was conducted during 2018–2019 at Southern Coastal Plains, which occupies 19,344 ha in Thiruvananthapuram district, Kerala, India. Farming system typology using multivariate statistical techniques of principal component analysis and cluster analysis characterized the diverse farm households coexisting within distinct homogenous farm types. Farming system typology identified four distinct farm types viz. resource constrained type-1 households with small land owned, high abundance of poultry, very low on-farm income, constituted 46.5%; resource endowed type-2 households oriented around fruit and vegetable, plantation crop, with a moderate abundance of large ruminant and poultry, high on-farm income, constituted 12.5%; resource endowed type-3 household oriented around food grain, extensive use of farm machinery, with a moderate abundance of large ruminant, low on-farm income, constituted 21.5%; and resource endowed type-4 household oriented around fodder, with high abundance of large ruminant, medium on-farm income, constituted 19.5% of sampled households. Constraint analysis using constraint severity index assessed the severity of constraints in food grain, horticulture, livestock, complementary and supplementary enterprises in each farm type, which allowed targeted farming systems interventions to be envisaged to overcome soil health problems, crops and animal production constraints. Farming system typology together with constraint analysis are therefore suggested as a practical framework capable of identifying type-specific farm households for targeted farming systems interventions.

scholarly journals Optimum Farm Plan for Higher Net Income in Southern and Eastern Dry Zone of Karnataka

2021 ◽  
Vol 66 (3) ◽  
Author(s):  
Bhavya, A.P.
Keyword(s):  
Sampling Technique ◽  
Farming Systems ◽  
Farming System ◽  
Farm Income ◽  
Annual Income ◽  
Total Expenditure ◽  
Net Income ◽  
Programming Technique ◽  
Dry Zone ◽  
Optimum Plan

The present study was focused on deriving an optimum farm plan which would enhance the farm income in different farming systems in Southern and Eastern dry zones of Karnataka. Data collected from 240 respondents selected using random sampling technique from two districts viz. Mandya and Kolar. The dominant farming systems identified in the study areas were crop + dairy, crop + sheep rearing, Crop + dairy + sericulture, and crop + dairy + horticulture. Linear programming technique was used to work out the maximum attainable return. In Mandya district, crop + sheep farming system were providing an annual income of ` 92468 per farm with the total expenditure of ` 175400, whereas, an optimal plan can fetch a return of ` 278810 per farm with the similar expenditure. In Kolar district, crop + dairy was giving annual income of ` 168216 per farm with the total expenditure of ` 150000 and through an optimum plan, a farmer could earn ` 327996 per farm. Mandya district In farming system with the component of crop + dairy + sericulture, farmers were realizing an annual income of ` 296433 per farm with the total expenditure of ` 274947, where optimization can provide the farmer an income of ` 640487 per farm with similar expenditure and this system is turned out to be most remunerative among all the farming systems

scholarly journals The Effects of Non-Farm Enterprises on Farm Households’ Income and Consumption Expenditure in Rural India

2019 ◽  
Vol 19 (1) ◽  
pp. 195
Author(s):  
. Zeeshan ◽  
Geetilaxmi Mohapatra ◽  
Arun Kumar Giri
Keyword(s):  
Propensity Score ◽  
Farm Households ◽  
Rural India ◽  
Farm Income ◽  
Consumption Expenditure ◽  
Income Diversification ◽  
Probit Models ◽  
Structural Differences ◽  
Nationally Representative ◽  
On Farm

Nationally representative data of farm households from India Human Development Surveys (IHDS) conducted in 2004-05 and 2011-12 are explored. This article analyzes the effects of income diversification in non-farm enterprises on farm households’ income and consumption expenditure in rural India. Panel probit models were built to examine the determinants of income diversification while propensity score matching was used to account selection bias resulting from unobserved factors and controls for structural differences between diversified and undiversified farm households. The results suggest that by engaging in non-farm enterprises, rural farm households make positive gains in farm income and consumption expenditure.

Does a farmland zoning program impact farm income: empirical evidence from farm households in Taiwan

2020 ◽  
Vol 47 (5) ◽  
pp. 1621-1643
Author(s):  
Hung-Hao Chang ◽  
Tzu-Chin Lin
Keyword(s):  
Income Distribution ◽  
Regression Discontinuity ◽  
Wealth Effect ◽  
Farm Households ◽  
Farm Income ◽  
Regression Discontinuity Design ◽  
Program Impact ◽  
Farm Operators ◽  
On Farm

Abstract Does farmland zoning affect farm income, and why? This study addresses these questions using a case study in Taiwan. We use a unique farmland-level dataset and apply the regression discontinuity design to quantify the effects of zoning on farm income. We find that the zoning program decreases farm income. The programme effects are heterogeneous, as they are more pronounced for farms in the higher percentiles of the farm income distribution. Moreover, a larger effect is found for elderly farm operators. Concerning the mechanism, we argue that the zoning program generated an optional benefit or wealth effect for eligible farms. This wealth effect then reallocates family labour to off-farm jobs. Consequently, the zoning program reduces income from farming.

scholarly journals Decomposition of Income Distribution Among Farm Families

1987 ◽  
Vol 16 (2) ◽  
pp. 165-173 ◽  
Author(s):  
Jill L. Findeis ◽  
Venkateshwar K. Reddy
Keyword(s):  
Income Inequality ◽  
Farm Households ◽  
Farm Income ◽  
Annual Data ◽  
Full Time ◽  
Farm Families ◽  
Income Source ◽  
Regional Income Inequality ◽  
On Farm ◽  
Distribution Of Income

The greater reliance of U.S. farm families on off-farm income has implications for the structure of agriculture and the distribution of income within agriculture. Using annual data on farm households from the Current Population Survey, the degree of income inequality for the U.S. and by region is assessed for 1984. The distribution of income among farm families is decomposed by income source. Off-farm income is shown to contribute to higher average incomes and reduce income inequality at the margin, but only in regions where full-time farming predominates. In the Northeast and South, increases in off-farm income increase regional income inequality.

A Logit Model Based Study on the Influencing Factors on Farm Household’s Adoption of Soil Testing and Formula Fertilizing Technology: A Case of Four Towns

2014 ◽  
Vol 675-677 ◽  
pp. 985-988
Author(s):  
Li Xia Yang
Keyword(s):  
Influencing Factors ◽  
Logit Model ◽  
Education Level ◽  
High Ratio ◽  
Soil Testing ◽  
Farm Households ◽  
Farm Income ◽  
Negative Effect ◽  
Incentive Policies ◽  
On Farm

Based on the survey data collected from 208 farm households of Zhili, Balidian, Huanzhu and Baique, 4 towns of Wuxing district of Huzhou city in Taihu Basin, this paper quantitatively analyzed the influencing factors on farm household’s adoption behavior of soil testing and formula fertilizing technology (STFFT) by using Logit Model. The results showed: (1) The significant favorable influencing factors are household head’s education level, is he/she a farmer cooperative member, has he/she been trained (technically), Has he/she received instructive card of STFFT, and whether or not the household is the STFFT demonstration household; (2) While the high ratio of non-farm income level has a significant negative effect; (3) The household head’s age and multi-operation behavior, farm land scale, and fragmentation of land plots have not significant affection. Based these analysis some related incentive policies about the households’ adoption of STFFT were put forward.

Relative profitability of farming systems research and development (FSRD) project farmers and non-project farmers of integrated farming systems in Tangail district of Bangladesh

2018 ◽  
Vol 16 (1) ◽  
pp. 117-122
Author(s):  
Sajia Sharmin ◽  
M Harun Ar Rashid ◽  
Ratna Begum ◽  
Sadia Sharmin Hoque
Keyword(s):  
Farming Systems ◽  
Farming System ◽  
Farm Income ◽  
Cost Ratio ◽  
Benefit Cost Ratio ◽  
Systems Research ◽  
Integrated Farming ◽  
Human Labor ◽  
Technological Intervention ◽  
Relative Profitability

Integrated farming system modifies the commercial farming system which ensures higher food production to equate the demand, environmental protection through effective recycling of waste and increased farm income. The present study was undertaken to examine the relative profitability of FSRD project farmers and non-project farmers of integrated farming system. Eighty (80) farmers (40 from FSRD project and 40 from non-project farmers) were selected from Kalihati Upazila under Tangail district of Bangladesh. In the study area, vegetables, fish and poultry enterprises were integrated under technological intervention. The waste of poultry farm was used in fish production and the soil of the pond was used in vegetables cultivation. Per hectare net returns from integrated farming were estimated at Tk513458.10 and Tk256511.90for FSRD project farmers and non-project farmers, respectively. Benefit cost ratio (BCR) was 1.66 for FSRD project farmers and1.37 for non-project farmers. In functional analysis, human labor, fingerling, feed, fertilizer, insecticides costs in case of FSRD project farmers and human labor, feed, salt and lime costs in case of non-project farmers had significant impact on per hectare return of integrated farming. FSRD project farmers were more profitable than the non-project farmers. Therefore, it can be concluded that there is great scope to improve the overall economic condition of farmers through introducing integrated farming system in Tangail District of Bangladesh.J. Bangladesh Agril. Univ. 16(1): 117-122, April 2018

scholarly journals Socioeconomic Analysis of Alternative Farming Systems in Improving Livelihood Security of Small Farmers in Selected Areas of Bangladesh

2012 ◽  
Vol 10 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Sadika Sharmin ◽  
M. Serajul Islam ◽  
Md. Kamrul Hasan
Keyword(s):  
Household Income ◽  
Farming System ◽  
Farm Households ◽  
Farm Income ◽  
Farm Household ◽  
Small Farmers ◽  
Small Farm ◽  
Livelihood Security ◽  
Integrated Farming ◽  
Alternative Farming

The present study attempted to determine the economic returns of alternative farming system of integrated farming aiming to address the livelihood security of small farm households. One hundred and sixty small and medium farmers practicing in four different FS such as Crop-Poultry (C-P), Crop-Poultry-Pond fisheries (C-P-F), Crop-Livestock-Poultry (C-L-P) and Crop-Livestock-Poultry-Pond fisheries (C-L-P-F) were selected from Mymensingh, Jamalpur and Sherpur district. The main information collected were socio-demographic characteristics of farm households, household income from farm and non-farm sources, size of land holding and farming system followed, livestock and poultry rearing and pond fish culture, and effect of integrated farming on household income and livelihood security of small farm households. Data were collected covering one production period during 2009-2010. For estimating farm income of small farm household, whole farm approach was considered. Increased number of farm enterprises caused higher farm income. However, considering the small farm practices and whole farm approach, the farm income as well as net return was higher for C-L-P-F farmers (Tk. 57002), followed by C-L-P (Tk. 52978), C-P-F (Tk. 20447) and C-P (Tk. 13734) farmers. Some of the most commonly used factors in the assessment of livelihood security included those related to household income and expenditure, expenditure spent on food, adequacy of food taken, household structure and facilities, owning household assets, and access to drinking water and sanitation, and other basic needs of farm household. All these socioeconomic factors were found to be related livelihood security of small farmers in Bangladesh. Women were more involved in income earning activities and household decision making with the introduction of integrated farming in small farm condition.DOI: http://dx.doi.org/10.3329/agric.v10i1.11065The Agriculturists 2012; 10(1): 51-63

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