UNDERSTANDING THE MULTIPLE SOURCES DRIVERS OF AGRICULTURAL INCOME AMONGST SMALLHOLDER FARMERS IN SOUTHERN MALI

Immediate yield loss information is required to trigger crop insurance payouts, which are important to secure agricultural income stability for millions of smallholder farmers. Techniques for monitoring crop growth in real-time and at 5 km spatial resolution may also aid in designing price interventions or storage strategies for domestic production. In India, the current government-backed PMFBY (Pradhan Mantri Fasal Bima Yojana) insurance scheme is seeking such technologies to enable cost-efficient insurance premiums for Indian farmers. In this study, we used the Decision Support System for Agrotechnology Transfer (DSSAT) to estimate yield and yield anomalies at 5 km spatial resolution for Kharif rice (Oryza sativa L.) over India between 2001 and 2017. We calibrated the model using publicly available data: namely, gridded weather data, nutrient applications, sowing dates, crop mask, irrigation information, and genetic coefficients of staple varieties. The model performance over the model calibration years (2001–2015) was exceptionally good, with 13 of 15 years achieving more than 0.7 correlation coefficient (r), and more than half of the years with above 0.75 correlation with observed yields. Around 52% (67%) of the districts obtained a relative Root Mean Square Error (rRMSE) of less than 20% (25%) after calibration in the major rice-growing districts (>25% area under cultivation). An out-of-sample validation of the calibrated model in Kharif seasons 2016 and 2017 resulted in differences between state-wise observed and simulated yield anomalies from –16% to 20%. Overall, the good ability of the model in the simulations of rice yield indicates that the model is applicable in selected states of India, and its outputs are useful as a yield loss assessment index for the crop insurance scheme PMFBY.

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Participation in ICT-based market information projects, smallholder farmers’ commercialisation, and agricultural income effects: findings from Kenya

Development in Practice ◽

10.1080/09614524.2020.1754340 ◽

2020 ◽

Vol 30 (8) ◽

pp. 1043-1057

Author(s):

Julius J. Okello ◽

Oliver K. Kirui ◽

Zachary M. Gitonga

Keyword(s):

Smallholder Farmers ◽

Market Information ◽

Income Effects ◽

Agricultural Income

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Agricultural infrastructure as the driver of emerging farmers’ income in South Africa. A stochastic frontier approach

Agronomía Colombiana ◽

10.15446/agroncolomb.v38n2.81292 ◽

2020 ◽

Vol 38 (2) ◽

pp. 261-271

Author(s):

Ndumiso Mazibuko ◽

Michael Antwi ◽

Theresa Rubhara

Keyword(s):

Smallholder Farmers ◽

Stochastic Frontier ◽

Agricultural Extension ◽

Stochastic Frontier Approach ◽

Cross Sectional ◽

Education Access ◽

Explanatory Variables ◽

Agricultural Income ◽

Household Members ◽

Physical Accessibility

A stochastic frontier model was applied to cross-sectional data to examine whether availability and accessibility of agricultural infrastructure for emerging farmers enhance their agricultural income through efficiency gains. Using a stratified sampling approach, the study grouped the farmers into two; those who had agricultural infrastructure and those who did not have it. Through a survey, data collected from a sample of 150 smallholder farmers in the study area were analyzed using the frontier model. The explanatory variables that were statistically significant and which influenced the agricultural income of the emerging farmers in the study area included the following: equipment, social, institutional availability and physical accessibility indices, education, access to agricultural extension services, age of farmers, assistance of household members in farming, membership in farmers’ organizations, and marital status of the farmers. Informed policies aimed at improving the income of smallholder farmers might consider the results of the explanatory variables included in this study.

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Identifying Constraints and Opportunities for Improving the Health and Productivity Of Chickens Raised By Smallholder Farmers In The Marginal Upland Barangays Of Inopacan, Leyte, Philippines

Annals of Tropical Research ◽

10.32945/atr36s19.2014 ◽

2014 ◽

pp. 278-296

Author(s):

Eugene Lañada ◽

Dave Amihan

Keyword(s):

Performance Indicators ◽

Smallholder Farmers ◽

Key Performance Indicators ◽

Epidemiological Methods ◽

Chicken Flock ◽

Attrition Rates ◽

For Profit ◽

Agricultural Income ◽

Commercial Feed ◽

Data Collection Sheet

o identify constraints and opportunities for improving the health and productivity of chickens raised by smallholder farmers in the marginal uplands, a survey was carried out in 4 upland barangays of Inopacan, Leyte, involving questionnaire-interviews on smallholder chicken raisers. Data were gathered from randomly selected households during a single visit to each of these households using a structured data collection sheet. Descriptive and analytic work on the data was carried out, with modeling on 2 key performance indicators: chicken attrition rates and income levels from chicken production. Results show that smallholder chicken raising in the uplands of Inopacan is typically a semi-scavenging system, with generally low productivity. Using epidemiological methods, 150 putative factors were examined for association with the 2 key performance indicators: overall chicken attrition (ATTRITION), and income from chicken production (INCOME). Of these factors, 13 and 29 variables were found to be associated (P<0.20), respectively, with ATTRITION and INCOME. Logistic regression analysis for ATTRITION revealed that feeding chickens while caged, giving rice as feed, and farmers' practice of treating sick chickens proved highly significant in the model. Likewise, for INCOME, analysis revealed that 5 factors were highly significant in the model: selling chickens owned for profit, commercial feed given as chicken feed, copra making is a source of agricultural income, raiser is satisfied with the performance of his chicken flock, and amount of coconut given per flock per month. The implications of the results, and using the epidemiological approach in studying smallholder chicken productivity and health are discussed.

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Adoption of Small-Scale Irrigation Farming as a Climate-Smart Agriculture Practice and Its Influence on Household Income in the Chinyanja Triangle, Southern Africa

10.20944/preprints201802.0006.v1 ◽

2018 ◽

Author(s):

Nelson Mango ◽

Clifton Makate ◽

Lulseged Tamene ◽

Powell Mponela ◽

Gift Ndengu

Keyword(s):

Climate Variability ◽

Household Income ◽

Smallholder Farmers ◽

Ordinary Least Squares ◽

Small Scale ◽

Least Squares Regression ◽

Climate Variability And Change ◽

Agricultural Income ◽

Smart Agriculture ◽

Small Scale Irrigation

This article concerns the adoption of small-scale irrigation farming as a climate-smart agriculture practice and its influence on household income in the Chinyanja Triangle. Chinyanja Triangle is a region that experiences mid-season dry spells and an increase in occurrences of drought due to low and erratic rainfall patterns which is attributed largely to climate variability and change. This poses high agricultural production risks, which aggravate poverty and food insecurity. For this region, adoption of small-scale irrigation farming as a climate-smart agriculture practice is very important. Through a binary logistic and ordinary least squares regression, the article determines factors that influence the adoption of small-scale irrigation farming as a climate-smart agriculture practice and its influence on income among smallholder farmers. The results show that off-farm employment, access to irrigation equipment, access to reliable water sources and awareness of water conservation practices, such as rainwater harvesting have a significant influence on the adoption of small-scale irrigation farming. On the other hand, the farmer’s age, distance travelled to the nearest market and nature of employment negatively influenced the adoption of small-scale irrigation farming decisions. Ordinary least squares regression results showed that the adoption of small-scale irrigation farming as a climate-smart agriculture practice has a significant positive influence on agricultural income. We therefore conclude that to empower smallholder farmers to quickly respond to climate variability and change, practices that will enhance adoption of small-scale irrigation farming in the Chinyanja Triangle are critical as this will significantly impact on agricultural income.

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Agreeableness, Conflict Resolution Tactics, and School Behavior in Second Graders

Journal of Individual Differences ◽

10.1027/1614-0001/a000199 ◽

2016 ◽

Vol 37 (3) ◽

pp. 145-151 ◽

Cited By ~ 2

Author(s):

Daniel L. Gadke ◽

Renée M. Tobin ◽

W. Joel Schneider

Keyword(s):

Conflict Resolution ◽

Problem Behaviors ◽

Second Graders ◽

Adaptive Behaviors ◽

Second Grade ◽

School Behavior ◽

Multiple Sources ◽

School Based ◽

Second Grade Students ◽

Negotiation Tactics

Abstract. This study examined the association between Agreeableness and children’s selection of conflict resolution tactics and their overt behaviors at school. A total of 157 second graders responded to a series of conflict resolution vignettes and were observed three times during physical education classes at school. We hypothesized that Agreeableness would be inversely related to the endorsement of power assertion tactics and to displays of problem behaviors, and positively related to the endorsement of negotiation tactics and to displays of adaptive behaviors. Consistent with hypotheses, Agreeableness was inversely related to power assertion tactics and to displays of off-task, disruptive, and verbally aggressive behaviors. There was no evidence that Agreeableness was related to more socially sophisticated responses to conflict, such as negotiation, with our sample of second grade students; however, it was related to displays of adaptive behaviors, specifically on-task behaviors. Limitations, including potential reactivity effects and the restriction of observational data collection to one school-based setting, are discussed. Future researchers are encouraged to collect data from multiple sources in more than one setting over time.

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