Farmers’ choice of varieties and demand for improved cassava stems in Nigeria

In this study, we used a household level survey to assess choices of varieties and demand for improved cassava varieties. A multivariate probit model was used to examine the determinants of choice decisions of the farmers for different varieties preventing potential endogeneity and measurement error. A Linearized Almost Ideal Demand System (LA/AIDS) model was used to analyze the demand system for improved cassava varieties. The results of the (LA/AIDS) model indicated farmers were very price sensitive to changes in improved stem prices and incomes. We suggest that intervention program that will improve the purchasing power of the farmers should be targeted towards the smallholder cassava farmers to accelerate adoption of improved cassava varieties. Int. J. Agril. Res. Innov. Tech. 11(2): 42-51, Dec 2021

Flood Hazards and Farm Based Agricultural Production Risks Management Practices in Flood Prone Areas in Punjab, Pakistan

Climate induced disasters more specifically the floods have caused severe damages to agriculture sector in Pakistan. These climatic risks have constrained farming community to adopt numerous risk management strategies to overcoming such risks. This research work attempted to examine the association of risk management tools with farmer’s perception of risk, risk averse attitude and various socioeconomic factors. The study employed the sample data of 398 farmers from flood prone two districts of Punjab, Pakistan. To investigate the association of dependent and independent variables this study used the multivariate probit model. Results of the study illustrated as heavy rains and floods consider not significant source of risk for large farmers in the study area while for small farmer these indicated as high risks as most of small farmers were more risk averse. Estimates of multivariate probit model interpreted as age of farmer, heavy rains risk perception and landholding size were positively relationship with risk management tool of depletion of assets. Farmers education, off-farm income, age and risk averse attitude of farmer were positive whereas experience of farming were negatively linked with reduction of consumption. Furthermore, experience of farming, risk averse attitude, heavy rains and floods risk perception were positively association with diversification adoption. Flood prone farming community of the study area is more vulnerable to these climatic risks and also relying traditional strategies for risk management. There is need of some specific agriculture base measure such as crop insurance, extending formal credit and flood base measure as pre-flood warning system, flood rescue management and post flood rehabilitation to overcome these climatic risks.

Determinants of Market Outlet Choices by Smallholder Chickpea Farmers in Estie District Amhara Region, Ethiopia

In Ethiopia, chickpea is an important plus crop, particularly in Estie district. It is a source of food and provides cash income for majority of smallholder farmers. To commercialize chickpea producers, selecting an appropriate market channel is mandatory. However, selecting an appropriate market channel is not an easy task because there are different factors that affect market outlet choices in the district. Hence, this study aimed to identify factors that affecting chickpea market outlet choices. Both primary & secondary sources of data were used. A two-stage random sampling procedure was used and a total of 122 smallholder farmers were randomly and proportionally selected to collect primary data. Multivariate probit model was employed to identify factors affecting chickpea market outlet choices. The result shows that five major chickpea marketing channels were identified and among them wholesalers and retailers purchased about (61.84%) and (18.2%) respectively. The estimation result of multivariate probit model showed that the likelihood of sampled households to select collectors, consumers, retailers and wholesalers were 25.3%, 35.4%, 30.5% and 36%, respectively. The joint probability of success and failure to select all market outlets was 0.01537% and 13.4% respectively. It also indicated that sex of household, education status, family size, off-farm income, access to credit; lagged price and distance to market significantly affected the market channel choice decision of producers. Based on the findings, Government and concerned stakeholders need to focus more on enhancing accessibility of infrastructures facilities, strengthening credit access and improving yield through extension service to accelerate selecting appropriate market channel.

Perception to Adaptation of Climate Change in Nepal: An Empirical Analysis Using Multivariate Probit Model

This study assessed farmers’ perception of climate change, and estimated the determinants of, and evaluated the relationship among, adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, were found to be more influential compared to other factors. All four adaptation options were found to be complimentary to each other. Importantly, the intensity of the impact of dependent variables in different models, and for the available adaptation options, were found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

Determinants of Market Outlet Choices by Smallholder Chickpea Farmers in Estie District Amhara Region, Ethiopia

In Ethiopia, chickpea is an important plus crop, particularly in Estie district. It is a source of food and provides cash income for majority of smallholder farmers. To commercialize chickpea producers, selecting an appropriate market channel is mandatory. However, selecting an appropriate market channel is not an easy task because there are different factors that affect market outlet choices in the district. Hence, this study aimed to identify factors that affecting chickpea market outlet choices. Both primary & secondary sources of data were used. A two-stage random sampling procedure was used and a total of 122 smallholder farmers were randomly and proportionally selected to collect primary data. Multivariate probit model was employed to identify factors affecting chickpea market outlet choices. The result shows that five major chickpea marketing channels were identified and among them wholesalers and retailers purchased about (61.84%) and (18.2%) respectively. The estimation result of multivariate probit model showed that the likelihood of sampled households to select collectors, consumers, retailers and wholesalers were 25.3%, 35.4%, 30.5% and 36%, respectively. The joint probability of success and failure to select all market outlets was 0.01537% and 13.4% respectively. It also indicated that sex of household, education status, family size, off-farm income, access to credit; lagged price and distance to market significantly affected the market channel choice decision of producers. Based on the findings, Government and concerned stakeholders need to focus more on enhancing accessibility of infrastructures facilities, strengthening credit access and improving yield through extension service to accelerate selecting appropriate market channel.

Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model

Multi-label classification is the challenging task of predicting the presence and absence of multiple targets, involving representation learning and label correlation modeling. We propose a novel framework for multi-label classification, Multivariate Probit Variational AutoEncoder (MPVAE), that effectively learns latent embedding spaces as well as label correlations. MPVAE learns and aligns two probabilistic embedding spaces for labels and features respectively. The decoder of MPVAE takes in the samples from the embedding spaces and models the joint distribution of output targets under a Multivariate Probit model by learning a shared covariance matrix. We show that MPVAE outperforms the existing state-of-the-art methods on important computational sustainability applications as well as on other application domains, using public real-world datasets. MPVAE is further shown to remain robust under noisy settings. Lastly, we demonstrate the interpretability of the learned covariance by a case study on a bird observation dataset.

Determinants of Relevant Constraints Inhibiting Farmers’ Adoption of Climate Change Adaptation Strategies in South Africa

The adverse effects of climate change on agricultural productivity are on the increase. This study employed both descriptive statistics and the multivariate probit model to estimate factors constraining the adoption of climate change adaptation strategies among smallholder farmers in the study area. The empirical results of the multivariate probit model showed that a lack of knowledge of climate change constraints was influenced by smallholder farmers’ age, gender, off-farm activity, susceptibility and membership in farmer-based organizations. Thus, to improve the adaptive capacity of farmers, government and development partners should work together to improve the conditions under which farmers can gain access to climate change information and suitable agricultural credit as well as policy incentives aimed at lowering the stringent conditions of borrowing in the agricultural sector.