Potential of Livestock Production Systems: Explaining Employability and Milk Productivity Through Multivariate Typology

Abstract

A study was conducted in four different agro-climatic zones of Maharashtra state in India. The typology was developed with an aim to identify livestock production system, employment generation, and milk productivity oflivestock production system. Multivariate statistical technique, i.e. Cluster analysis (CA) was used to classify groupsof farm households with similar farm characteristics into four homogenous clusters, viz. households possessingsmall landholding, a larger high yielding dairy stock with small goat flock size (37.5%); small landholding with asmall stock of high yielding dairy animal and small goat flock size (39%); large landholding with large high yieldingdairy stock and small flock size (13.5%); small landholding with small high yielding dairy stock and large flock size(10%). It was observed that 47.5% of the respondents had dairy and 31.3% had a goat production system. The totalman-days generated for family labour were high (165.87) for cluster 2 households while, for hired labour, man-daysgenerated were high for cluster 4 households. Milk yield index was significantly high for cluster 3 and cluster 1households. Spearman correlation revealed that independent variables, viz. total SAU, flock size, income from dairyand goat production system positively correlated with milk productivity, employment generation (man-days) andgross annual income. Multiple regression analysis revealed that the integration of dairy and goat farming along with technology adoption significantly influenced the employment generation of small landholders.

Multivariate Typology of Osmanabadi Goat Farming in its Home Tract: A Cluster Analysis

“…Average annual employment generation in semi-intensive goat-keeping households (C2) was significantly higher than the households with small flock under extensive system and small landholding (C3), except for extensive goat-keeping households with large flock and large landholding (C1). Pathade et al, (2022) found a positive correlation between landholding, flock size and technology adoption with employment generation. Most goat-keeping households across all clusters used a medium extent of scientific practices.…”

“…Semi-intensive goat-keeping households (C2) were significantly higher in their use of hired labourers in goat farming than extensive goat-keeping households in C1 and C3. Pathade et al, (2022) found that the hired labours were mostly utilized by the households with small landholding, small dairy herd and large flock. Extensive goat-keeping households were primarily depended on family labours.…”

Combining Novel Integration and the DEA Technique to Compute Dredging Productivity

“…Several computations with an efficiency equal to 1 can be used to solve DEA efficiently. Some scholars used the multiple regression (ML) method to adopt farming techniques that significantly impact the integration of dairy cows and goats and create smallholder employment [21]. This study proposes an integrated and novel DEA construction productivity calculation method.…”