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Sugarcane is an important cash crop that grows in different agro-climatic zones: tropical and subtropical regions in India. It is the second-largest growing non-food crop in Tamil Nadu. Sugarcane mills generate waste at different stages of processing, which are bagassee, pressmud and wastewater. Managing and hand gripping of these wastes have been challenging tasks for the sugarcane industry. Wastewater generated by the sugarcane industry is rich in organic material such as carbohydrates and proteins, which enhance crop productivity. The present study aims to understand the farmers’ perceptions about the usage of sugarcane industry wastewater and measure the technical efficiency of the usage while also identifying the key determinants of sugarcane farming households. The primary survey for this study was conducted with 99 sugarcane farmers of Cuddalore district during January and February 2017. A semi-structured questionnaire was designed and pre-tested before final administration in the field. Out of 10 blocks in the district, 2 were selected. Within these blocks, six villages were chosen based on the extent of wastewater use in agricultural fields. Results showed that the farmers were not aware of the wastewater quality, and they believed it increased the productivity of sugarcane in the selected study location. For the land size, fertilisers are positively impacting the farm output and the price of sugarcane, but labour is negatively impacted. Results yield that the age and class of the respondents also have a direct relationship with the technical efficiency. JEL: Q12, Q25, Q53

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Background/Objectives: To prevent leakages and to efficiently roll out development programs, it is important that policy-makers and researchers are able to identify poor households that need intervention. Such identification will aid in adopting a targeted approach for poverty reduction strategies and improvement of livelihoods. Methods/Statistical analysis: The present study conducted amongst 3845 farm households in three agro-biodiversity hotspot regions in India, uses non-money metrics method to measure household economic status. Principal component analysis is used to build an asset index score of each household and determine the economic grouping based on caste categories. Findings: The results show a high level of inter-regional differentiation among the household economic status and intra-sub caste groups. The overall economic status reveals that Meenangadi falls in the 'rich/richest' group compared to the Kolli Hills in the 'middle' group and Koraput in the 'poorest' group. Our results are also important for household classification based on the social stratification within a regional context. Hence, it is reasonable to state that the asset based method is relevant for fine tuning identification of marginalized communities, notably in the deprivation hotspots, paving the path for their inclusive growth. Novelty/Applications: The present study attempts not only to identify economic status of rural households in different states of India, but also looked at the economic status of different castes, particularly at scheduled tribe groups that are dominant in the study area.