Study of saving and investment pattern on sample farms households

The saving and investment pattern of different forms sample group was studied during 2014-16 and it was observed that large farm holders were able to save higher income than small farmers while lowest income group had negative savings. In respect of investment on different fixed assets, irrigation was on first priority, followed by purchase of milch animals, farms buildings and investment in land and its improvement. Investment on working capital amongst different cash inputs, hired human labourer accounted highest share (29.44 per cent), followed by manure & fertilizers (22.33 per cent), hired power tractor (16.96 per cent), irrigation (13.61 per cent) and seeds (13.50 per cent) to total cash inputs. Marginal farmers could not invest for nonfarm physical capital because of no savings with them. Small and large farmers groups invested in all the items in which it was highest in working capital (61.28 to 61.84 per cent), followed by investment in fixed capital (14.41 to 16.84 per cent), financial capital (12-14 per cent) and non-farm capital (7-12 per cent). The highest investment was made on working capital (69.02 per cent) by sample farmers. Current income was found to be the main source of finance in all income groups which accounted for 49.70 to 94.79 per cent share of the total investment followed by savings which shared for 40.10 to 49.12 per cent in total investment.

Pig Genomics and Genetics

The pig (Sus scrofa) is the most popular large farm animal in the world [...]

A Study on Socio-economic Condition of Sheep Rearers of District Uttarkashi, Uttarakhand

Background: Uttarakhand is a hilly state and a very little land is under cultivation but animal husbandry appears to be a good source of livelihood for farmers and sheep rearing is one of the major components of animal husbandry in Uttarakhand which help farmers to run their life. Sheep rearing is very much prevailing in hilly regions of the State. Aim: To find the socio-economic condition of the rearers. Methodology: A study was conducted in Uttarkashi district of Uttarakhand. A total of 80 rearers were selected randomly from the Bhatwari block of Uttarkashi, Uttarakhand and a pre structured questionnaire was used to collect data from the rearers. Respondents were classified into three categories on the basis of number of sheep viz. small (having less than 50 sheep), medium (between 50-100 sheep), and large (more than 100 sheep). Results: Study showed that small rearers have 46.86 average numbers of sheep whereas medium size rearers have 73.88 and large rearers have 258.52 average numbers of sheep. Out of which number of Ram were lowest. Most of the rearers were from 35-50 years of age group. 48.74 % of rearers had completed their primary education and 14.11% of rearers were illiterate. Majority of rearers (i.e., 68.75) were engaged with two occupations. On an average 57.48 % of rearers were OBCs (Other backward class) and 29.99 % were from tribal community(i.e.,Bhotiya). The average income of small, medium and large farm group is ₹53,440, ₹89,627 ₹1,96,802 respectively. Conclusion: It was concluded that there is need to eradicate the lack of awareness about the new technologies and educate the rearers about more efficient way of sheep rearing. With this women participation and youth should also be encouraged to involve in sheep rearing.

Ownership Changes Through the Eyes of Workers on Large Farms

The paper offers an assessment of ownership changes on a large farm from the point of view of the employees. Such farms, some of them operating as companies, are important workplaces for the rural population today. The paper presents the results of a qualitative research (ten free-form interviews) involving people who managed such a farm located in this case in the village of Pągów (Opolskie province, Namysłów county), as well as the farm’s employees. The aim of the study was: 1) to reconstruct the employees’ work biographies, 2) to evaluate the extent to which they were active participants of the changes or objects of those changes when ownership transformations were carried out without their knowledge, despite affecting them directly, 3) to determine what impact the ownership changes had on the employees’ work situation and how they were treated by the owners and managerial staff.

An economic analysis of production and marketing of cauliflower in Bilaspur district of Chhattisgarh State

The study was conducted in Bilaspur district of Chhattisgarh in the year 2014-15 to analyse the production and marketing of cauliflower with a sample size of 154 farmers and 30 intermediaries from 4 blocks of the district. The study found on an average cost of cultivation of cauliflower Rs. 50573.84 per ha. The lowest cost of cultivation was observed at small farm as Rs. 48964.52 per ha while highest at large farm as Rs. 52104.68 per ha. Hired human labour cost maximum share as 20.18 per cent to total cost of cultivation. Cost A1 was observed Rs. 21653.84 per ha. The net return on Cost A1 was Rs. 1169.06 per q and Rs. 154100.06 per ha. The overall B:C ratio was estimated 3.48 for cauliflower production, minimum at marginal farm i.e. 3.26 and maximum at medium farm as 3.75. There were two marketing channels identified Channel I: Producer to Consumer and Channel II: Producer to Commission agents/retailers to consumer. The channel I was found most efficient as 39.85 per cent as compare to channel II i.e. 14.52 per cent. Monkey’s nuisance was appeared as most common problem in study area.

Level and Pattern of Consumption Expenditure of Rural Households among Different Regions of Punjab

The present study, dealing with the inequality in consumption of the rural households across the different regions, is based upon the primary data of the Punjab state. The analysis showed that Malwa excelled other two regions in the per capita consumption. The highest average propensity to consume was observed for Doaba, and it was the lowest for Malwa. All the rural households except large farm of all the three regions and medium farm households of Malwa and Majha were in deficit. Considering all households together, the inequality of household consumption expenditure was relatively high in all three regions, with the same being highest in Majha, followed by Malwa and Doaba. The concentration of consumption expenditure among the land-owning households was greater than the landless households.

Pattern and Sources of Farm Investment in Agriculture of West Bengal: A Comparative Analysis Between Small and Large Farm

The analysis of the farm level investment is a complex problem, being very useful in the planning as well as in policy making process. This paper is the first to attempt a systematic comparison of investment between small and large farms in West Bengal. There has been a growing interest in recent years in the pattern of the capital formation, and sources of farm investment between different categories of farmer. The paper identifies the pattern of investment on different farm assets viz., purchase of land and land improvement, livestock, machinery, farm building, irrigation equipments and perennial crops. Data for the study was generated through a sample survey of 90 farm households from two districts in West Bengal. The rate of capital formation increased as the farm size increased. Purchase of irrigation appliances and land were the major item of capital formation in the farms of both small and large categories. Large farms invested highest on irrigation implements (` 66,467) and least on perennial crops (` 10,700). However, magnitude of investment was different across the different categories of farm. The per hectare investment on different farm capital assets found higher in case of small farms (` 2,77,559 per ha) than large farms (` 2,77,010 per ha). On aggregate, share of investment on different items was more than three times higher than investment made by small farmers in the last twelve month on their farms.

Leaf Disease Detection Using AI

Plants play a significant role in everyone's life. They provide us essential elements like food, oxygen, and shelter, so plants must be supervised and nurtured properly. During cultivation, crops are prone to different kinds of diseases which can severely damage the whole yield leading to financial losses for farmers. In last 10 years, researchers have used different machine learning techniques to detect the disease on plants, but either the methods were not efficient enough to be implemented or were not able to cover the wide area in which plant diseases can be detected. So, the author has introduced a method which is efficient enough to easily detect plant disease and can be implemented in large fields. The author has used a combination of CNN and k-means clustering algorithms. By using this method, crops disease is detected by analyzing the leaves, which notifies users for action in the initial stage. Thus, the proposed method prevents whole crops from getting damaged and saves time and energy of farmers as disease will be identified way before a human eye can detect it on a large farm.

Determining the Factors Affecting Investment in Punjab Agriculture

Investment is the expenditure incurred for real capital formation. A sample of 150 farmers was taken with 23 (15.3%), 28 (18.7%), 46 (30.7%), 43 (28.67%) and 10 (6.7%) farmers selected from marginal, small, semi-medium, medium and large farm size categories respectively in proportion to the share of respective category in total farmers in Punjab. Income, consumption, funds available post-consumption and investment level of the respondent farmers was worked out to find the factors that affect farm investment. Information related to education level, family type, cropping pattern and credit availability was also collected to see if they affect the level of investment. Income, consumption and funds available post-consumption were higher for larger farm households. The level of investment was higher on large farms but the investment per hectare was highest on marginal farms. The availability of credit was more on larger farms but per cent share of credit in investment decreased as the farm size increased as large farmers were using owned funds extensively. The regression analysis revealed that the size of the operational holdings, saving and the credit availability showed positive relation with the level of investment while the education level, family type and cropping intensity were non-significant.