As our country supports around 33% of total cattle inventory of the world in 2023 and ranks No-one in buffalo population in the world India has come out to be a hub for dairying activity as profession and source employment very extensively Dairying of course is standing as an industry in the present social-texture cooperative bodies and corporate body have surfaced and flourished over here for organized dairying. The net work of Corporative societies all over the country is the back bone of dairy industry and thus India has come out as the largest milk producers and consumers throughout the world. Indian dairy sector ofcourse has under gone massive changes after white revolution because of having tremendous potential, Dairy of farming is ancillary to agriculture growth and has registered a very major rule in uplifting the socio-economic status of rural household or investors. As a result the milk production has grown at a Compound annual rate of 6.2 to reach 209.96 million tonnes in 2020-21 from 146.31 million tonner 2014-15. The all India percapita availability of milk was reported as 444 gm per day on 2021-22. All these feathers in our Cap were studded due to dairy cooperative only in the shape of providing basic dairy services such as supply of Cattle feed, fodder, seeds, animal health services, artificial insemination, vaccination etc by professionally qualified managers. This socio-economic status of the farmers actually affects dairying management and breed selection etc. High milk yield less expenditure of feed, breed suitable for an area, availability of government supported.

Commodity facilities are directly related to the viability of any unit In the above light this study was conducted and inferences were drawn after plotting the figure sector wise, species wise, season-wise and category-wise so that the inferences have universal acceptance as well as applicability.

Resembling studies- Mandi Kalyan et.al (2022) The study Concluded that farmers participation in Cooperative dairying has a  positive and statistically significant influence on socio-economics variable Members differed significantly from non-members in terms outcome variables, the mean difference value explained that the socio-economic conditions of members was better than non-members. The descriptive statistics for out come and explanatory variables as per the table given below.

The data present in above table showed that member group reaped higher milk yield as compared to non-member. This was due to cooperative member reared large herd sizes of milch animal comprising of high yielding crossbred cattle and buffalo.

Sharma Hemant et.al (2020)-The study confirmed that operational holding size of members households was 5.19 hect. as compared to non-member holding size being 4.17 hect.

Dubey L.R. et.al. (2014) - The study was performed in two blocks champawat district of Uttarakhand state to compare the socio economies profile of members and non members. The findings were that average family size in case of member was 6.93 while in case of non members, it was 6.76. Education level Coefficient was registered as 5.60 in case of members while 4.76 in case of non-members. Average size milch animals was 1.16 in case of members while 1.03 in case of non member it was also observed that non-members do not go for crossbred Cows and buffaloes species instead they stick to Deshi cow breed only. Average milk yield in litres per  annum was registered as 2481.33 litres in case of members while a meagre 1776.67 only in case of non member The inference drawn was that the awareness about the benefits from becoming members should be increased at large.

Niraula (2003) has also inferred that socio-economic impacts of dairy cooperatives is significantly positive, Cooperatives have ofcource rendered the farmers more social and this changes them culturally as with good housing, hygienic toilets, bio plants. TV. Education etc.

Dhanapala (1988). The study inferred that dairy cooperatives have great importance as they play a useful sole in promoting rural development especially they can facilitate the development of rural economics and thus it upgrade the standard of living.

Khan Nizamuddin (2014) - The study concluded that the importance of cooperatives due to fair returns and largest shares of traction through cooperative units. Another advantages that dairy cooperatives have emerged as a source of employment generation, efficient milk marketing and socio-economic development of dairy farmers so revalent polices and measures should be under taken to ensure efficient milk marketing better semuneration and sustainable socio-economic development of entrepreneur.

Priscill Laishram and chauhan A.K. (2019) The study inferred that About 11 percent of heads of household amongst members cooperatives were illiterate as compared to 15% amongst non-member co-operatives. A majority of household from members cooperative (32.50%) and non member Cooperative (27.50%) had attained middle level schooling. The average land holding size was found higher in case of cooperative member (0.66 acres) compared to that of non-cooperative member Another findings shows that ratio of crossbred to total milch cow’s was higher for member cooperative (0.691) as compared to that of non member respondents (0.361) with significant difference.

The data so collected was bifurcate on the basis of PCDF and Non PCDF sectors and different categories were assigned on the basis of size of land holding  as portable being given here under.

The sample was pre determined for 120 household from PCDF sector and 120 households from non PCDF sectors for the analysis a seasonal impact, the data were collected thrice in all the three seasons namely from March to June (summer), July to October (rainy season), and November to February (winter season) standard Adults  Units (SAU'S) were calculated as per the scale being mentioned here under. (Singh.K. 1984)

Buffalo in milk = 1 unit

Buffalo dry =0.4 unit

Local cow in milk = 0.7 unit

Local cow dry = 0.3 unit

Crossbred cow in milk = 1.4 unit

Crossbred Cow dry = 1.0 unit

Heifer = 0.5 unit

Young stock = 0.2 unit

 (Male & Female)

Draught dairy animal = 0.5 Unit

The weight assigned for the conversion of female labour and child labour into main equivalent were as under.

2 Males = 3 Females

1 Male = 1.5 Female

I male = 2 children

This study was conducted to analysis socio-economic profile of the households resorting to dairying under PCDF and Non PCDF sectors and important inferences were drawn regarding socio-economic texture of the Covered household on the basis of under mentioned broader heads.

2.     Family size and its composition.

3.     Educational status.

4.     Composition of herd strength.

5.     Species wise  average number of animal per household.

6.     Proportion of animals in milk as compared to milch animal.

7.     Average milk yield per milch/milking animal.

Figure were collected under above mentioned heads in respect of both the sectors just to analysis impact of cooperative activities and community

facilities over unorganized i.e, non-cooperative members The findings were eye opener as under.

Size of operation holdings

Land owners respondents were categorized in four categories as per the standards fixed by NCA (1976) Average land holding size sectors wise was found as depicted in the following table-1 enclosed.

We observed that the average size of operational land-holding in both the sectors was small farmers 0.556 hecture/0.537hect, marginal farmers 1.667 hect/1.541hec, Medium farmers 3.113 hect 2.529 hect, Large farmers 5.231hect/5.180hect for PCDF and Non PCDF sectors respectively. Overall average for all the households covered was 1.749 hect. in case of PCDF while 1.650 in case of Non-PCDF sectors.

The analysis proved that size of average holding under PCDF scoter were bigger than the average size under non-PCDF sectors. Thus the analysis revealed that the bigger the holding the higher is the preference to opt PCDF sectors.

1. Family she and its composition - Dairy enterprise being labour Intensive the size of  any family and its composition reflects a lot over employment perspective and self composition and market surplus etc. Collecting various data and analysing the same multifacetedly it came out as per enclosed table No-2. That over family size in case of P.C.D.F sector respondent was 6.90 members and corresponding figures for Non-PCDF sector was 6.69 members The composition of male & female members was recorded 3.75 males and 3.15 female, and 3.69 males and 3.00 females on PCDF sectors and non PCDF sector respectively. The inference drawn signifies equal participation of female members in both the sectors. It was also observed that youth participation in case of PCDF sector was slightly higher as compared to non PCDF sectors Average family in the analysis came out to be bigger in case of large and medium farmers in the case of both the sectors signifies that more than one set of parents and children are Jointly running a single enterprise in both the sectors. This also proves that the larger is holding the larger is the work force and there potentiality of being engrossed in self employments is rendered very high.

2. Education Status - Analysing the data collected in respect of the educational status of the head of the sample households the results were very surprising as reflected in table No-3 being enclosed. To our utter surprise only 37.50% family heads were found illiterate, in PCDF households and the percentage was 61.67% in non PCDF household. Examination under the categories of primary middle, high school, Intermediate, graduate and above graduate categories revealed that in all the categories educational status was drastically higher in PCDF sectors. This clearly signifies that with the advancement of education the inclination towards adopting PCDF sectors increases as educated heads of the households are prone to appreciate  the advantages or supremacy of PCDF sectors over non PCDF sectors.

3. Composition of the herd strength per household is terms of SAU’s with seasonal variation- (Table No-4) Under this segment of this study the basic data was analysed in respect of category wise holding of the land during different seasons in both the sectors. The inference drawn was that all categories shows as a rising trend from summer to winter in both the sectors and average holding was found higher in case of PCDF sectors other than the non-PCDF sectors. Micro analysis reflected that in PCDF sector the milch stock average for all the category vis-à-vis SAU’s for total stock figures were 2.34/3.00 numbers in summer 2.54/3.29 in rainy session and further jumped to 2.63/3.45  winter.  In non-PCDF sectors the figures were 2.17/2.85, 2.28/3.02 and 2.35/3.18 respectively. Thus the table signifies  positive trend  horizontally and vertically. This also proves that winter season was most health some for all the animals. ofcource SAU’s conversion reflectd in the table in question is of utmost  importance for the calculations of labour requirement etc. and the conservations facilitate comparison also.

4. Species-wire average number of animal per household – During  the study analysis in respect of specie-wise average number of animals per household was also made as reflected in enclose table No-5 In Case of PCDF sectors the total number of animals per household for buffaloes, local cow's and crossbred Cow's. was 4.44, 0.75 and 0.59 respectively, Under non-PCDF sectors the corresponding figures were 4.20, 1.13 and 0.33. Category-wise trend reflected the same features in both the sectors with the inference that holding size advanced with the advancement of category. It was also found out that in case of the species of local cows, non- PCDF sectors prefers this species than P.CDF sector. The Phenomenon may be attributed to low yield and high maintenance requirement of this species. It was also shown-up that milch stock In comparison to total stock was one-third approximately in all the categories and in both the sectors implying that respondents had to support twice the other stocks be it young stock or draught animals in comparison to milch stock. Another inference which we were able to draw through the Comparison of both the sectors was that investors having crossbred cow's prefers to join cooperative sector Analysing the over all data it was established that buffaloes top the tally being 4.44/4.20 per household on an average in both the sector Local cow's are just 0.75/1.13 and crossbred cow’s are 0.59/0.33. Thus it is crystal clear that dairying is more or less based on buffaloes and those investors who are promoting crossbred species PCDF sectors.

5. Proportion of animals in milk as compared to total milch animals - Analysis of proportion for animals in milk as compared to total milch animals was also conducted on the basis of data collected so that viability of any unit may be calculated more precisely and with clear perspective of this features amongst the animals of all the species. Every one known that milk production solely depends upon the proportion of milking animals out of the total stock or out of the milch animals as a whole. Every producer’s try that this proportion to be as high as possible. In other words the lesser in percentage of the dry animals the more is the proportion. enclosed table-6 was prepared by plotting relative data of milking animals in respect of species, season-wise, category-use and sector-wise. As per the figures plotted in case of buffaloes in PCDF sector over all percentage was recorded 82.31 percent, the trend revealed was maximum in winter followed by rainy season and the least in summer seasons. For local cow of this sector, the percentage in question was 83.78 percent and for crossbred cows was 87.50 percent.

As far as non-PCDF sectors was concerned figures of all the three species were 77.27%, 77.67% and 88.89% respectively for all the season put together. Interspecies comparison reflected that milking proportional is the lowest for the species of local cow's generally. The maximum proportion credit goes to crossbred cows as far some categories there proportion is 100% at certain points of time. This such as unique characteristics of crossbred cow’s species that invites attention and accolades.

6.  Average milk yield per milch/milking animal - As milch animal categories can be further be segmented in milking and dry animals the analysis on the features was also conducted species-wise, category-wise and season-wise and season-wise through plotting the data in table-7 to 8 being enclosed. Under PCDF sectors overall yield in case buffaloes was recorded 5.82 litre per milch animal per day. The corresponding figures for non-cooperative sector was recorded 4.97 litre only showing clearly that PCDF sectors fetches better yield. Seasonal impact analysis revealed that the yield was lowest during the summer season followed by rainy season and winter seasons. Both the sectors as well as category-wise figures generally confirm the same trend in respect of seasonal impacts. For the species of local cows overall averages for PCDF sectors and non-PCDF sectors were 3.36 litre and 3.51 litre respectively. This signifies that for the species of local cow's in PCDF sectors was higher. The features recorded in all the categories except category of medium farmers as far as seasonal impact is concerned the lowest yield was during the summer seasons while the highest was during the rainy for all categories  under PCDF sectors. In case of non-PCDF sectors maximum yield reflected during the rainy season in respect of four categories but marginal farmers came out as an exception the maximum yield in these case was registered during the winter seasons.

Over all figures for both the sector conformed that average yield trend to rise with the size of land holding pattern. The third part of the table is in respect of Crossbred cow’s  the figures for which were registered 9.23 litre per milch animal per day under cooperative sectors while corresponding figure  for non-cooperative sectors was registered 7.54 litre.

The seasonal trend observed for this species were that the yield per milch animals per day was maximum during the winter season under both the sectors, and all the categories. Another table-8 as enclosed  was prepared for calculating yield per day of milking animals in respect of all the three species for all the five categories and for all the three seasons The figures are naturally higher as compared to figures for milch animals as the milch animals stock comprises of milking as well as dry animals. Be it any milch animal under any species it can never be permanently wet and dry because of calving and lactation cycle. Having a looks at the fable it was found that figures for all the three species in respect of both the sectors were 7.07 litre/6.43 litre, 4.01 litre/4.55litre and 11.21litre/9.89litre for PCDF and non-PCDF sectors respectively. Seasonal trend are same as discussed in respect of miich animals Analysis of both the table reveled that reflection of dry animals came out in the form of reduction of yield per milch animal as compared to milking animals.

After the analyses on the broader beads of size of operational holdings, family size and its composition, Educational status, composition of herd strength, species-wise average livestock, proportion of animals in milk as compared to the milch animals. We conclude that operational holdings were bigger under PCDF sector while family size dictates for performing PCDF sector in comparison to non- PCDF sectors. Educational status an analysed plays a very important role in favourable opinion forming for PCDF sectors. Analysis of composition of herd strength has revealed that bigger the category bigger is the herd size. Another features find out was that in case of the species of local cow’s non- PCDF sector was preferred and the yield of local cow’s was also registered better under non-PCDF sectors.

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