Growth and Instability in Livestock Population and Milk Production in South Gujarat and Gujarat

Dairying has been a longstanding tradition among rural households, playing a vital role in ensuring food security, generating income and creating employment opportunities especially for marginal and small farmers. India’s dairy industry has witnessed remarkable growth, largely due to initiatives like the Operation Flood project, which transformed the sector into a cooperative-led movement. As a result, India has become the world’s largest milk producer.
       
In the year 2022-23, the country produced 759.96 million tonnes of milk, with a per capita availability of 459.63 grams per day. This upward trajectory in milk production has been consistent over the years, with projected outputs of 199.1 MT in 2020, 210.5 MT in 2021, 221.9 MT in 2022, 233.3 MT in 2023 and 244.7 MT in 2024. A similar trend of increasing milk production in India was reported by Mishra et al., (2020), highlighting the sector’s steady expansion. This sustained growth is expected not only to strengthen the dairy sector itself but also to facilitate development in allied sectors of the economy.
       
This progress is strongly supported by dairy cooperatives, particularly in states such as Uttar Pradesh, Rajasthan andhra Pradesh, Gujarat and Punjab, which are among the top contributors. According to the Indian Council of Medical Research (ICMR), the recommended daily intake of milk for a healthy individual is 240 grams. Gujarat notably exceeds this recommendation, with a per capita milk availability of 670 grams per day, reflecting the state’s robust dairy infrastructure and widespread participation in milk production (Anonymous, 2021).
       
The state boasts 17 cooperative dairy milk unions and 25 private dairy plants, collecting 3.45 billion liters of milk from over 30 lakh producers associated with more than 15,000 primary milk cooperative societies. Milk production contributes 22 per cent to Gujarat’s agricultural GDP and is a crucial sector for supporting livelihoods. According to state census data, out of 102 lakh households in Gujarat, 43 lakh households are engaged in dairy and animal husbandry as a primary or secondary income source.
       
The South Gujarat region, known for its successful dairy and agriculture cooperatives, encompasses seven districts: Bharuch, The Dangs, Narmada, Navsari, Surat, Valsad and Tapi. In terms of milk production, Surat leads with 502.67 lakh kg, followed by Navsari with 357.15 lakh kg, Tapi with 331.52 lakh kg and Valsad with 279.95 lakh kg. The comparative view of the dairy animal population and milk production in South Gujarat, Gujarat and India for the year 2022-23 (Anonymous, 2023) is shown in Tables 1.1 and 1.2.




 
Research gap
 
The study highlights that India’s dairy growth is primarily driven by an increase in livestock numbers rather than yield improvements. However, there is a need to explore strategies for improving per-animal productivity through better breeding, feeding and management practices.

Methodology outlines the study area profile, the nature and sources of data collected and the analytical tools and techniques employed to achieve the study’s objectives. The selection of the study area mainly based on the highest milk production in the South Gujarat, four districts viz, Surat, Navsari, Valsad and Tapi were the significant contributors of milk production in the South Gujarat. Secondary data were used to study the stipulated objectives. Additionally, secondary data regarding livestock population and milk production were obtained from government reports issued by the Directorate of Animal Husbandry and animal census reports. These sources included the State Veterinary Department, State Statistical Abstract, District Cooperative Milk Producer’s Union Ltd. and respective milk producer’s societies. The secondary data of animal population and milk production of the local cow, crossbreed cow and buffalo spanned from the year 2000-2001 to 2022-2023. Based on the available data for goat and sheep populations data collected from the years 2012-2013 to 2022-2023.
 
Descriptive statistics
 
To examine the nature of time series data, statistical tools used were minimum, maximum, average, standard error. Selvin, (1998).
 
Parametric trends models

To get an overall movement of the time series data, trend equations were fitted. In this exercise, different functional forms like: linear, compound etc. were used for the purpose and linear form was found the best fit based on the highest value of coefficient of determination (R²). Selvin, (1998).
 
Compound annual growth rate
 
The growth rate in agriculture refers to the increase or improvement in agricultural productivity over a specific period of time. It is a crucial metric that measures the pace at which agricultural output, such as crop yields or livestock production, is expanding (Rajanbabu et al., 2022; Singh et al., 2015). The importance of growth rate in agriculture can be understood through several key aspects like food security and environmental sustainability. The livestock population and their milk production was investigated using tabular analysis and the Compound Annual Growth Rate (CAGR) of livestock population and milk production was estimated as follows: (Hasan and Khan, 2018)                

Where,
Y_t = The livestock population and milk production in t^th period.
t= Time variable (1,2,3……,n).
a= Constant    b = (1 + r)
r = Compound growth rate.
       
After log transformation and estimation of the above function as, Y_t = Ina + t Inb, compound growth rate was estimated as follows: (Dash et al., 2017; Dhakre and Sharma, 2010).

Student’t’ test was used to determine the significance of “b” of compound growth rate obtained for which the following formulation was employed,

 

Where,
b_i  = Regression co-efficient.
SE (b_i) = Standard error of the coefficient.
       
he calculated ‘t’ values, from equation (3), was compared with the table ‘t’ values and the significance was tested at 1 % and 5 % level of significance.
 
Instability index
 
Instability in agriculture refers to fluctuations and uncertainties in various factors that affect the agricultural sector, such as climate conditions, market prices, input costs and policy changes (Buragohain and Borah, 2022; Dhaka et al., 2019). While instability can pose challenges for farmers and the agricultural industry as a whole, it is also important to understand its significance. Instability is important for risk management, economic implications, environmental consideration and food security (Bhalla and Singh, 2009; Dudhat et al., 2021). In the current study, the Cuddy-Della Valle Index was employed to investigate the instability in livestock population and their milk production of local cows, crossbred cows and buffalo in South Gujarat and Gujarat. The index was calculated using the following formula: Cuddy, J. D. and Valle, P. D. (1978).
       
The coefficient of variation was computed by using following formula, Della Valle, (1979).

   
Where,
σ = Standard deviation.
X = Arithmetic mean.
       
As the CV (%) may overestimate the level of instability characterised by long term trends, the CDVI (%) would be used to de-trend and show the exact magnitude of instability. The specification of CDVI (%) to be used in the study.

Where,
R²= Adjusted R-squared.
P=Numbers of predictors.
N=Total sample size.

 
Where,
CV=Coefficient of Variation.
Adj.R²=Adjusted R-squared
       
The corresponding range and interpretation for the index was used given by Adhikari et al., (2024), Low instability: 0-15, Moderate instability: >15- Upto 30, High instability: Above 30.
 
Matrix of association between growth and instability
 
Based on variation in rates and instability indices the variable under consideration was classified four-fold-typology (Fig.1). As shown below, an analysis was done for the overall period and subsequent discussions were organized into categories from most desirable to not desirable.(Rao and Raju, 2005).


 
High growth/low instability (HG-LI) (Most desirable situation)
 
The variables whose growth rate is higher than the average but the instability is lower.
 
High growth/high instability (HG-HI) (Desirable situation)
 
The variables whose growth rate and instability are greater than the average.
 
Low growth/low instability (LG-LI) (Least desirable)
 
The variables with growth rates and instability below average.

Low growth/high instability (LG-HI) (Not desirable)
 
The variables with growth rate below average and instability above average.

Compound annual growth rate
 
The purpose of studying the Compound Growth Rate (CGR) of livestock variables was to determine the behaviour for capturing the inter-temporal dynamics of the particular variable. Here the compound growth rate of breed wise animal population and milk production of dairy animal for South Gujarat and Gujarat were studied for the period 2000-2001 to 2022-2023.
 
Spatio-temporal growth pattern of livestock population in South Gujarat and Gujarat
 
In this section the Compound Annual Growth Rate of the milch animal, In-milk animal and total animal population in South Gujarat and Gujarat was studied during the study period 2000-2001 to 2022-2023 and results were furnished in Table 1.     


       
The results from Table 1 showed that the per annum compound growth rate of overall total animal population was found positive and significant in South Gujarat (3.97%). In total animal population crossbred cow (23.60%) had the highest and significant Compound Annual Growth Rate followed by buffalo (2.82%) and sheep (1.37%), whereas goat and local cow shows the negative and significant Compound Annual Growth Rate (-7.01% and -3.53%, respectively) in the South Gujarat. This same pattern showed for the milch and In-milk animal population in the South Gujarat. In case of milch animal population crossbred cow has the highest Compound Annual Growth Rate (31.84%), followed by buffalo (1.68%) and local cow(-3.76%). Same followed by the In-milk animal population, highest in crossbred (22.63%), followed by buffalo (3.46%) and local cow (-3.48%).
       
For Gujarat, overall total animal population was found positive and significant at 1% level (7.37%). In total animal population crossbred cow (35.81%) has the highest and significant Compound Annual Growth Rate followed by Sheep (31.73%), buffalo (5.33%) and local cow (4.30%) in the Gujarat. This same pattern showed for the milch and In-milk animal population in the Gujarat. In case of milch animal population crossbred cow has the highest Compound Annual Growth Rate (35.19%), followed by buffalo (5.34%) and local cow (4.12%). Same followed by the In-milk animal population, highest in crossbred (36.25%), followed by buffalo (5.32%) and local cow (4.41%).
       
The above results showed that the animal population Compound Annual Growth Rate was found positive and significant for all milch, In-milk and total animal population for crossbred and buffalo population in South Gujarat and Gujarat except the local breed animal population in all categories of milch, In-milk and total animal population in South Gujarat (negative). The reasons for slow growth in indigenous stock were low milk yield and decreasing demand for draught animals. These results were in conformity findings of earlier studies (Rathore et al., 2019, Singh et al., 2020, Khalandar et al., 2022 and Mondal and Mishra, 2022). Despite abundant livestock wealth, low productivity persisted due to factors like dominance of low yielding breeds, improper management and disease control. This factors supported by government and stakeholders were deemed necessary.
 
Spatio-temporal growth pattern milk production in South Gujarat and Gujarat
       
In this section breed wise the Compound Annual Growth Rate of milk production of local cow, crossbred cow, buffalo and goat in South Gujarat and Gujarat was studied from the period 2000-2001 to 2022-2023 and results were furnished in Table 2.      

  
       
The results from Table 2 showed that the per annum compound growth rate of overall total animal milk production was found positive and significant in South Gujarat (12.45%). In animal milk production crossbred cow milk production (34.17%) has the highest and significant Compound Annual Growth Rate followed by goat (7.03%) and buffalo (5.93%). Whereas local cow breed showed the lowest and significant Compound Annual Growth Rate (3.21%) in the South Gujarat. This result was in conformity with the findings of earlier studies (Shah and Dave, 2010, Rathore et al., 2019, Singh et al., 2020 and Khalandar et al., 2022).  The reason for this was that the local cow productivity was low as compared to the crossbred cow but it has the higher fat content and the population of the local cow was significantly low in South Gujarat. In the case of crossbred cow, the increase in milk production is mainly attributed to the population effect than the yield effect over the study period.
       
For Gujarat, the Compound Annual Growth Rate for overall animal milk production was found positive and significant (13.31%). The highest Compound Annual Growth Rate was found in crossbred cow milk production (40.97%) followed by local cow (9.24%) and buffalo (9.00%) although, for goat milk production the Compound Annual Growth Rate was found low (4.77%). These results have similarity with the study Khalandar et al., (2022) and Kumar et al., (2023).
       
The above result showed that the compound annual growth of overall milk production for the local cow, crossbred, buffalo and goat was found positive and significant for both South Gujarat and Gujarat during the study period 2000-2001 to 2022-2023.
 
Instability analysis of livestock population and milk production of dairy animal in South Gujarat and Gujarat
 
Instability is one of the significant decision parameter in development dynamics and more so in the concept of livestock and their output (Rajanbabu et al., 2022).The study applied the Coefficient of Variation (CV) and Cuddy- Della Valle Index for calculating instability in livestock population and milk production. A CDV index was preferred over CV in order to provide clear direction about instability in the variable as well as examine the extent of livestock population and milk production risk. In addition, CV has some limitations in calculating instability of time series data, since it disregard trend and overestimates instability. Therefore, CDVI alone should be used when there was a significant trend. Otherwise, CV (%) alone can measure instability. When CDV index was high, there was high instability in production and vice versa.

 
Instability analysis of livestock population of dairy animal in South Gujarat and Gujarat
 
The results of instability analysis of livestock population of dairy animal through Cuddy- Della Valle Index method have been represented in Table 3. From the analysed results, it was observed that in the study period 2000-2001 to 2022-2023, the instability in total animal population was found the CDVI value 16.02 per cent in South Gujarat.  The highest instability was found for the crossbred cow population in the total animal population (48.53%) followed by sheep (19.62%) and goat (15.91%) population and lowest instability was found for local cow population (7.11%). The category wise total milch animal population was found with 26.00 per cent CDVI value. Milch crossbred cow was found highest instability with the CDVI value 96.02 per cent followed by milch buffalo (11.67%) and milch local cow (8.57%). Same pattern observed in the total In-milk animal population with CDVI value 5.29 per cent. In-milk crossbred cow was found highest instability with the CDVI value 19.67 per cent followed by in-milk local cow (9.86%) and in-milk buffalo (7.83%).


       
For Gujarat, the instability in total animal population was found with the CDVI value 2.12 per cent. The highest instability was found for the sheep (36.57%) population in the total animal population followed by crossbred cow (12.14%), local cow (6.93%) and goat population (5.22%). The category wise total milch animal population was found 2.69 per cent CDVI value. Milch crossbred cow was found highest instability with the CDVI value 12.19 per cent followed by milch local cow (7.28%) and milch buffalo (2.66%). Same pattern observed in the total In-milk animal population with CDVI value 1.49 per cent. In-milk crossbred cow was found highest instability with the CDVI vale 12.20 per cent followed by in-milk local cow (6.56%) and in-milk buffalo (1.93%).
       
The overall results suggest that South Gujarat has higher instability in milch animal, in-milk animal population and total animal population as compared to the Gujarat. The higher values of CDVI indicated the presence of high instability, which observed in South Gujarat which showed that South Gujarat has high variation as compared to the Gujarat in animal population. As observed above particularly in all animal population crossbred cow has found higher instability and lower instability presence in buffalo population.
 
Instability analysis of milk production in South Gujarat and Gujarat
 
The results of analysis in instability of breed wise milk production through Cuddy- Della Valle Index method have been represented in Table 4.


       
From the analysed results, it was observed that in study period 2000-2001 to 2022-2023, the instability in total milk production was found 5.17 per cent CDVI value in South Gujarat. The highest instability was found for the crossbred cow milk production (19.95%) followed by goat (13.80%) and local cow milk production (11.17%) although buffalo milk production has lowest instability (5.17%). Crossbred cow milk production has highest instability which showed the high variation as compared to the buffalo milk production with lower instability.     
       
For Gujarat, the instability in total milk production was found 2.23 per cent CDVI value. The highest instability was found for the crossbred cow milk production (25.56%) followed by goat (7.71%) and local cow milk production (6.74%). Buffalo milk production has 2.84 per cent instability. This same pattern showed in the South Gujarat that crossbred cow milk production has highest instability which showed the high variation as compared to the buffalo milk production with lower instability.
       
The overall results suggest that the South Gujarat has higher instability in total milk production as compared to the Gujarat. The higher values of CDVI indicated the presence of high instability, which observed in South Gujarat which showed that South Gujarat has high variation as compared to the Gujarat in milk production. As observed above particularly in all animal milk production crossbred cow milk production has found higher instability and lower instability presence in buffalo. This result has similarity with the previous study (Choudhry, 2021).
 
Trade-off between growth and instability of livestock population and milk production

Matrix association or trade-off between growth and instability was shown in Table 5 and Table 6 in terms of livestock population and milk production in South Gujarat and Gujarat, respectively.




 
Trade-off between growth and instability of livestock population and milk production in South Gujarat
 
High growth-low instability (Most desirable situation)
 
In terms of livestock population buffalo 2.82 per cent per annual and low instability fall under this category and milk production goat, local cow and buffalo fall under this category with 7.03, 3.21 and 7.03 per cent per annum growth rate, respectively and low instability.
 
High growth-high instability (Desirable situation)
 
 In terms of livestock population crossbred cow with 23.60 per cent per annum growth rate and high instability (48.53%) and milk production crossbred cow (high growth and medium instability) fall under this category.
 
Low growth-low instability (Least desirable)
 
In terms of livestock population, local cow fall under this category, while in terms of milk production no one comes under this category.
 
Low growth-high instability (Not desirable)
 
In terms of livestock population, sheep and goat fall under this category, while in terms of milk production no one comes under this category.
 
Trade-off between growth and instability of livestock population and milk production in Gujarat
 
High growth-low instability (Most desirable situation)
 
In terms of livestock population crossbreed cow and buffalo with 35.81 and 5.33 per cent per annum growth rate and low instability and in milk production local cow fall under this category with 9.24 per cent per annum growth rate and low instability.
 
High growth-high instability (Desirable situation)
 
In terms of livestock population sheep fall under this category, while in milk production crossbred cow (high growth and medium instability) fall under this category.
 
Low growth-low instability (Least desirable)
 
In terms of livestock population, goat and local cow fall under this category, while in terms of milk production buffalo and goat comes under this category.
 
Low growth-high instability (Not desirable)
 
In terms of livestock population and milk production, no one comes under this category.
       
This study primarily focuses on the South Gujarat and Gujarat regions; therefore, a comparison between Gujarat and India is not feasible. Additionally, the study emphasizes local cows, crossbred cows and buffaloes, making it difficult to provide detailed information on goats and sheep due to the unavailability of data.

Gujarat is a leader in livestock health and dairy development, with a strong three-tier cooperative model. South Gujarat was studied due to its high milk production. Crossbreed cows and buffaloes showed positive growth in both livestock population and milk yield, while local cows and goats declined in South Gujarat. The Compound Annual Growth Rate (CAGR) for animal population and milk production was positive and significant, led by crossbreed cows. Gujarat showed lower instability in livestock and milk production than South Gujarat. To boost productivity, targeted efforts are needed to stabilize populations and promote high-yielding breeds. Buffaloes in South Gujarat and crossbreed cows in Gujarat showed the best growth-stability balance.

I express my heartfelt gratitude to my Major Guide, Dr. Narendra Singh, whose unwavering support, insightful guidance and fatherly presence have been invaluable throughout my study. I also extend my sincere appreciation Yogesh Garde sir, Alpesh Leua sir and Umang for their unwavering encouragement, moral support and for fostering a positive and collaborative work environment. Finally, I am deeply thankful to the Government of Gujarat for providing the Shodh Scholarship (Scheme for Developing High-Quality Research) during my research period.
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
All animal procedures for experiments were approved by the Committee of Experimental Animal care and handling techniques were approved by the University of Animal Care Committee.

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.