Influence Milk Production Research Articles

Análisis de la producción de leche bovina y su impacto económico en la organización agropecuaria Tucayta del cantón Cañar”

This study analyzed bovine milk production and its economic impact on the Tucayta agricultural organization in the Cañar canton, aiming to identify factors influencing milk production and develop improvement strategies. A descriptive quantitative approach was adopted, collecting data from 200 members across 15 communities through surveys focused on demographics, management of agricultural production units (UPA), infrastructure, and production economics. The results revealed a strong reliance on family labor and a generally basic educational level among producers, which may limit the sector's modernization and expansion. Dairy farming emerged as the main source of income for most UPAs, highlighting the importance of diversifying into meat production. While the infrastructure for water management was adequate, significant deficiencies were found in housing and mechanization. Production costs were high, dominated by expenses on feed and animal health, with a notable lack of soil analysis. Investments in education and technology are recommended to improve productivity and efficiency. The increase in milk prices in 2023 suggests a market recovery, although significant challenges remain for the long-term sustainability of the sector in the region.

Analysis of factors influencing cow’s milk production in Suitable Environment of Kampung Susu Lawu, Magetan Regency, East Java

Abstract This study will examine the variables that impact milk output from dairy cows in Kampung Susu Lawu. This study was conducted on a community dairy farm in the suitable environment of Plaosan subdistrict, Magetan regency, East Java Province. Data was collected using the purposive sampling approach. Multiple regression was analyzed to identify the parameters influencing milk output in dairy cows. The study findings indicate that the multiple linear regression model is Y = 3.160 + 0.001 X1-0.767 X2 + 0.120 X3-1.164. The regression analysis shows that the R2 coefficient value is 0.62, meaning that the independent variables forage, concentrate feed, land area, number of workers and number of family livestock influence milk production by 62% while 48% by outer variables. The findings of the F test show that the variables forage, concentrate feed, land area, labor, and number of animals simultaneously influence the milk production of farmers. The t test shows that forage, concentrate feed, land area and labor do not significantly influence the factors that influence milk production in dairy cows. The conclusion of this research is that factors that can influence milk production are the number of dairy cows.

Leptin on the apical surface inhibits casein production and STAT5 phosphorylation in mammary epithelial cells

Leptin is a peptide hormone present in both the blood and milk. A close relationship between leptin and milk production in lactating mammary glands has been previously reported. However, how leptin influences milk production in lactating mammary glands remains unclear. Also, whether leptin in milk or blood influences mammary epithelial cells (MECs) during lactation needs further investigation. This study investigated the effects of leptin on mouse MECs using a culture model in which MECs produced milk components and formed less permeable tight junctions. Our results showed that β-casein production in MEC was inhibited by leptin in a concentration-dependent manner. Leptin also inactivated the signal transducer and activator of transcription 5 (STAT5), a transcription factor that facilitates milk production in MECs. Leptin treatment induced the activation of p38 and c-Jun N-terminal kinase (JNK) in MEC before STAT5 inactivation, and anisomycin, an activator of p38 and JNK, induced the inactivation of STAT5. Furthermore, leptin exposure on the apical surface of MECs inhibited β-casein production and inactivated STAT5. However, leptin exposure on the basolateral surface hardly caused these effects. These findings suggested that milk leptin, but not plasma leptin, inhibited milk production in MECs.

Codon Bias of the DDR1 Gene and Transcription Factor EHF in Multiple Species.

Milk production is an essential economic trait in cattle, and understanding the genetic regulation of this trait can enhance breeding strategies. The discoidin domain receptor 1 (DDR1) gene has been identified as a key candidate gene that influences milk production, and ETS homologous factor (EHF) is recognized as a critical transcription factor that regulates DDR1 expression. Codon usage bias, which affects gene expression and protein function, has not been fully explored in cattle. This study aims to examine the codon usage bias of DDR1 and EHF transcription factors to understand their roles in dairy production traits. Data from 24 species revealed that both DDR1 and EHF predominantly used G/C-ending codons, with the GC3 content averaging 75.49% for DDR1 and 61.72% for EHF. Synonymous codon usage analysis identified high-frequency codons for both DDR1 and EHF, with 17 codons common to both genes. Correlation analysis indicated a negative relationship between the effective number of codons and codon adaptation index for both DDR1 and EHF. Phylogenetic and clustering analyses revealed similar codon usage patterns among closely related species. These findings suggest that EHF plays a crucial role in regulating DDR1 expression, offering new insights into genetically regulating milk production in cattle.

IGF-I and GH Genes polymorphism and their association with milk yields, composition and reproductive performance in Holstein–Friesian dairy cattle

BackgroundThe insulin-like growth factor (IGF-I) and growth hormone (GH) genes have been identified as major regulators of milk yield and composition, and reproductive performance in cattle. Genetic variations/polymorphism in these genes have been found to influence milk production, yield and quality. This investigation aimed to explore the association between IGF-I and GH polymorphisms and milk yield and composition, and reproductive performance in a herd consisting of 1000 Holstein–Friesian (HF) dairy cattle from El-Alamia farm. The experimental animals were 76 ± 7.25 months in age, with an average live weight of 750 ± 50.49 kg, and raised under the same conditions of feeding and weather. The studied animals were divided into three categories; high producers (n = 280), medium producers (n = 318) and low producers (n = 402).ResultsThe digestion of 249 bp for IGF-I-SnaBI using the Restriction-fragment-length-polymorphism (RFLP) technique yielded two alleles; T (0.59) and C (0.41) and three genotypes; TT (0.52), TC (0.39) and CC (0.09) and this agrees with the results of DNA/gene sequencing technique. The sequencing analysis of the IGF-I gene revealed polymorphism in position 472 (C > T). Nucleotide sequencing of the amplified fragment of the IGF-I gene of different genotypes was done and submitted to the NCBI GenBank with Accession no. MH156812.1 and MH156811.1. While the digestion of 432 bp for GH-AluI using the RFLP technique yielded two alleles; A (0.81) and G (0.19) and two genotypes; AA (0.77) and AG (0.23) and this agrees with the results of DNA/gene sequencing technique. The sequencing analysis of the GH gene revealed polymorphism in the position 1758 C > G and in turn led to changes in amino acid sequence as Alanine for (A) compared to Glycine for (G). Nucleotide sequencing of the amplified fragment of the GH gene was done and submitted to the NCBI GenBank with Accession no. MH156810.1. The results of this study demonstrate the effects of variants of the GH-IGF-I somatotrophic axis on milk production and composition traits in commercial HF cattle. The greatest values of milk yield and reproductive performance were observed on IGF-I-SnaBI-TC and GH-AluI-AG genotypes. While the greatest % fat and % protein values were observed on IGF-I-SnaBI-CC and GH-AluI-AA genotyped individuals.ConclusionThe genetic variation of the studied genes can be utilized in selecting animals with superior milk yield, composition and reproductive performance in Holstein–Friesian Dairy Cattle under subtropical conditions.

Factors Influencing Milk Production among the Dairy Farms of Savar Sub-District, Dhaka, Bangladesh

Milk production among the dairy farms is one of the important sources of income for the farmers. However, many reasons may influence milk production. In this aspect, the objective of the study was to assess the determinants or factors influence milk production in the dairy farm of Savar sub-district under Dhaka district of Bangladesh. A sample of 218 dairy farmers was randomly selected for data collection. The survey was conducted using a pre-tested structured interview schedule among the respondents. The data was analyzed using percentage, mean, frequency, standard deviation, and regression analysis. Majority of the farmers (96.8%) had up to 70 liters of milk production in their farm with an average of 18 liters. The statistical analysis showed that credit, total cow, milking cow, and livestock income significantly influences on the amount of milk produced in the farm. The Department of Livestock Service (DLS) and other related Non-Government Organizations (NGOs) may arrange more livestock income related programs for the dairy farmers focused on milk. Initiative like providing credit facilities either interest free or lower rate of interest to purchase milking cow may help the farmers to improve their livelihood through more milk production.

Milk Production and Morphometrics Derived from Digital Images of Friesian and Holstein Cows in Different Lactation Periods

This study was conducted to analyze milk production and morphometrics derived from digital images of Friesian and Holstein cows in smallholder farms located in Pondok Rangon, Lembang, and Cibungbulang Bogor in different lactation periods. The morphometric parameters measured in this study included body length, height, chest girth, and body weight. The findings indicated that Holstein cows exhibited greater body length, height, chest girth, and body weight compared to Friesian cows across all farms. Milk production in Friesian cows remained relatively stable from lactation periods one to three. Additionally, body length, height, chest girth, and body weight were found to influence the milk production of both Friesian and Holstein cows. Cows with longer body lengths, greater heights, higher body weights, and wider chest girths tended to produce more milk. Chest girth and weight emerged as the primary factors influencing milk production in Friesian and Holstein cows, while height, body length, and lactationperiod also played significant roles.

POLIMORFIZM W GENIE UCP3 A CECHY UŻYTKOWOŚCI MLECZNEJ BYDŁA

The protein UCP3 can perform several different functions such as regulating lipid metabolism in mitochondria, protecting against oxidative stress, and regulating energy metabolism, and proper metabolism is crucial in cows during lactation. The aim of the study was to determine the frequency of genes and alleles and their influence on milk production traits for four SNP (rs467440799, rs446854207, rs444645335, and rs440638775) polymorphisms in the UCP3 gene. The experiment was conducted in a herd of Polish Holstein-Friesian black and white cows, and genotypes were determined using the PCR-RFLP method. The conducted research showed that the analyzed SNPs significantly (p ≤ 0.05) influence milk production traits such as milk yield, fat yield, and protein yield.

Computation of Heritability for Production and Reproduction Traits in Frieswal Cattle under Field Progeny Testing

Aims: To study the genetic parameter (heritability) for production and reproduction traits in Frieswal cattle under field progeny testing programme. Place and Duration of Study: G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India, between March, 2023 and March, 2024. Methodology: The present study was conducted on 1163 Frieswal cattle comprised of five different sets maintained at six field units over a period from 2013-2021. The traits considered were age at sexual maturity (ASM), age at first calving (AFC), gestation period (GP), test day peak yield (TDPY), 305 days milk yield (305D-MY), fat percentage (FP), lactation length (LL), calving interval (CI), service period (SP), number of services per conception (NSPC), dry period (DP). The data were analyzed for the estimation of heritability by the software WOMBAT. Results: The heritability estimates of the traits namely; ASM, AFC, GP, TDPY, 305D-MY, FP, LL, CI, SP, NSPC and DP were 0.469±0.082, 0.467±0.082, 0.259±0.067, 0.248±0.059, 0.354±0.013, 0.413±0.069, 0.389±0.071, 0.394±0.071, 0.452±0.072, 0.072±0.046 and 0.08±0.06, respectively. Conclusion: Therefore, the heritability estimates were found to be low to high magnitude for different reproduction and production traits and further it has been concluded that, this study will aid breeders in selecting high-performing animals for future generations, taking into account the genetic factors that influence milk production and reproductive traits during early lactation.

Effect of feeds and hygienic practices on milk production and its nutritional and microbiological quality

Abstract The review emphasizes that factors such as feed type, diet composition, and hygiene standards during milking significantly impact milk yield, composition, and microbial population. A comprehensive methodology was employed to gather relevant literature from diverse sources, including textbooks, academic journals, and databases. The review focused on research articles investigating the impact of feed type and nutrients on dairy cattle milk yield, and quality. The search terms used to organize this article were breed, feed, hygienic practices, sources of microorganisms, and milk production, and by synthesizing findings from these studies; key factors influencing milk production and quality were identified. The review highlights the significance of breed selection, feeding practices, and hygienic measures in dairy farming. Optimizing these factors can enhance milk production, nutritional quality, and microbial safety, ensuring the delivery of high-quality milk to consumers. Overall, the review provides valuable insights into the relationship between animal breed, nutrition, and hygiene practices in dairy cattle production.

Comprehensive analysis of differences in the physiochemical composition of foremilk and hindmilk of grazing indigenous and crossbred dairy goats; implications for growth, milk production and industry.

This study was conducted on 90 grazing Hair, Alpine × Hair F1 (AHF1), and Saanen × Hair F1 (SHF1) crossbred goats in three farms located around the Taurus Mountains in Konya, Türkiye. The study investigated variation in milk production, physico-chemical traits of milk fractions (foremilk, hindmilk and total milk), and growth traits. Genotype, parity, offspring sex, birth type, and flock factors significantly influenced milk production and quality traits of milk fractions (P < 0.05 to P < 0.01). Does with male/single offspring produced less milk, but with higher nutrient density (P < 0.05). Hindmilk was 272%, 31% and 61% richer in fat, total solids and energy content than foremilk, respectively (P < 0.001). However, the protein, lactose and solids-non-fat content of hindmilk was on average 7% lower than that of foremilk (P < 0.001). Physico-chemical quality traits of foremilk, hindmilk and total milk had a strong negative correlation with daily milk yield (P < 0.05 to P < 0.001). Live weight and average daily gains (ADG) of kids were influenced by maternal parity, flock, offspring sex and birth type (P < 0.05). The overall Kleiber ratios (KR) from birth to 2 months, birth to 3 months, birth to 6 months and 3 to 6 months of age were 21.0 ± 0.22, 17.1 ± 0.11, 10.5 ± 0.06 and 8.5 ± 0.21g/kg of metabolic weight, respectively. It was concluded that these findings are critical for milk sampling protocols, offspring growth strategies, product development and precision livestock management.

Optimizing Feed Formulation Strategies for Attaining Optimal Nutritional Balance in High-Performing Dairy Goats in Intensive Farming Production Systems

Abstract Genetic factors play a pivotal role in shaping feed formulation strategies for dairy goats, influencing milk production, composition, and overall productivity through the modulation of genetic parameters and polymorphisms associated with milk protein fractions and yield. Moreover, environmental challenges, including heat stress and feed availability fluctuations, pose significant hurdles in achieving optimal nutrition and performance, necessitating precision livestock farming and the utilization of local by-products to mitigate their impact on herd health and productivity. In addition, nutritional interventions, such as supplement utilization and alternative feed incorporation, offer promising avenues for addressing specific deficiencies and enhancing overall performance, from fatty acid supplementation to herbal feed additives, while balancing rations to meet evolving nutritional needs and ensuring long-term sustainability remains paramount for optimizing herd nutrition, health, and performance in intensive dairy goat production systems. The aim of this study was to explore the multifaceted influences of genetic factors, environmental challenges, and nutritional interventions on feed formulation strategies and overall herd nutrition, health, and performance in intensive dairy goat production systems.

Genome-Wide Association Study for Test-Day Milk Yield, Proteins, and Composition Traits of Crossbred Dairy Cattle in Ethiopia.

Identifying genetic regions and candidate genes that influence milk production traits is critical for understanding genetic inheritance and improving both the quality and quantity of milk in dairy cattle. Crossbred dairy cattle significantly contribute to increasing milk production and ensuring food security in the middle- and high-altitude regions of Ethiopia. However, the genetic architecture underlying their milk yield and composition traits has not yet been thoroughly investigated. This study conducted a genome-wide association study (GWAS) on 308 crossbred dairy cows from central, northeastern, and southern Ethiopia to identify genetic markers associated with key milk production traits. Using high-density SNP chip data and the fixed and random model circulating probability unification (Farm CPU) method via the Memory-efficient, Visualization-enhanced, and Parallel-accelerated R package (rMVP) (Version 1.0.7.), we analyzed traits including test-day milk yield (TDMY), total protein (TP), casein (CN), whey (W), protein percentage (P), fat percentage (F), lactose percentage (L), total solids (TS), density (D), solids-not-fat (SNF), salt (S), and freezing point (FP). This study identified 16 significant SNPs associated with these traits, including rs41661899 on Chromosome 6, which was significantly associated with both TP and W, and rs42274954 on Chromosome 12, which was significantly associated with CN. Eight SNPs, such as rs43560693, rs109098713, rs111029661, rs134499665, rs133908307, rs133627532, rs42098411, and rs110066280, were found across multiple chromosomes (8, 10, 14, 15, 19, 21, 26, and 28, respectively) and were significantly associated with milk P. Additionally, SNPs rs110844447 and rs135995768 on Chromosomes 6 and 14 were significantly associated with D and FP, respectively. Three SNPs, including rs109564259, rs135552551, and rs41620904 on Chromosomes 6, 11, and 24, were significant associations with S. Candidate genes identified near and within these SNPs include TRAM1L1, DIAPH3, PEBP4, WDR89, BCAS3, RALGAPA1, HABP2, NRG3, HPSE, PCDH7, LINC02579, TRNAS-GGA, and OR5CN1P. These findings enhance our understanding of the genetic architecture of milk-related traits in Ethiopian dairy cattle and highlight the potential for marker-assisted selection to improve milk production and composition in breeding programs.

The effect of oral administration of zeolite on the energy metabolism and reproductive health of Romanian spotted breed in advanced gestation and post partum period

The dairy cow experiences the most significant impact from negative energy balance during this period, which adversely affects reproductive health. Consequently, most pathologies affect dairy cows during this time frame. Thus, with the primary objective of reducing the incidence of these pathologies on dairy farms, we questioned whether supplemental zeolite administration in cattle feed would affect metabolism and reproductive health.Therefore, we proposed introducing an antepartum and postpartum supplementation of 400 g of zeolite in the basal diet. The control group received only the basal diet without zeolite supplementation. Monitoring the results stemmed from the consideration that reproductive health can only be present based on an unaltered energy metabolism. Hence, we deemed it necessary to analyze several metabolic markers in light of the expected outcomes concerning reproductive health.Cows treated with zeolite exhibited a calving to first service interval 12.78 days earlier than those in the control group. Moreover, the average number of services per conception used for future gestation was 0.44 lower in the zeolite-treated group compared to the control group (p<0.05). Additionally, the treatment group showed a lower presence of pathogens in the uterus and displayed a more favorable average uterine score.Observations following the completion of the research point towards an improvement in the health of transition dairy cows, opening a new path for dairy farms in terms of preventing postpartum pathologies. Indeed, the benefits from this study primarily impact the animals rather than directly influencing milk production. Therefore, further research is necessary in this regard.

Morphophysiological Responses of the Goat Mammary Gland to Water Scarcity in Arid and Semi-Arid Environments: Are They Enough to Generate Adaptation to New Climatic Challenges?

Due to climate change, diverse territories of the planet will suffer from water restrictions. Goats are perceived as the most resilient ruminants in this scenario. So, various studies have focused on describing how a lower water intake influences milk production, especially in breeds adapted to desert environments. In water-stress situations, goats lose up to 32% of their body weight (BW), the rate of passage is reduced, and the digestibility of the feed increases. When goats consume water again, the rumen prevents hemolysis and osmotic shock from occurring. Regarding milk production, the response varies depending on the breed and the level of water restriction, maintaining the milk volume or reducing it by up to 41%. Systemically, it decreases the urinary volume and glomerular filtration rate, increasing blood osmolality and the vasopressin (ADH) concentration. Studies are scarce regarding changes in blood flow to the mammary gland, but there would be a reduction in blood flow velocity of up to 40% without changing blood pressure. New studies must be undertaken to determine which breeds or crosses are the best adapted to changing environmental conditions and to improve our understanding of the changes that occur at the morphophysiological level of the caprine mammary gland.

Milk-y Way: the impact of single-nucleotide polymorphisms on milk production traits in Kilis dairy goats.

This study aimed to investigate the impact of single-nucleotide polymorphisms (SNPs) on milk production traits in Kilis dairy goats by analyzing the genotypes of POU1F1, PRLR, -Lg, GH1, and GH2 genes and their association with lactation milk yield (LMY), lactation length (LL) and average daily milk yield (ADMY). Blood samples were collected from 227 goats, and genotyping was performed using polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP). The results revealed that the frequencies of the genotypes varied among the genes. The polymorphisms were found to be significantly linked with milk production traits. These findings suggest that SNPs of POU1F1/AluI, PRLR/RsaI and -Lg/SacII are significantly associated with LMY and that the POU1F1-TC genotype, PRLR-TT genotype and -Lg-AB genotype are associated with higher LMY and ADMY. Additionally, the POU1F1-TC genotype was found to have a longer LL. However, no significant association was found between the GH1 and GH2 genotypes and LMY, LL and ADMY. Overall, this study provides valuable insights into the genetic factors influencing milk production traits in Kilis dairy goats, which can be utilized for the selection of high-yielding animals in breeding programs.

Genetic factors influencing milk and fat yields in tropically adapted dairy cattle: insights from quantitative trait loci analysis and gene associations.

The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-yearseason, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

Factors influencing milk production among dairy farmers in Southwest, Nigeria

It is estimated that herds of cattle worth $18.2 million are reared and 82% of these animals are raised in an extensive system but Nigeria spent about $1.2 billion on milk importation, this indicates that the nation is still far from sustainability. The study examines the management practices of dairy farmers, sources of information, challenges, and factors that influence milk production in the study area. The study area covered Southwest, Nigeria. A multi-stage sampling technique was used to select 293 respondents. Data were analyzed using descriptive and influential statistics. The result shows that the majority of the respondents were between 51-60 years, married, with no formal education, and had 21-30 years of farming experience. The majority produced an average of 11-20 liters of milk per day, radio was their main source of information, challenges faced by dairy farmers were the health of the animal, climate change, and breed of the animals. The factor influencing the farmers’ decision is the milking of animals (P>0.032). It is concluded that dairy production in the study area is not thriving as expected due to the above challenges. Therefore, dairy farmers need more orientation, government support, and training on the intensive management system.

Smart modelling of dairy milk production with machine learning

Complex non-linear correlations between the predictors (features) and the independent variable can be modeled using machine learning techniques. This modeling strategy is clever because it uses machine learning to develop process predictions after the right model has been created. Therefore, the purpose of this work was to examine how to simulate dairy milk production using machine learning. The daily milk output in Iwo and its environs between May 26, 2021, and May 31, 2022, as measured in liters, was used. Five features in the data set were identified; the day of the week, month, year, season and day number. We tested a total of 14 different supervised learning (regression) machine learning techniques. 20% of the data were used for validation, while 80% were used to train these algorithms. The Bagged Tree gave the highest R - square value of 0.67 and the lowest RMSE of 20.26 among the 14 Machine Learning techniques taken into account. It is therefore recommended to be used in smart prediction of daily milk production in Iwo and its environs. Also, season was found to influence milk production in the study area with higher milk production in wet season than dry season(p<.05).

Exploring the Determinants of Milk Production among Smallholder Dairy Farming: A Case of Pirojpur District, Bangladesh

Dairy farming is a good income source of the smallholder dairy farmers in Bangladesh to maintain their livelihood. In this aspect, the objective of the study was to assess the determinants or factors infl uencing milk production in the smallholder dairy farms in Pirojpur district of Bangladesh. A sample of 93 smallholder dairy farmers was randomly selected for data collection. A pre-tested structured interview schedule was employed to conduct the survey among the respondents. The data were interpreted by using percentage, mean, frequency, standard deviation and regression analysis. Majority of the farmers (84.9%) had low to moderate milk production in their farm. The milk production was infl uenced by training in cattle rearing, smaller cattle herd size, farmers’ higher knowledge on milk production, and a greater number of milking cows. The Department of Livestock Service (DLS) and other related NGOs may arrange more training programs for the smallholder dairy farmers focused on milk production. Initiative like providing credit facilities either interest-free or lower rate of interest may help the farmers to be owner of more milking cow as well as increase farm income of the smallholder dairy farmers