The Indian dairy industry is one of the fastest growing industries in the world which employs millions of farmers directly and also participates more than five per cent in the economy as well. As the industry continues to expand there is a growing need to adopt sustainable practices in the supply chain to minimize negative impact on the environment and society and ensure viability. The present research aims at examining the supply chain management practices of the two leading dairy firms -Amul and Danone. The study relies primarily on secondary sources like peer-reviewed journals, authentic websites and reports. A case study-based approach has predominantly been used to compare two leading firms in the dairy industry with respect to sustainable practices across the supply chain.&nbsp; Key aspects such as the scale of dairy production, technology adoption, pricing, traditional supply chain management, artificial intelligence in sustainable supply chains and logistics management in select dairy firms have been critically reviewed for comparison purposes. The study identified the various problems and challenges being faced by the Indian dairy industry. The study found that Amul and Danone both have focused on sustainable and green practices. However, Danone&rsquo;s ability to incorporate and enable technology has helped in improving efficiency across the supply chain making the chain sustainable. On the other hand, Amul lacked the adaptation of emerging technologies across its supply chain. The study suggested the exploration of artificial intelligence that might help in achieving a sustainable supply chain in Indian dairy firms.

Sustainable Supply Chain Management Practices in the Dairy Industry: A Comparative Study of Leading Dairy Firms and Future Research Directives

Background: India has the most significant milk production and consumption level in the world. Fluid milk consumption will rise to 90 million metric tons in FY 2024 (Annual Report 202-23, United States Department of Agriculture). Milk is an essential component of daily diet in every age segment in India. Consumers&rsquo; behaviour and consumption patterns are based on their choices and preferences about product quality, price and preferences. This article critically investigates the consumer perception towards indigenous dairy markets and their consumption and behavioural pattern.&nbsp; 
 
Methods: Quantitative approach and Multiple Logistic Linear Regression Analysis (MLLRA) technique was used to test the hypothesis to establish a direct and indirect relationship among endogenous and exogenous variables. The sample was drawn from rural and urban regions of India&rsquo;s top ten milk-producing states.&nbsp; 
 
Result: The research findings suggested a significant relationship between the direct and indirect role of consumers buying behaviour characteristics towards milk and dairy products and their satisfaction level. This research is limited to milk processors, dairy companies and dairy scientists in the field of marketing and dairy research. Dairy Farmers, Processors and Producers are vigilant about the quality of food products, especially milk delivered to their end users and their value-addition in the Milk Supply Chain (MSC) and logistics. In the past three years, during the unprecedented COVID-19, consumers&rsquo; consciousness level about health and well-being has been argued.&nbsp;

Consumer Behavioural Patterns Towards Milk and Dairy Products: An Analytical Investigation of an Indian Dairy Supply Chain

<div style="text-align: justify;">Background: Disruption through present pandemic is applicable to almost all the sectors of economy. However, impact on Indian food and dairy industry is largely experienced considering it as the livelihood of sizable stakeholders emphasizing small and marginal farmers. Present study is undertaken to examine the global assessment of dairy supply chain with emphasizing on India, USA and Canada, which will be important to observe positive and negative trends of Covid-19 and suggesting appropriate measures for dealing with present and similar situations in near future. Methods: Systematic literature review assessment had been followed from major web platforms like Jgate, Ebsco database and popular news articles were explored since December 2019 to April 2020 for the study purpose.&nbsp; Conclusion: Along with supply chain assessment through its various components, it was observed that although different countries have negative effect on the dairy communities, but these adverse situations can be converted into new possibilities for expansion. It was also observed that dairy industry has the potential to convert present crisis into opportunity thereby not only concentrating on health part of consumers but also contributing towards generating employment. &nbsp;&nbsp;</div>

<div style="text-align:justify">Impact of COVID-19 on Global Dairy Supply Chain: A Review</div>

<div>Background: Jharkhand State Cooperative Milk Producers&rsquo; Federation (JMF) plays crucial role in processing of raw milk procured from the member-producers across the Jharkhand State and contributes to dairy development. The current study investigates the critical factors in JMF&rsquo;s dairy supply chain, specifically the processing unit and offers an initial decision framework for its implications.&nbsp; 
 
Methods: To summarise the strengths, weaknesses, opportunities and threats (SWOT) of the milk processing system in JMF, the necessary data were collected from dairy producer members, including dairy farmers, executives and key informants of processing units. This includes identifying the dairy industry&rsquo;s objectives as well as the internal and external critical factors (CFs). Because SWOT analysis provides no investigative basis for evaluating the priorities of CFs, the analytic hierarchy process is used to define the priorities of identified CFs. The CFs have also been sorted in the order of importance.&nbsp; 
 
Result: The findings of this study show that fully computerised system with self-automation facilities; high operational cost for processing liquid milk; development of new product and value addition; high labour cost or shortage of labour are the major strength, weakness, opportunity and threat of JMF, respectively. Further, the SWOT-based methodology provides critical sensitivity in assessing supply chain strategies for the dairy cooperative like JMF.&nbsp;</div>

SWOT Analysis of Dairy Processing Supply Chain of JMF using Analytical Hierarchy Process

<div>Background: Dairy sector has highly fragmented supply base and unique ecosystem of delivery resulting that a chain of value addition actors involved in its production and distribution. Value chain financing approach provides opportunities to develop equitable business models that better link all actors in the value chain. Accordingly, this study has carried out to assess the diversity of financial arrangements and the actors involved in dairy value chain in the Eastern Uttar Pradesh. The study also brings about the relatively prominent components/actors of the dairy value chain that could be emphasised while financing dairy value chain.&nbsp; 
 
Method: The value chain actors including milk producers have identified purposively and interviewed with well-constructed scheduled. The study has analysed on the data collected from 64 milk producers in 8 villages, 3 inputs suppliers, 8 milk collectors/assemblers, 4 milk transporters, 1 milk processor and 12 distributers for the year 2019-20.&nbsp; 
 
Result: The study observed that there is vast network of financing institutions have engaged in the financing of dairy value chain in the study area. Financing agencies have identified the set of activities associated with milk value chain and determine the structure of finance accordingly, in order to minimize costs, to maximize efficiency and to reduce risk. However, there are several informal mechanism of value chain financings also existed parallel to institutional finance due to informal sources are willing to lend money more easily without collateral. Relationships between actors in the value chain facilitate informal financial flows directly to his client actors is also observed in the study. The study has further inferred that among all the actors involved in milk value chains, the processor, producer and distributer have added greater value addition in comparison to other actors in the value chain.&nbsp;</div>

<div>Value Chain Finance to Dairy Sector-A Case Study of Eastern Uttar Pradesh</div>

Background: Jharkhand State Cooperative Milk Producers&#39; Federation (JMF) plays a vital role in the processing of raw milk purchased from Jharkhand State member-producers and contributes to the development of the dairy sector. The current study explores the essential components in JMF&#39;s dairy supply chain, focusing on the marketing&nbsp;unit, and provides a preliminary framework for making decisions regarding its ramifications.

Methods: To compile a SWOT analysis of the milk marketing&nbsp;system in JMF, data were collected from dairy producer members, including dairy farmers, marketing&nbsp;unit executives, and key informants. This includes establishing the objectives of the dairy sector and the internal and external critical factors (CFs). Because SWOT analysis does not give an investigative basis for evaluating the priorities of CFs, the analytic hierarchy approach is utilised to determine the priorities of detected CFs. The CFs have also been ranked according to their importance.

Results: This study&#39;s findings indicate that the SWOT-based methodology gives crucial sensitivity when evaluating marketing&nbsp;chain strategy for dairy cooperatives like JMF. The findings of this study show that wide range of quality dairy products, absence of strong sales and marketing experience, emerging new markets offering greater marketing potential, seasonal slump are the major strength, weakness, opportunity and threat of JMF, respectively.

SWOT Analysis of Dairy Marketing Chain of JMF using Analytical Hierarchy Process

Background: The increasing demand for organic legume products has raised concerns about the validity of supply chains. This research explores the integration of blockchain and Artificial Intelligence (AI) technologies as a robust solution for ensuring the accuracy of organic legume products in supply chains. Leveraging the immutable and transparent nature of blockchain, the study establishes a decentralized ledger to record and validate each stage of the supply chain, from crop husbandry to distribution.&nbsp; 
 
Methods: Artificial intelligence (AI) algorithms are used in tandem to examine data points and identify irregularities that can signal the existence of fake goods. Through the integration of various technologies, the research aims to offer an advanced and flexible system that can anticipate and detect any risks to the validity of the product. Smart contract implementation on the blockchain enables automated verification procedures assuring, adherence to organic norms and laws. 
 
Result:&nbsp;Through case studies and empirical evidence, this paper demonstrates the efficacy of the proposed blockchain and AI integration in mitigating the risks associated with counterfeit organic legume products. This research contributes to the burgeoning field of blockchain and AI applications in supply chain management, offering a novel approach to fortify the integrity of organic food supply chains.

Blockchain and Artificial Intelligence for Ensuring the Authenticity of Organic Legume Products in Supply Chains

Background: This paper attempt supply chain and post-harvest losses in fruits cultivation. India ranks second in fruit and vegetable production in the world. 
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Methods: A data was collected from seven districts of middle Gujarat for identifying the existing supply chain in fruit supply chain and calculate the post-harvest losses. Tabular Analysis method was used to calculate post-harvest losses. 
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Result: In middle Gujarat average production of banana, mango, papaya and lime was 863.80, 105.00, 810.97 and 540.00 q/ha respectively, where total damaged fruits at filed level was 6.59, 2.50, 2.30 and 1.01 per cent in banana, mango, papaya and lime, respectively. Losses at wholesale level is quite high as compared to field level because after harvesting this fruit passes through village level suppliers in banana or pre-harvest contractors in case of mangoes and papaya and APMC wholesaler in lime supply chain. Post-harvest losses in different fruit crops at retail level, highest loss at retail level found in papaya which was 8.70 followed by mango 8.09, banana 4.41 and lime 2.70 per cent. These losses can be minimized using new advancement and mechanization in harvesting and postharvest losses like, mechanical harvesting, pre-cooling immediately after harvesting, proper packaging and storage.

Estimating Post-harvest Losses in Fruits Supply Chain in Middle Gujarat Region&nbsp;

Background: The loss of vegetables is immense which is accrued to its perishability and sub optimal level of post-harvest management. There is a technological gap in adoption of harvesting and post-harvesting practices by farmers. There is sparse qualitative and quantitative assessment of post-harvest losses of vegetables in Punjab. The objective of the study is to identify the operation and channel where the losses are crossing the threshold, to estimate the extent of losses and characterize them at various post-harvest operations and levels for selected vegetables in Punjab and to analyse the factors responsible for post-harvest losses. 
 
Methods: The sample in survey location consisted of all the stakeholders of supply chain network for vegetables in the state of Punjab, India. The stakeholders consisted of farmers, wholesalers and retailers. The study adopted cluster sampling technique. The clusters selected for the study were Nakodar, Malerkotla and Baba Bakala Sahib and the vegetables selected for the study were potato, pea, tomato, okra and cauliflower. Further snowball sampling technique was used to select 80 farmers from each cluster, making up a total sample of 240 farmers and one reference each for wholesaler and retailer was identified in every cluster. Then using snowball technique, 2 wholesalers and 10 retailers were selected from each cluster. Thus, making total sample of 10 wholesalers and 30 retailers were selected for the study. The instrument used for the data collection was a structured interview schedule. The one-way ANOVA and Tukey&rsquo;s Honest Significant Difference test were employed to understand the significant difference in post-harvest losses between the selected vegetables and along the supply chain. 
 
Result: The results revealed that the maximum losses were observed in tomato crop at farm level (17.71%) and retailer level (30.10%) whereas at wholesaler level maximum losses were recorded in pea (8.19%). The extent of losses at farm level has been higher as compared to wholesaler level and it was highest at the retailer level. At farmer&rsquo;s level it was observed that there have been significantly higher losses in tomato crop (17.7&plusmn;13.35). At retailer level, significantly higher losses were observed in tomato (30.10&plusmn;15.80) whereas at wholesaler level, significantly higher losses occurred in pea (12.29&plusmn;3.15). There was no significant difference in losses between farmer and retailer level. Major cause of loss reported by tomato growers (88.6%) was infestation of fruits with disease and insect. Main reason of post-harvest losses in okra and cauliflower as stated by farmers were bruises/blackening and over maturity. Since the findings reveal that the major losses in the supply chain of vegetables was due to lack adoption of harvest and post-harvest practices at farmer&rsquo;s level. It is suggested that field level training should be imparted to farmers regarding post-harvest management techniques.

Characterization of Post-harvest Losses along the Supply Chain of Vegetables in Punjab

Background: Apple fruit is the major horticultural crop cultivated in the state of Himachal Pradesh. Shimla district is the largest apple producer among all districts of Himachal Pradesh. Though significant studies related to Apple fruit marketing and understanding of Apple&rsquo;s supply chain management have been conducted in the past of the state. However, there is a discernible gap in understanding the supply chain management practices adopted by apple growers in Himachal Pradesh. This highlights the need for the present study to provide a comprehensive analysis of the key determinants influencing apple farmers&rsquo; supply chain management practices, as well as the impact of supplier selection criteria and institutional support on SCM practices in the Shimla District of Himachal Pradesh. 
 
Methods: In order to meet the objectives of the study well-structured questionnaire was administered among the respondents to collect the required information. For the selection of the respondents, the non-probability sampling method, i.e., convenience sampling, was used in the study. The data thus collected was analysed through, descriptive and advanced statistical techniques such as Cronbach&rsquo;s alpha for reliability analysis, descriptive statistics and advanced statistical techniques such as multiple regression. 
 
Result: The findings of the study revealed that there is strong internal consistency across all constructs, ensuring the reliability of the instruments used. The regression analysis revealed that there is a significant and positive relationship between supplier selection criteria, institutional support and SCM practices. 
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