Correction: Market performance and supply chain selection dynamics for vegetables grown through sustainable practices in the Northwest Himalayan region Name of all authors as they appear in the published original article (

Ajay Kumar^*Divyanshu KumarRaghubir Singh PrasherRajeshwar Singh ChandelINDER DEVSubhash SharmaPiyush MehtaRohit Vashishat

• Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, India

AbstractThe production of marketable vegetable crops in the Northwest Himalayan region is crucial for bolstering the economy and sustaining the livelihoods of farming communities in the area. The factors influencing vegetable crop production, marketing, and farmer livelihoods include the selection of output market supply chains. Recognizing the importance of these aspects, this study examines the key determinants influencing farmers' decisions regarding marketing supply chain selection. The study has highlighted the socio-economic dimensions of the area and its dwellers, further attempted to understand the cost of natural farming cultivation, followed by understanding the resource utilization in the natural farming practices, analytical representation of marketing components associated with the natural farming cultivation, and also attempted to analyze the key production and marketing problems associated with the natural farming. The concerned study has presented the analytical aspects of marketing supply chains comprehensively. The findings revealed that three primary marketing supply chains were prevalent in the study area. Among these, SC - C (Producer-Local Trader-Wholesaler-Retailer-Consumer) was the most commonly used, with 63% of the produce marketed through this supply chain, reflecting a preference for intermediary-based systems due to limited direct market access. The study reported facing significant marketing challenges, including a lack of access to specialized markets, an absence of fair pricing, and inadequate government support. Moreover, issues such as wholesalers not consulting farmers while selling their produce, lack of training and extension services, and poor market infrastructure were highlighted as key constraints. These marketing problems hinder farmers from obtaining fair value for their natural farming produce. The study emphasizes the need for improved market access, enhanced training facilities, and policy interventions to address these challenges and improve the overall marketing efficiency of natural farming systems in the region.Keywords: Natural farming, Vegetable crops, Marketing challenges, Market supply chains, Consumer awareness.IntroductionGlobally, agriculture contributes to about 18% of the net emissions just from the production of crops. The post-farm-gate contribution in packaging, transportation, consumption, and wastage is over and above this contribution (Hannah Ritchie, 2020). Overall, it is estimated that conventional food systems impact about 26% of the global climate crisis. In India, there is a major challenge to food systems from a sustainability perspective of social, ecological, and economic proportions. This is also reflected by the frequent farmer protests linked to these aspects and the impact of climate change, which is experienced due to many factors (Hannah Ritchie et al., 2022). The strategic shift toward diversified horticulture, especially vegetable cultivation, is recognized as a key driver for improving food and nutritional security, rural livelihoods, and sustainable agricultural intensification (Schreinemachers et al., 2018). India stands out globally for its ability to cultivate a wide variety of vegetables, owing to its diverse agro-climatic conditions, which enable year-round vegetable production. Compared to cereal crops, vegetables often command higher market prices, have shorter cultivation cycles, and yield more per hectare. This makes them crucial not only for enhancing farmers' incomes but also for contributing significantly to the country's nutritional security (Rishitha et al., 2017). This convergence of global insights and India's unique production advantages underscores the transformative potential of vegetable cultivation as a sustainable strategy for achieving both economic and nutritional goals in agriculture (Confo et al., 2024; Shraddha et al., 2024; Shraddha et al., 2023). These factors, combined with the growing importance of achieving food and nutritional security, position vegetable farming as a critical element in India’s agricultural sector. According to the Dietary Guidelines by the Indian Council of Medical Research (ICMR 2024), it is recommended that every individual consume at least 400g of vegetables daily. This includes 100g of GLV, 250g of other vegetables, and a portion of roots and tubers. The economic significance of vegetable consumption is linked to increased market demand, which directly influences farmers' cropping decisions. By aligning production with market needs, vegetables serve as high-value crops that enhance income opportunities for producers while simultaneously addressing the Zero Hunger goal (SDG 2 of the Sustainable Development Goals) (Vashishat et al., 2024; Agrawal et al., 2021).Himachal Pradesh is a North Indian state known for its varied agro-climatic zones, supporting the cultivation of a broad spectrum of crops, particularly vegetables. Within Himachal Pradesh, the Mandi District stands out as a significant hub for vegetable cultivation, with food crops being a major source of livelihood for farmers. The data from 2021-2022 indicates that vegetable farming plays an essential role in the region’s agricultural output, contributing significantly to its economy. A total of 7,931ha was dedicated to vegetables (Department of Economics and Statistics 2022). Mandi District's agricultural profile reveals that vegetables are vital for both subsistence and commercial agriculture, further reinforcing the link between vegetable farming and rural development in the region. In recent years, natural farming practices have emerged as an alternative to conventional methods, offering a more sustainable and cost-effective approach. These practices have proven transformative, particularly for small and marginal farmers who have benefited from reduced input costs due to the reliance on organic inputs like bio-fertilizers and pest management techniques (Bharucha et al., 2020). This shift not only helps protect the environment but also increases net income, making natural farming an increasingly attractive option for vegetable growers.However, despite the potential for higher incomes from vegetable farming, farmers in Mandi and across Himachal Pradesh face numerous challenges. Traditional farming practices, along with market inefficiencies, restrict farmers from fully capitalizing on the benefits of vegetable farming. As consumers become more health-conscious and demand for chemical-free, organic produce rises, farmers practicing natural farming find themselves in a position to tap into premium markets. This trend has enabled them to command higher prices for their produce, contributing to a noticeable improvement in their financial stability (Nayak et al., 2020; Chandrashekar, 2010; Yadav et al., 2013). Yet, challenges remain, particularly in terms of market access, transportation, and the availability of specialized markets that cater to natural or organic produce. Despite these hurdles, natural farming is gradually reshaping the agricultural landscape in Himachal Pradesh by improving farmers' incomes while promoting sustainability.Marketing vegetable crops is a complex endeavor that involves various stakeholders, including producers, intermediaries, and retailers. The efficiency of the marketing supply chains chosen by farmers has a direct impact on their income and the sustainability of their livelihoods (Negi & Anand, 2015). In districts like Mandi, where smallholder farming is prevalent, the lack of streamlined marketing systems can significantly hinder the potential benefits of vegetable cultivation. Farmers often face obstacles such as high transportation costs, a lack of proper market information, and intermediaries who take a significant share of profits. As a result, optimizing these marketing supply chains is critical for ensuring that farmers can maximize their earnings from vegetable production (Chand, 2012).This research paper aims to investigate the production and marketing challenges faced by vegetable farmers in the Mandi District of Himachal Pradesh state in India, with a particular focus on those practicing natural farming. By examining these issues, the study intends to provide insights into how natural farming practices can be integrated into the existing agricultural framework, ultimately leading to more sustainable and profitable outcomes for farmers. The study also highlights the broader implications for rural development and food security, emphasizing the role of sustainable agricultural practices in enhancing the livelihoods of farmers and promoting long-term environmental health. This research focuses specifically on the Production and Marketing of Vegetable Crops Grown under Natural Farming: a Case Study of Mandi District in Himachal Pradesh, offering valuable insights into the opportunities and challenges that shape the livelihoods of vegetable farmers in this region.Materials and Methods Subhash Palekar Natural Farming (SPNF), as adopted by farmers surveyed, follows a natural farming approach utilizing locally available biological resources for crop production and protection. Core interventions under SPNF include Beejamrit (a seed treatment formulation prepared from cow dung, cow urine, lime, and forest soil), Jeevamrit/Ghanjeevamrit (a microbial culture used as a biostimulant to enhance soil microbial activity and nutrient cycling), Achhadan (biomass mulching to conserve moisture and organic matter), and Waaphasa (ensuring optimal soil aeration and moisture balance for plant roots). These interventions are designed to regenerate soil health, minimize dependency on synthetic inputs, and strengthen agroecological balance. The biopesticide formulations like Neemastra, Brahmastra, and Agniastra—prepared using cow urine, neem leaves, green chili, garlic, and other botanicals—were used periodically to manage pests under SPNF.“A sustainable food system (SFS) is a food system that delivers food security and nutrition for all in such a way that the economic, social, and environmental bases to generate food security and nutrition for future generations are not compromised. This means that: – It is profitable throughout (economic sustainability); – It has broad-based benefits for society (social sustainability), and – It has a positive or neutral impact on the natural environment (environmental sustainability”). (FAO, 2018)The SPNF approach aligns with the broader vision of transitioning toward a Sustainable Food Systems Platform for Natural Farming (SuSPNf) by promoting ecological integrity, reducing the carbon footprint of agriculture, and improving farm-level resilience. By eliminating external inputs and reducing water usage, SPNF fosters self-reliance among farmers and enhances agrobiodiversity, which is vital for climate adaptation. The circular use of on-farm resources contributes to closed-loop nutrient cycles and reduced pollution, making SPNF a practical model for food system transformation, especially in resource-constrained hill agriculture contexts like Himachal Pradesh. Study areaThe Mandi district can be found between latitudes 31°13'50" and 32°04'30" north and longitudes 76°37'20" and 77°23'15" east. On the northwest, it is bordered by Kangra, and on the west, by Hamirpur and Bilaspur. The majority of the population in the Mandi district is dependent on agriculture for their livelihood. Mandi district ranks third for the production of vegetables (226725 tons) and second for the area under vegetables (11109ha) (Department of Economics and Statistics 2018).Sampling Procedure:Selection of the study area and Sampling designMost districts in Himachal Pradesh engage in the practice of natural farming. Himachal Pradesh's Mandi district was specifically chosen for this study. The farmers who practice natural farming were ultimately chosen using a simple random sampling design. From the Project Director of ATMA, Mandi, a list of farmers engaged in Subhash Palekar Natural Farming (SPNF) was initially obtained. Following that, 40 farmers were chosen at random from each of the three blocks of Sundernagar, Karsog, and Balh, based on their natural farming experience and progress. 120 farmers were therefore chosen as a sample for the study. Selection of market intermediaries The study determined the sample size of market functionaries based on information obtained from the agricultural produce market committee office. As a result, four main markets were chosen. Shimla, Solan, Chandigarh, and Delhi markets were selected purposively. Further, to investigate different aspects of the four vegetables' output marketing, a total sample size of 80 traders was formed by randomly selecting 5 local traders, 5 commission agents, 5 wholesalers, and 5 retailers from each market.Distribution of natural farmers by size of their landholding among the sampled farmers To analyze the data, all respondents were divided into three groups based on the size of their landholdings: marginal (<1 ha), small (1 to 2ha), and medium (2 to 4ha). Table 1 shows how the sample households were distributed based on their holding size.Table 1: Distribution of sample households according to their land holdingsSr. No.Category of farmerSize of landholding (ha)Number of farmersPercentage of farmersThe average size of landholding (ha)1Marginal< 18974.170.582Small1 – 22420.001.223Medium2 – 40705.832.33Analytical framework for marketing performanceMarketing Cost The marketing costs were calculated by combining the costs incurred by each marketing functionary participating in the supply chain process of major vegetable production. The amount spent on marketing differed depending on various factors such as the type of specific marketing activities, the type of marketing institutions, and the location of marketing. The intermediaries marketing costs comprised costs for packaging materials, fees for loading and unloading, transportation costs, commission charges, and taxes (Acharya and Agarwal, 2016). nTCm= Cg + ∑ MCi i=1Where,TCm = Total cost of vegetable marketingCg = Cost paid by the grower in the marketing of his produce MCi = Marketing costs incurred by an ith middleman.Marketing Margins: Marketing margin analysis examines price variations at various stages of the marketing chain within the same timeframe. It evaluates the share of the final selling price captured by a specific agent in the marketing chain, often expressed as a percentage of the final price or the price paid by the end consumer (Thakur et al., 2023). In this study, marketing margins were employed as a key indicator for assessing market performance (Ghorbani, 2008). The marketing margin represents the difference between the farm-gate price, which is the price paid to the initial seller, and the retail price, or the price paid by the final consumer (Abankwah et al., 2010).For this research, marketing margins were computed by calculating the absolute margin, where the cost price (including purchase price and marketing costs) is subtracted from the selling price of peas by a market agent. Several factors influence the size of marketing margins in different agricultural output marketing supply chains for peas, including the length of the marketing chain, the number of economic activities involved, and the profit expectations of each marketing entity. To calculate the percentage of marketing margins received by each intermediary in the marketing process, the formula provided by Acharya and Agarwal (2016) was applied. Ami = PRi – (Ppi + Cmi) Where, Ami = Absolute margin of middlemen PRi = Total value of receipts per unit (sale price) Ppi = Purchase value of goods per unit Cmi = Cost incurred on marketing per unit Price spreadThe difference between the price paid by the consumer and the price received by the producers was the marketing margin, or price spread. Generally the economic efficiency of a marketing system is measured in terms of price spread. The smaller the price spread, the greater the efficiency of the marketing system, as suggested (Acharya and Agarwal 2016). Producer’s share in consumer’s rupee: It is the price received by the producer expressed as a percentage of the retail price (i.e., the price paid by the consumer). The producer’s share in the consumer’s rupee has been worked out as under:Where, PS = Producer’s share in consumer’s rupeePF = Price received by the farmer per unit of outputRP = Retail price per unit of outputMarketing efficiency Marketing efficiency of the marketing supply chains: In the case of marketing supply chains, the marketing efficiency is concerned with the movement of goods from producer to consumer at the lowest possible cost consistent with the provision of services desired by the consumers. The marketing efficiency of various supply chains in the study area has been computed by using Acharya’s method (Acharya and Agarwal 2016), as follows:1Where, ME = Marketing efficiencyRP = Retailer’s priceMC = Total marketing costs.MM = Total marketing marginsAnalytical framework for factors influencing choice Multinomial logit regression model We used a multinomial logistic regression model to assess farmers' preferences for agricultural output marketing supply chains. We employed this technique because farmers in the study regions have more than two options for marketing their farm produce. The model plays a significant role because, through this choice, the method can value multiple marketing supply chains. To examine the factors influencing their choice of marketing supply chains, an MNL model was employed. The MNL model is commonly used when there are several alternatives for the variable being explored (Bardhan et al., 2012; Martey et al., 2012; Delong et al., 2019; Asante and Weible, 2020; Goncalves et al., 2022). This technique is suitable for analyzing responses that are not ordered and involve more than two options (Chung et al., 2011; Mgale and Yunxian, 2020; Olutumise, 2022). Furthermore, based on the conceptual framework and previous empirical research on market supply chain selection, several relevant explanatory variables with potential impact on the choice of marketing supply chains were identified and incorporated into the multinomial logit analysis (Panda and Sreekumar, 2012; Gelaw et al., 2016; Pham et al., 2019; Thakur et al., 2022a,b). According to (Greene, 2003) and (Gujarati and Porter, 2009), we assumed the probability (Pij) that the ith farmer will choose the jth agricultural output marketing supply chain among two available options. Consequently, the multinomial logistic regression model was used to estimate the probability of a farmer selecting a specific alternative j in the following manner: (1)3Where xi is a distinct characteristic of the ith farmer, while βj represents a set of estimated regression parameters associated with the jth alternative. It is important to note that there are two agricultural output market supply chains available for selection in the choice set. In the multinomial logit model, the coefficients of the independent variables for the reference or omitted category are assumed to be zero. To determine the probability of selecting the base category, the following equation is employed: (2)The probabilities of the ith farmer belonging to the remaining one category (where j = 2) can be computed using the following approach: (3)To assess the impact of various characteristics on the likelihood, the marginal effects can be determined by differentiating equation (1) concerning the covariates in the following manner: (4)Pj represents the probability that the vegetable producer will choose marketing supply chain j, while βj is a vector of regression parameter estimates specifically associated with option j,The empirical Multinomial Logit Regression model incorporates the following variables that influence the farmers’ selection of marketing supply chains for their pea produce: Pij = 1n (Pi/Pj ) = β0+ β1 Education + β2 Farming Experience + β3 Storage Facility + β4 Distance + β5 Financial Urgency + β6 Payment in Advance + β7 Premium Price + β8 Specialized Market. The variables that need to be estimated in the model are β0. . . . . . . . . . . . . . . . β8. Pij represents the probability that farmer i chooses marketing supply chain j for their agricultural output. Where, j= 1 for producer→ retailer→ consumer, j= 2 for producer→ local trader→ wholesaler→ retailer → consumer. In the present research study, we used STATA-12 software to estimate the empirical model.Analytical framework for marketing constraintsMarketing problems: To study the various problems associated with the production and marketing of natural farming, it was assumed that the extent of a particular problem varies from place to place and farmer to farmer. The multiple responses of producers reporting various problems were taken into consideration for analysis.Chi-square test: To test whether there was any significant difference among marginal, small, and medium farms of Mandi for the problems faced by them. The chi-square test in the (m x n) contingency table was applied (Turhan, N. S. 2020), where m and n are the number of marketing problems faced by the farmers of natural farming in Mandi district. The detail of the approximate chi-square test is given as under:Where,O = Observed values.E = Expected values.