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The global organic market is expanding, and India is in an advantageous position with the highest number of organic producers worldwide. Although many articles have been published on the value chain of organic products from India, no significant studies were found related to the value chain analysis of organic pineapple. This study aims to know the various aspects of the organic pineapple value chain, i.e. network structure, value addition at various stages of chain actors, value chain upgradation and governance structure.

The study is explorative in nature, and primary data from various actors involved in the chain is collected and analyzed. Primary data through a structured schedule and interviews are collected from farmers and traders. A multistage sampling plan has been adopted. A sample of 75 farmers was randomly selected from the study area. For traders, snowball sampling is used due to the nonavailability of the sampling frame. A total of 10 commission agents, 10 wholesalers and 20 retailers were thus selected for the study. For objectives 1 and 4, descriptive statistics are used. For objective 2, a modified formula described by (Murthy et al., 2007) is used to calculate farmer’s net price and marketing margin. For objective 3, Garrett’s ranking technique is used to identify various constraints in upgrading the organic pineapple value chain in Assam.

This study shows that the value chain of organic pineapple is in the initial stage and proper value addition is required to have a complete regulated value chain. Six marketing channel is identified, and products are sold through farmer producer company only in case of export and trade with distant buyers. The marketing efficiency for channels II and III is 1.69 and 0.99, respectively. The degree of value addition for channel II in the hands of the commission agent, wholesaler and retailer is 11.65%, 4.56% and 12.60%, respectively. In the various constraints in upgrading the value chain, farmers rank “policy support” as a major constraint. In the governance structure, trade with distant traders and exports is done formally and through written contracts.

The study performs value chain analysis of organic pineapple in Cachar district of Assam, India for the year January 2022–January 2023. Future studies are encouraged related to various aspects of the supply chain and value chain of organic pineapple from various northeastern states of India and other states.

The study will help policymakers and key actors to know the existing chain and frame a well-coordinated and regulated value chain.

This study is one of the first study to explore the value chain of organic pineapple of Cachar district of Assam, India. Implementation of these findings can help various actors to strengthen the existing value chain.

The aim of the study is to systematically map the articles published in the area of organic food value chain. Many articles have been published in various domains of organic food value chain, but no significant study has been found related to the systematic mapping of literature.

This study relies on secondary data. Articles from Scopus and Google Scholar databases between January 1, 1990, and July 10, 2021, have been considered. On the basis of inclusion criteria, 56 articles have been analysed in this systematic mapping study.

This study describes the geographical coverage, the methodologies used, sector/industry-specific context of the articles and scope the for future research. Five clusters were identified through co-occurrence analysis: (1) “organic agriculture and sustainable value chain” (2) “organic farming and food value chain,” (3) “organic value chain and sustainable development,” (4) “organic value chain and environmental impact” and (5) organic value chain and profitability.

The study considers only articles published in Scopus and Google Scholar with some specific keywords related to the value chain and organic food industry. Future studies are encouraged by considering a wide range of keywords with a larger data set.

To the best of the author's knowledge, this study is the first to have a systematic mapping of literature on the organic food value chain.

The COVID-19 has had a diversified and dynamic impact on the food and agricultural sector, particularly in the agri-food value chain. Although a good number of articles were published in various countries and continents covering various aspects of the impact of COVID-19 on the agri-food value chain, no significant studies were found related to the mapping of published literature to know about the scenario and current trend research. The study aims to perform a systematic review and bibliographic mapping in the agri-food value chain to provide insights into the same.

Articles included in the Scopus database from January 1, 2020 to July 10, 2021 are considered. After initial screening and inclusion criteria, 41 articles have been selected to perform a systematic review which is published in the agri-food value chain. In addition to this, by considering the growth of the online food market, systematic mapping with the application of bibliometric analysis is performed to know the trend of the publications. Co-occurrence analysis with VOS viewer software version 1.6.16 is used for making network maps and supports the visualization of these maps.

The synthesis of the findings reveals that four broad themes recur in the articles: namely, food security and crisis during the pandemic, food price fluctuations, the impact of COVID-19 and disruption in the agri-food value chain and resilience strategies to strengthen the value chain. Alongside, the synthesis of the findings, this study describes the geographical coverage, methodologies used, sector/industry-specific context of the articles and scope of future research. In co-occurrence analysis with keywords, four clusters are identified related to the online food market and are categorized as “COVID-19 and Online food delivery services,” “Consumer satisfaction to online food delivery services,” “Food delivery system” and “Demographic impact on online food market.”

The study considers only the article from the Scopus database and article published between January 1, 2020 and July 10, 2021. Future studies are encouraged related to impact analysis studies of resilient strategies suggested by various authors by considering multiple databases.

This study will be beneficial for scholars and policymakers to know what is trending in the agri-food value chain and policymakers can implement various resilience strategies as discussed to mitigate the impact. The future research scope highlighted in this paper will encourage scholars and academicians to explore this area and will provide in-depth understanding.

The purpose of this paper is to investigate the estimation methodology with a highly generalized cost-effective single hidden layer neural network.

The aerodynamic parameter estimation is a challenging research area of aircraft system identification, which finds various applications such as flight control law design and flight simulators. With the availability of the large database, the data-driven methods have gained attention, which is primarily based on the nonlinear function approximation using artificial neural networks. A novel single hidden layer feed-forward neural network (FFNN) known as extreme learning machine (ELM), which overcomes the issues such as learning rate, number of epochs, local minima, generalization performance and computational cost, as encountered in the conventional gradient learning-based FFNN has been used for the nonlinear modeling of the aerodynamic forces and moments. A mathematical formulation based on the partial differentiation is proposed to estimate the aerodynamic parameters.

The real flight data of longitudinal and lateral-directional motion have been considered to estimate their respective aerodynamic parameters using the proposed methodology. The efficacy of the estimates is verified with the results obtained through the conventional parameter estimation methods such as the equation-error method and filter-error method.

The present study is an outcome of the research conducted on ELM for the estimation of aerodynamic parameters from the real flight data. The proposed method is capable to estimate the parameters in the presence of noise.

Despite competition and supply-chain disruptions during Covid-19 pandemic (2019–2021), one grocery retailer consistently thrived and was ranked top. The sources of the sustained performances needed examination. Guided by self-congruity theory and integrating three models, the authors examined how much the retailer's brand performances (brand loyalty, equity, preference and repurchase intentions) were emanating from brand personalities and marketing offerings. The mediating roles of brand loyalty and equity were tested.

Cross-sectional data was collected from 480 frequent customers using an online questionnaire posted on the researchers' social media pages. Factor analysis was conducted to identify the dimension that best describes the grocery retailer. Partial least square–structural equation modelling (PLS-SEM) was used to test a conceptual model.

Factor analysis results show that brand sincerity (28.582% variance-explained; M = 4.1) was top (factor 1), followed by excitement (20.336% variance-explained; M = 3.9) and then trustworthiness (18.854% variance-explained; M = 3.87). PLS-SEM results revealed that two brand personalities (brand excitement and trustworthiness) and marketing offerings (price, place, product, promotion) impacted loyalty found to be a strong driver of brand equity. Repurchase intention and brand preference were influenced by brand equity. Brand loyalty mediated most of the relationships between brand personality dimensions, marketing offerings and brand equity. Brand equity also significantly mediated the relationships between brand loyalty, preference and repurchase intentions. The integrated model produced high explanatory powers with brand equity (67.8%), brand preference (71.7%), brand loyalty (63.2%) and repurchase intentions (54.2%).

The study extends a brand personality-loyalty model through integrating two other models that provided marketing offerings and brand equity outcomes. It demonstrates that a stream of profitable customers' responses awaits a retailer who holds both brand and customer mindsets by building admired brand personalities while providing desired marketing offerings.