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This paper examines the determinants of concurrent adoption of farm risk management strategies by rice growers in two different ecosystems of Telangana agriculture-irrigated and rainfed ecosystems.

The primary data have been collected from the rice growers in two different ecosystems, and after checking the variance inflation factor (VIF) for controlling multicollinearity, a multinomial logit model has been used to examine the determinants of concurrent adoption of coping strategies by rice growers.

The study finds that adopting one risk management strategy persuades farmers to embrace other strategies, reducing the risk in agriculture between the two ecosystems. Among the determinants, farmers' age, education, contact with extension services, irrigation sources, livestock income, total farm income, crop loss reasons, and crop insurance awareness significantly influence the adoption of various risk management measures. However, considerable heterogeneity is found among the driving forces across the rice ecosystems.

The major policy implications that can be drawn from the analysis are increased access to information through government-funded extension services and the provision of alternative risk management technologies, such as drought-resistant or flood-resistant seeds, farmers' field schools and increased provision of crop insurance, farmer-friendly agriculture extension services, and farm investment support, are critical for assisting farmers managing risks. In addition, however, there should be ecosystem-specific policies to tackle the ecosystem heterogeneity.

This paper is very timely and entails some relevant policy implications for the development of Indian agriculture.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

The present study provides evidence on export advantages of horticultural commodities based on competitiveness, trade balance and seasonality dimensions.

The study delineated horticultural commodities in terms of comparative advantage, examined temporal shifts in export advantages (mapping) and estimated seasonality. Product mapping was carried out using the Revealed Symmetric Comparative Advantage (RSCA) and Trade Balance Index (TBI). Seasonal advantages were examined through a graphical approach along with the objective tests, namely, modified QS-test (QS), Friedman-test (FT) and using a seasonal dummy.

Cucumbers/gherkins, onions, preserved vegetables, fresh grapes, shelled cashew nuts, guavas, mangoes, and spices emerged as the most favorable horticultural products. India has a strong seasonal advantage in dried onions, cucumber/gherkins, shelled cashew nut, dried capsicum, coriander, cumin, and turmeric. The untapped potential in horticulture can be addressed by handling the trade barriers effectively, particularly the sanitary and phytosanitary issues, affecting the exports. Proper policies must be enacted to facilitate the investment in advanced agricultural technologies and logistics to ensure the desired quality and cost effectiveness.

Commodity-specific studies on value chain analysis would provide valuable insights into the issues hindering exports and realizing the untapped export potential.

There is no holistic and recent study illustrating the horticulture export advantages covering a large number of commodities in the Indian context. The study would be helpful to the stakeholders for drawing useful policy implications.

The purpose of this paper is to ascertain if practising healthy lifestyles improves the technical efficiency of farms in Kwara state, Nigeria. In theory, all deviations from the optimum level of output are due to random effects and inefficiency of producers in which their health plays a key part and is dependent on the kind of lifestyle practiced whether healthy or unhealthy.

Cross-sectional data were employed through a three-staged sampling technique to pick 320 arable crop farmers across the state using a well-defined questionnaire. Data analysis was carried out using descriptive statistics, healthy lifestyles index (HLI), stochastic production frontier (SPF) and propensity score matching (PSM).

First, the analysis showed that about one-third of the sampled arable crop farmers practised healthy lifestyles. Second, the average technical efficiency of arable crop production for farmers who practised a healthy lifestyle was 0.893, and the level of technical inefficiency of the farms was determined by health-related lifestyle status, number of day's illness and educational level. Third, technical efficiency was improved by 0.00431067 for farms whose farmers practised a healthy lifestyle.

Rather than seeing that technical efficiencies of farms are attributed to farm characteristics, inputs used and socioeconomic characteristics alone, the findings suggest that technical inefficiencies of arable crop farmers were also due to the kind of lifestyle practised, which was evidenced in the increased efficiency for farmers who practised healthy lifestyle.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0353

Industry 4.0 has an inimitable potential to create competitive advantages for the apparel industry by enhancing productivity, production, profitability, efficiency and effectiveness. This study, thus, aims to assess the digitalisation level of the Tanzanian apparel industry through the Industry 4.0 perspectives.

A mixed-methods-based approach was deployed. This study deployed semi-structured interviews, document review and observation methods for the qualitative approach. For the quantitative approach, closed-ended questionnaires were used to ascertain the digitalisation levels and maturity level of the textiles and apparel (T&A) factories and small and medium-sized textile enterprises in Tanzania. The sample size was 110, with participants engaged through the purposive sampling technique.

Industry 4.0 frameworks evolved into practices mainly since 2011 in several service and manufacturing industries globally. For Tanzania, the findings indicate that the overall maturity level of the T&A industries is 2.5 out of 5.0, demonstrating a medium level of adoption. Thus, the apparel industries are not operating under the industry 4.0 framework; they are operating within the third industrial revolution – Industry 3.0 – framework. For such industries to operate within the fourth industrial revolution – Industry 4.0 – that is only possible if there is significantly well-developed industrial infrastructure, availability of engineering talent, stable commercial partnerships, demand from the marketplace and transactional relationship with customers.

This study’s limitations include: firstly, Industry 4.0 is an emerging area; this resulted in limited theoretical underpinnings in the Tanzanian perspectives. Secondly, the studied industries may not suffice the need to generalise the findings for the entire country, thus needing another study.

Although Industry 4.0 conceptual frameworks have been on trial in several industries since 2011, this is amongst the first empirical research on Industry 4.0 in the Tanzanian apparel industry that assesses the digitalisation levels.

This study empirically examines the impact of climate change and agricultural research and development (R&D) as well as their interaction on agricultural productivity in 12 selected Asian and Pacific countries over the period of 1990–2018.

Various estimation methods for panel data, including Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and two-step System Generalized Method of Moments (SGMM) were used.

Results show that both proxies of climate change – temperature and precipitation – have negative impacts on agricultural productivity. Notably, agricultural R&D investments not only increase agricultural productivity but also mitigate the detrimental impact of climate change proxied by temperature on agricultural productivity. Interestingly, climate change proxied by precipitation initially reduces agricultural productivity until a threshold of agricultural R&D beyond which precipitation increases agricultural productivity.

The findings imply useful policies to boost agricultural productivity by using R&D in the context of rising climate change in the vulnerable continent.

This study contributes to the literature in two ways. First, this study examines how climate change affects agricultural productivity in Asian and Pacific countries – those are most vulnerable to climate change. Second, this study assesses the role of R&D in improving agricultural productivity as well as its moderating effect in reducing the harmful impact of climate change on agricultural productivity.

A better understanding of the determinants of demand through accurate estimates of the elasticity of import demand can help policymakers and exporters improve their market access and competitiveness. This study analyzed the EU's demand for imported potato from major suppliers between 1994 and 2018, with the aim to evaluate the competitiveness of Egyptian potato.

This study adopted an import-differentiated framework to investigate demand relationships among the major potato suppliers to the EU's. To evaluate the competitiveness of Egyptian potato on the EU market, expenditure and price demand elasticities for various suppliers were calculated and compared.

The empirical results indicated that as income allocation of fresh potatoes increases, the investigated EU markets import more potatoes from other suppliers compared to imports from Egypt. The results show that EU importers may switch to potato imports from other suppliers as the import price of Egyptian potatoes increases, which enter the EU markets before domestically produced potatoes are harvested.

Due to data unavailability, the present study relied on yearly data on quantities and prices of EU potato imports. A higher frequency of observations should allow for considering seasonal effects, and thereby providing a more transparent picture of market dynamics and demand behavior of EU countries with respect to potato import from various sources of origin.

The study used a system-wide and source differentiated approach to analyze import demand. In particular, the empirical approach allowed for comparing different demand models (AIDS, Rotterdam, NBR and CBS) to filter out the superior and most suitable model for that data because the suitability and performance of a demand model depends rather on data than on universal criteria.

This paper aims to investigate how and when visual referents in brand visual aesthetics (i.e. colours, shapes, patterns and materials) serve as design applications that enable consumer diasporic identity.

This paper uses an innovative methodology that triangulates 58 in-depth interviews with diasporic consumers, 9 interviews with brand managers and designers and a visual analysis of brands (food retailer, spices and nuts, skincare, hair and cosmetics, ice cream and wine) to provide a view of the phenomenon from multiple perspectives.

This study illustrates how and when particular applications and compositions of product and design referents support diasporic identity for Middle Eastern consumers living outside the Middle East. Specifically, it illustrates how the design applications of harmonising (applying separate ancestral homeland and culture of living product and design referents simultaneously), homaging (departing from the culture of living product and design referents with a subtle tribute to ancestral homeland culture) and heritaging (departing from the ancestral homeland culture product and design referents with slight updates to a culture of living style) can enable diasporic identity in particular social situations.

Although applied to the Middle Eastern diaspora, this research opens up interesting avenues for future research that assesses diasporic consumers’ responses to brands seeking to use visual design to engage with this market. Moreover, future research should explore these design applications in relation to issues of cultural appreciation and appropriation.

The hybrid design compositions identified in this study can provide brand managers with practical tools for navigating the design process when targeting a diasporic segment. The design applications and their consequences are discussed while visually demonstrating how they can be crafted.

While previous research mainly focused on how consumption from the ancestral homeland occurred, to the best of the authors’ knowledge, this study is the first to examine how hybrid design compositions that combine a diaspora’s ancestral homeland culture and their culture of living simultaneously and to varying degrees resonate with diasporic consumers.

This paper's purpose is to explore the current interest and knowledge that UK consumers hold around agroforestry. Despite the many reported benefits of agroforestry systems, uptake in the UK, as well as other temperate nations, has been low. As the consumer has a role to play in the transition of agriculture to methods that are more environmentally friendly it is vital to have an understanding of their perceptions. Yet to date no work has looked at agroforestry from the perspective of the UK consumer.

An online survey was conducted using a convenience sample accessed by floating a link through social media and messaging apps. The survey was also shared to the members of a private Facebook group associated with an organic vegetable box service. A mix of multiple choice and open text boxes were used. The survey received 139 responses.

Non-parametric tests indicate that this sample of UK consumers would be mostly likely to buy, and willing to pay more for, agroforestry produce; and the sample showed a split group regarding familiarity. Inductive thematic analysis of the qualitative data highlighted some important barriers to the purchase as well as capturing a snapshot of this sample's perceptions.

This paper presents, to the authors knowledge, the first set of data regarding a sample of UK consumers' perspective of agroforestry produce. The findings could bolster producers' confidence in adopting agroforestry practices, but also highlight the need for policymakers to bolster consumer support through parallel means.

This study aims to investigate the determinants of United Arab Emirates (UAE) and Qatar consumers’ perceptions of organic food.

Using a survey approach and focusing on six known determinants identified from empirical studies, data were analysed using a mean difference analysis and a multi-regression model.

Citizens in both countries had similar access to organic food products, yet consumer perceptions differed significantly. Given the geographical, cultural and topographical proximity and similarities of these countries, differences in the mean values indicate that targeted or bespoke marketing is required to attract customers.

One limitation of this study its sample size that may limit the generalizability of its results. However, the highly statistically significant results offset this to some extent as the differences the authors have demonstrated are likely to be real. These do require confirmation by further similar studies. The study relied on a random sample of respondents who might have exhibited bias in answering questions.

The two countries central to this research study, the UAE and Qatar, have vested interests in supporting the organic food product market that mainly concern supporting and promoting the health of their citizens and the environment. As shown in this paper, the key obstacles preventing consumers’ accessing organic products are availability and price. With appropriate governmental subsidies and logistics support, however, these barriers can be overcome.

If governments are sincere in their declarations that the health and welfare of their citizens is of prime importance, they will support attempts to promote the sale and consumption of organically grown food. The results of this study can help to inform such policies.

This study provides insights into the most important factors that influence consumers’ attitudes towards organic foods. This study fills a gap in the existing research on consumer buying behaviour for organic food in two Middle Eastern countries.