While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term…
Abstract
While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term ecological implications including degradation of biodiversity. It is increasingly recognised that ensuring agricultural sustainability under the changing climatic conditions requires a change in the production system along with necessary policies and institutional arrangements. In this context, this chapter examines if climate-smart agriculture (CSA) can facilitate adaptation and mitigation practices by improving resource utilisation efficiency in India. Such an attempt has special significance as the existing studies have very limited discussions on three main aspects, viz., resource productivity, adaptation practices and mitigation strategies in a comprehensive manner. Based on insights from the existing studies, this chapter points out that CSA can potentially make significant contribution to enhancing resource productivity, adaptation practices, mitigation strategies and food security, especially among the land-constrained farmers who are highly prone to environmental shocks. In this connection, staggered trench irrigation structure has facilitated rainwater harvesting, local irrigation and livelihood generation in West Bengal. However, it is necessary to revisit the existing approaches to promotion of CSA and dissemination of information on the design of local adaptation strategies. This chapter also proposes a change in the food system from climate-sensitive to CSA through integration of technologies, institutions and policies.
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Jeetendra Prakash Aryal, M.L. Jat, Tek B. Sapkota, Arun Khatri-Chhetri, Menale Kassie, Dil Bahadur Rahut and Sofina Maharjan
The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both…
Abstract
Purpose
The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both national and international agricultural organizations to promote CSAPs in India, adoption of these practices is low. This study aims to examine the elements that affect the likelihood and intensity of adoption of multiple CSAPs in Bihar, India.
Design/methodology/approach
The probability and intensity of adoption of CSAPs are analyzed using multivariate and ordered probit models, respectively.
Findings
The results show significant correlations between multiple CSAPs, indicating that their adoptions are interrelated, providing opportunities to exploit the complementarities. The results confirm that both the probability and intensity of adoption of CSAPs are affected by numerous factors, such as demographic characteristics, farm plot features, access to market, socio-economics, climate risks, access to extension services and training. Farmers who perceive high temperature as the major climate risk factor are more likely to adopt crop diversification and minimum tillage. Farmers are less likely to adopt site-specific nutrient management if faced with short winters; however, they are more likely to adopt minimum tillage in this case. Training on agricultural issues is found to have a positive impact on the likelihood and the intensity of CSAPs adoption.
Practical implications
The major policy recommendations coming from of our results are to strengthen local institutions (public extension services, etc.) and to provide more training on CSAPs.
Originality/value
By applying multivariate and ordered probit models, this paper provides some insights on the long-standing discussions on whether farmers adopt CSAPs in a piecemeal or in a composite way.
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Jeetendra Prakash Aryal, M.L. Jat, Tek Bahadur Sapkota, Dil Bahadur Rahut, Munmum Rai, Hanuman S. Jat, P.C. Sharma and Clare Stirling
Conservation agriculture-based wheat production system (CAW) can serve as an ex ante measure to minimize loss due to climate risks, especially the extreme rainfall during the…
Abstract
Purpose
Conservation agriculture-based wheat production system (CAW) can serve as an ex ante measure to minimize loss due to climate risks, especially the extreme rainfall during the wheat production season in India. This study aims to examine whether farmers learn from their past experiences of exposure to climate extremes and use the knowledge to better adapt to future climate extremes.
Design/methodology/approach
The authors used data collected from 184 farmers from Haryana over three consecutive wheat seasons from 2013-2014 to 2015-2016 and multivariate logit model to analyse the driver of the adoption of CAW as an ex ante climate risk mitigating strategies based on their learning and censored Tobit model to analyse the intensity of adoption of CAW as an ex ante climate risk mitigation strategy. Farmer’s knowledge and key barriers to the adoption of CAW were determined through focus group discussions.
Findings
The analysis shows that the majority of farmers who had applied CAW in the year 2014-2015 (a year with untimely excess rainfall during the wheat season) have continued to practice CAW and have increased the proportion of land area allocated to it. Many farmers shifted from CTW to CAW in 2015-2016.
Practical implications
While farmers now consider CAW as an ex ante measure to climate risks, a technology knowledge gap exists, which limits its adoption. Therefore, designing appropriate methods to communicate scientific evidence is crucial.
Originality/value
This paper uses three years panel data from 184 farm households in Haryana, India, together with focus groups discussions with farmers and interviews with key informants to assess if farmers learn adaptation to climate change from past climate extremes.
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Tripti Agarwal, Prarthna Agarwal Goel, Hom Gartaula, Munmum Rai, Deepak Bijarniya, Dil Bahadur Rahut and M.L. Jat
Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop…
Abstract
Purpose
Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks. This study aims to assess how knowledge related to CSAPs, male out-migration, education and income contribute to the determinants of male out-migration and CSAPs adoption and how they respond to household food security.
Design/methodology/approach
Sex-disaggregated primary data were collected from adopter and non-adopter farm families. STATA 13.1 was used to perform principle component analysis to construct knowledge, yield and income indices.
Findings
Yield and income index of adopters was higher for men than women. The probability of out-migration reduced by 21% with adoption of CSAPs. An increase in female literacy by 1 unit reduces log of odds to migrate by 0.37. With every unit increase in knowledge index, increase in log-odds of CSAPs adoption was 1.57. Male:female knowledge gap was less among adopters. Non-adopters tended to reduce food consumption when faced with climatic risks significantly, and the probability of migration increased by 50% with a one-unit fall in the nutrition level, thus compelling women to work more in agriculture. Gender-equitable enhancement of CSAP knowledge is, therefore, key to safeguarding sustainable farming systems and improving livelihoods.
Social implications
The enhancement of gender equitable knowledge on CSAPs is key to safeguard sustainable farming systems and improved livelihoods.
Originality/value
This study is based on the robust data sets of 100 each of male and female from 100 households (n = 200) using well-designed and validated survey instrument. From 10 randomly selected climate-smart villages in Samastipur and Vaishali districts of Bihar, India, together with focus group discussions, the primary data were collected by interviewing both men and women from the same household.
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Barun Deb Pal, Shreya Kapoor, Sunil Saroj, M.L. Jat, Yogesh Kumar and K.H. Anantha
Laser land leveling (LLL) is a climate-smart technology that improves water use efficiency and reduces risk in crop cultivation due to weather variability. Hence, this technology…
Abstract
Purpose
Laser land leveling (LLL) is a climate-smart technology that improves water use efficiency and reduces risk in crop cultivation due to weather variability. Hence, this technology is useful for cultivating water-intensive crops in a sustainable way. Given this background, the state government of Karnataka initiated to promote LLL in drought-prone districts and selected Raichur district for implementation. Moreover, farmers in this district had observed drought situation during monsoon paddy growing season in 2018. Therefore, this study attempts to investigate the importance of LLL technology for paddy cultivation under drought conditions.
Design/methodology/approach
A primary survey with 604 farmer households had been conducted in Raichur in 2018. Among them, 50% are adopters of LLL who have been selected purposively and rest 50% are non-adopters who have grown paddy in the adjacent or nearest plot of the laser-leveled plot. The adoption and causal impact of LLL has been estimated using propensity score matching, coarsened exact matching and endogenous switching regression methods.
Findings
The result reveals a positive and significant impact of LLL on paddy yield and net returns to the farmers. The results indicate an increment of 12 and 16% in rice yield and net income, respectively, for LLL adopters in comparison to the non-adopters of LLL.
Research limitations/implications
The major limitation of the study is that it does not adopt the method of experimental study due to certain limitations; hence, the authors employed a quasi-experimental method to look at the possible impact of adoption of LL.
Originality/value
There have been various agronomic studies focusing on the ex-ante assessment of the LLL. This study is an ex-post assessment of the technology on the crop yield and farmers' income in a dry semi-arid region of India, which, according to the authors, is the first in this approach.
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Isham Alzoubi, Mahmoud Delavar, Farhad Mirzaei and Babak Nadjar Arrabi
This work aims to determine the best linear model using an artificial neural network (ANN) with the imperialist competitive algorithm (ICA-ANN) and ANN to predict the energy…
Abstract
Purpose
This work aims to determine the best linear model using an artificial neural network (ANN) with the imperialist competitive algorithm (ICA-ANN) and ANN to predict the energy consumption for land leveling.
Design/methodology/approach
Using ANN, integrating artificial neural network and imperialist competitive algorithm (ICA-ANN) and sensitivity analysis (SA) can lead to a noticeable improvement in the environment. In this research, effects of various soil properties such as embankment volume, soil compressibility factor, specific gravity, moisture content, slope, sand per cent and soil swelling index on energy consumption were investigated.
Findings
According to the results, 10-8-3-1, 10-8-2-5-1, 10-5-8-10-1 and 10-6-4-1 multilayer perceptron network structures were chosen as the best arrangements and were trained using the Levenberg–Marquardt method as the network training function. Sensitivity analysis revealed that only three variables, namely, density, soil compressibility factor and cut-fill volume (V), had the highest sensitivity on the output parameters, including labor energy, fuel energy, total machinery cost and total machinery energy. Based on the results, ICA-ANN had a better performance in the prediction of output parameters in comparison with conventional methods such as ANN or particle swarm optimization (PSO)-ANN. Statistical factors of root mean square error (RMSE) and correlation coefficient (R2) illustrate the superiority of ICA-ANN over other methods by values of about 0.02 and 0.99, respectively.
Originality/value
A limited number of research studies related to energy consumption in land leveling have been done on energy as a function of volume of excavation and embankment. However, in this research, energy and cost of land leveling are shown to be functions of all the properties of the land, including the slope, coefficient of swelling, density of the soil, soil moisture and special weight dirt. Therefore, the authors believe that this paper contains new and significant information adequate for justifying publication in an international journal.
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Loan T. Le, Luan Duc Tran and Trieu Ngoc Phung
The study investigates determinants of willingness to pay (WTP) for laser land leveling (LLL) technology, its demand heterogeneity across individual farmers and plot…
Abstract
Purpose
The study investigates determinants of willingness to pay (WTP) for laser land leveling (LLL) technology, its demand heterogeneity across individual farmers and plot characteristics and the technology's empirical impact on paddy productivity.
Design/methodology/approach
The study applies the Becker-DeGroote, Marschak style to elicit the WTP for LLL technology and the Cragg model to examine the determinants of the WTP to capture both the demand decision and affordability. The randomized controlled trials (RCT) are incorporated with a production function model to analyze the technology effects on paddy productivity.
Findings
The Cragg model finds that the key demographic and behavioral traits such as age, extension services and risk acceptance significantly influence the adoption decision; however, the plot area, bank and financial capacity become predominant factors in the adoption affordability. The LLL treatment effect results in a statistically significant increase in paddy yield of 6.48%, equivalent to 492,138 kg ha-1.
Research limitations/implications
The analysis underscores the factor complexity, illustrating that the LLL-promoting interventions need to address both the adoption barriers and the enablers for greater affordability. A composite of climate-smart agricultural programs should be employed to facilitate the LLL adoption. The empirical evidence highlights the positive effect on agricultural productivity, potentially offering a significant boost to output and farmer income.
Originality/value
The study contributes to existing literature by analyzing the heterogeneous demand for LLL technology with two distinguishable features of the paddy mono-cropping system and land fragmentation and by incorporating the RCTs alongside a production function for the effects on paddy productivity.
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Tanushree Gupta, Jennifer Fernandes and Susobhan Maiti
Food security emerges when all people always have physical and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for an…
Abstract
Food security emerges when all people always have physical and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for an active and healthy life. The availability of food, access to food, and absorption of food are three key aspects of food security. Considering the above, the initial goal in this chapter is to measure annual growth rate and compound annual growth rate (CAGR) of production of food grains, nutri coarse cereals, total pulses, and nine oilseeds for the period 2011–2021 in India. To estimate per capita availability of Food Grains, Nutri Coarse Cereals, Total Pulses and Nine Oilseeds (in kg) represents the food security in India. The highest production is recorded in between 2011 and 2021 for food grains (315.72), followed by the production of nine oil seeds (36.7), total pulses (27.69), and nutri coarse cereals (26.42). In 2016, the annual growth rate for food grains and nine oilseeds was 9.37 and 23.88%, respectively. It is very evident that the availability per capita has grown from 2011 to 2021. The per capita availability of food grains increased from 206.17 kg in 2011 to 224.30 kg in 2021. The per capita availability of total pulses increased from 13.59 kg in 2011 to 19.67 kg in 2021. The per capita availability of nine oil seeds increased from 23.70 kg in 2011 to 26.78 kg in 2021 which indicates India has managed food security successfully in the last decade.
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Javier Isaac Torres Vergara, Jania Astrid Saucedo Martínez and Daniela Olivo Lucio
In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and…
Abstract
Purpose
In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and sustainability paradigms. In this way, this research aims to identify the attributes that a supply chain (SC) should follow to be resilient and sustainable, and then to evaluate their importance according to industry experts.
Design/methodology/approach
This study suggests a hybrid approach. The authors identified the most commonly used criteria using literature review, and then applied fuzzy Delphi technique (FDT) with the objective of surveying experts to find the attributes used in practice and asked to assess their relevance.
Findings
The resilient-sustainable supply chain (RSSC) is formed by four dimensions: resiliency, economic, environmental and social. A total of 15 criteria are identified, and the most important are visibility, flexibility, supply chain risk management (SCRM) culture, work conditions and communication.
Research limitations/implications
This study used a literature review, so it is subject to a time frame, and the criteria could no longer be relevant as the time and business conditions change. Also, the findings may not be completely applicable throughout different industries, and therefore the finding cannot be replicated to other businesses.
Practical implications
This study will assist decision-makers among other interested parties to construct and/or strengthen an integrated SC that mixes resiliency and sustainability.
Originality/value
This study contributes to the state-of-art by producing a characterization of the resilient and sustainable supply chain for the automotive industry. Also, this research produces a new and holistic framework for resilient and sustainable SCPM supporting the decision-making process.
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Anam Ul Haq Ganie, Arif Mohd Khah and Masroor Ahmad
The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).
Abstract
Purpose
The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).
Design/methodology/approach
This study employs econometric techniques, including Westerlund cointegration tests, cross-sectional augmented distributive lag model (CS-ARDL) and Dumitrescu and Hurlin (DH) causality tests to investigate the relationship between renewable and non-renewable energy consumption, agriculture, economic growth, financial development and carbon emissions in SAE from 1990 to 2019.
Findings
The CS-ARDL test outcome supports the presence of the agriculture-induced EKC hypothesis in SAE. Additionally, through the application of the DH causality test, the study confirms a unidirectional causality running from renewable energy consumption (REC), fossil fuel consumption (FFC), economic growth (GDP) and squared economic growth (GDP2) to carbon dioxide (CO2) emissions.
Research limitations/implications
This study proposes that future research should extend comparisons to worldwide intergovernmental bodies, use advanced econometric methodologies for accurate estimates, and investigate incorporating the service or primary sector into the EKC. Such multidimensional studies can inform various methods for mitigating global climate change and ensuring ecological sustainability.
Originality/value
Environmental degradation has been extensively studied in different regions and countries, but SAE face significant constraints in addressing this issue, and comprehensive studies in this area are scarce. This research is pioneering as it is the first study to investigate the applicability of the agriculture-induced EKC in the South Asian region. By filling this gap in the current literature, the study provides valuable insights into major SAE and their environmental challenges.