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This paper explores through Schumacher's perspective on ‘the proper use of land’: the reasons for, and the means and consequences of, monitoring soil condition in managing agricultural landscapes sustainably. This particular perspective illustrates its argument with soil monitoring initiatives operating at various scales within the global agricultural context. Schumacher's land management goals are health, beauty and permanence, yet productivity is the goal most land managers focus on. The chosen indicators for soil monitoring need to reflect these goals. Hence, the indicators of choice for monitoring soil condition are attributes that can be: easily measured, improve soil productivity or protect the soil. Often attributes that have intrinsic ‘beauty’ (value), maintain ‘health’ (function) in ecosystems and are difficult to measure are ignored as soil condition indicators. The usefulness of information gained through monitoring soil condition is to make decisions that will be relevant for varied audiences and at different points in the decision-making process.

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.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

There is a connection between cotton production and the Aral Sea disaster in Uzbekistan. Large-scale cotton production utilizes the practices of conventional agriculture and has severe environmental consequences in arid regions. Some of these problems, such as salinization, currently exist in Uzbekistan as a result of cotton production and these conventional farming practices. This chapter is a review of cotton production, the environmental consequences of conventional agriculture, and its relationship to the Aral Sea Disaster. Storm water management with biofiltration, sustainable farming practices, efficient irrigation, ecological horticultural practices, and a water conservation program are remedies that can help to reduce the environmental degradation caused by cotton production and restore some of the water resources in Uzbekistan.

There is an urgent need to develop climate-smart agrosystems capable of mitigating climate change and adapting to its effects. Conventional agricultural practices prevail in Mauritius, whereby synthetic chemical fertilizers, pesticides and insecticides are used. It should be noted that Mauritius remains a net-food importing developing country of staple food such as cereals and products, roots and tubers, pulses, oil crops, vegetables, fruits and meat (FAO, 2011). In Mauritius, the agricultural sector faces extreme weather conditions like drought or heavy rainfall. Moreover, to increase the crop yields, farmers tend to use 2.5 times the prescribed amount of fertilizers in their fields. These excess fertilizers are washed away during heavy rainfall and contaminate lakes and river waters. By using smart irrigation and fertilization system, a better management of soil water reserves for improved agricultural production can be implemented. Soil Nitrogen, Phosphorus and Potassium (NPK) content, humidity, pH, conductivity and moisture data can be monitored through the cloud platform. The data will be processed at the level of the cloud and an appropriate mix of NPK and irrigation will be used to optimise the growth of the crops. Machine learning algorithms will be used for the control of the land drainage, fertilization and irrigation systems and real time data will be available through a mobile application for the whole system. This will contribute towards the Sustainable Development Goals (SDGs): 2 (Zero Hunger), 11 (Sustainable cities and communities), 12 (Responsible consumption and production) and 15 (Life on Land). With this project, the yield of crops will be boosted, thus reducing the hunger rate (SDG 2). On top of that, this will encourage farmers to collect the waters and reduce fertilizer consumption thereafter sustaining the quality of the soil on which they are cultivating the crops, thereby increasing their yields (SDG 15).

This study examines how small famers in southern Costa Rica think about environmental issues and climate change in agricultural practice and sustainability, assuming local models about these issues must be understood as dynamic representations which are modified in response to both changing conditions and new ideas.

Ethnographic research in Coto Brus, in southern Costa Rica, in the late 1990s and mid-2000s forms the basis of this analysis.

Farmers in this area understand environmental issues in terms of local controllable circumstances around environmental issues. This puts them at odds with government agents and outside researchers, who offer solutions based on their perceptions of the situation rather than farmer perceptions. Farmer resistance to proposals which do not solve problems that farmers see as important frustrates government representatives, who perceive these actions to be arbitrary.

The research is quite limited in time and space, giving only a quick snapshot of a complicated and ongoing problem.

Different models for understanding problems and a lack of understanding of how other stakeholders perceive the situation has made it harder to improve the sustainability of agriculture in southern Costa Rica. Similar dynamics can be seen elsewhere and suggest that a greater attempt to engage with local models and understandings can improve development and acceptance of innovations and improvements.

The exploration of conflicts between local and national/scholarly understandings of environmental issues suggests a way forward, engaging with local understandings and concerns to change behavior.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

Of all the natural disasters, drought is the most gradual and the most hard to predict. However, this insidious disaster continually affects the lives and livelihoods of farmers living in drought-affected areas. The northwestern part of Bangladesh is recognized as being more severely affected by drought than the rest of the country, as drought is a recurring event in this area. It has substantial impacts on agriculture and causes great suffering for farmers – in particular, poor and small farmers, who are more vulnerable to drought. Therefore, this study tries to illustrate farmers’ existing coping practices with regard to drought. It also addresses their prioritized adaptation practices, which are based on local context and available resources. This study not only focuses on the implementation of these adaptation practices from the national to the local level, but it also mentions various roles of stakeholders and a definite timeframe for each adaptation practice.