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Joshi, P.K.

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Joshi
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P.K.
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Joshi, P.K.
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0000-0002-9637-1767

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2005 - 200912010 - 20182
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Now showing 1 - 4 of 4
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    Climate-smart agriculture in Asia-Pacific: role in identifying country priorities
    (CIMMYT, [2021]) Aggarwal, P.K.; Khatri-Chhetri, A.; Shirsath, P.B.; Jat, M.L.; Joshi, P.K.
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    Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions
    (Elsevier, 2018) Dunnett, A.; Shirsath, P.B.; Aggarwal, P.K.; Thornton, P.; Joshi, P.K.; Pal, B.D.; Khatri-Chhetri, A.; Ghosh, J.
    Climate-smart interventions in agriculture have varying costs and environmental and economic impacts. Their implementation requires appropriate investment decisions by policy makers that are relevant for current as well as future scenarios of agro-ecology, climate and economic development. Decision support tools are therefore needed to assist different stakeholders to prioritize and hence implement appropriate strategic interventions. These interventions transform agriculture ecosystems to climate-resilient, adaptive and efficient. This paper outlines the mathematical modelling framework of one such, the Climate Smart Agricultural Prioritization (CSAP) toolkit. This toolkit employs a dynamic, spatially-explicit multi-objective optimization model to explore a range of agricultural growth pathways coupled with climate-adaptation strategies to meet agricultural development and environmental goals. The toolkit consists of three major components: (i) land evaluation including assessment of resource availability, land suitability, yield and input-output estimation for all promising crop production practices and technologies for key agro-ecological units; (ii) formulation of scenarios based on policy views and development plans; and (iii) land-use optimization in the form of linear programming models. Climate change and socio-economic drivers condition the land evaluation, technological input-output relations, and specification of optimization objectives that define modelled scenarios. By integrating detailed bottom-up biophysical, climate impact and agricultural-emissions models, CSAP is capable of supporting multi-objective analysis of agricultural production goals in relation to food self-sufficiency, incomes, employment and mitigation targets, thus supporting a wide range of analyses ranging from food security assessment to environmental impact assessment to preparation of climate smart development plans.
    Publication
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    Farmers' prioritization of climate-smart agriculture (CSA) technologies
    (Elsevier, 2017) Khatri-Chhetri, A.; Aggarwal, P.K.; Joshi, P.K.; Vyas, S.
    Addressing climate change impacts on agriculture is special challenge. There are number of factors that influence the extent to which farmers in a particular location adopt CSA technologies. This study applied a participatory assessment method to assess farmers' preferences and willingness-to-pay for selected CSA practices and technologies in diverse rainfall zones. The study found that farmers' preferences for CSA technologies are marked by some commonalities as well as differences according to their socio-economic characteristics and rainfall zones. The most preferred technologies by local farmerswere crop insurance, weather-based crop agro-advisories, rainwater harvesting, site-specific integrated nutrient management, contingent crop planning and laser land levelling. The results also indicate that farmers' preferences and willingness-to-pay are influenced by technologies and their cost of implementation. This study shows the potential for using a participatory CSA prioritization approach to provide information on climate change adaptation planning at local level.
    Publication
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    Maize in India: production systems, constraints, and research priorities
    (CIMMYT, 2005) Joshi, P.K.; Singh, N.P.; Singh, N.N.; Gerpacio, R.V.; Pingali, P.L.
    Maize is a promising substitute crop allowing diversification from the rice-wheat system in the upland areas of India. The crop has high production potential, provided the available improved hybrids and composites reach the farming community. This study found that major biotic production constraints were Echinocloa, Cynodon dactylon, rats, and termites, which reduced maize production levels by more than 50%. Other important abiotic and biotic stresses listed in descending order of importance were: caterpillars, water stress, stem borers, weevils, zinc deficiency, rust, seed/seedling blight, cutworm, and leaf blight. Non-availability of improved seeds, inadequate input markets, ineffective technology dissemination, and lack of collective action were the principal socio-economic constraints.
    Publication