Author: rpuri

By

Shubham Anil Durgude

Millets are deeply rooted in the traditions of local farmers of India. For instance, finger millet was a dietary staple in Bihar, and farmers in the northern regions were experts in growing Sanwa or Barnyard millet. Proso millet, known as “Cheena,” was famous for its short growing period, so much so that farmers used to say it could be harvested almost as fast as it grew! But as the years pass, things change. Rice, wheat, and maize became the new favorites, pushing millets to the sidelines. The younger generation has forgotten the old ways.

A New Dawn for Millets

Seeing the value of millets, the team at BISA (Borlaug Institute for South Asia) is on a mission. The BISA team at Samastipur and other farms (in Ludhiana and Jabalpur) are searching for the old knowledge, updating it for today’s challenges, and preparing to put millet back on the food plate again. The good news is that the roots of millet farming run deep in Indian communities. The challenge is to help millets thrive in a world very different from the one they once dominated.

The Challenge: Growing More, Selling Well

When BISA scientists sit down with farmers, one issue remains: millets don’t produce as much as the new popular crops like rice and wheat. This is a real challenge, but BISA is trying to address it. They are developing cutting-edge techniques to boost millet yields. The response from farmers has been overwhelming. They are eager to try these new methods but need support in getting their millet to market at a fair price. Hence, BISA is working with farmers to create groups, provide training, and connect them with buyers. The goal is to make millet farming a profitable, sustainable choice for families across India.

Science in the Field

BISA’s work starts in the fields. Scientists are testing millets in different conditions, figuring out the best ways to plant and care for them in the unique climate of Bihar, MP, Punjab and other states. They know millets are tough and adaptable, perfect for mixing things up in a world where too many farmers grow the same few crops. By providing farmers with customized planting schedules and advice on fitting millets into their existing plans, BISA is making it easy to give millets a try.

Weeds and Nutrients: The Details Matter

Two significant hurdles in growing millets are weeds and nutrients. Weeds can choke out young plants, but few proven strategies exist to control them. BISA is searching for simple, effective ways to manage weeds. At the same time, they’re studying what makes millets tick. Unlike some crops, little is known about what nutrients millets need, how they absorb them, or how fertilizers affect them. By filling these knowledge gaps, BISA can give farmers precise advice to keep their millet healthy and robust.

Finding the Best Millets for BISA sites

BISA does not just work with any millet. They are testing over 400 different types, from local favorites to varieties worldwide, to find the ones that will shine in Indian environments. Some contenders in Bihar include RAU-1 finger millet, DHBM 93 barnyard, and JK-137 Kodo millet. By identifying the top performers, BISA can help farmers get the best results.

Real-Time Advice at Your Fingertips

In today’s world, the best farming involves technology. This is why BISA offers digital advice to millet farmers through its Climate-Resilient Agriculture Program. Imagine getting a message on your phone telling you exactly when to plant, how to control weeds, and what fertilizer to use. This is what farmers get through BISA’s WhatsApp chatbot. From planting to harvest, they get the guidance they need to succeed.

A Healthy, Sustainable Future

Millets are more than just a crop – they are a key to a better future. They are packed with iron, calcium, and fiber, making them a nutrition powerhouse. They are great for women’s health, can help fight anemia and strengthen bones. Because they release sugar slowly, millet is perfect for managing diabetes or heart disease. With millet, BISA is creating an efficient farming system for people and the planet. They are not just growing a crop; they are growing a movement initiated by the Government of India worldwide. With millet, Indian farmers can build a future rooted in heritage but looking toward a greener, healthier tomorrow.

Econometric and statistical methods lead to informed decision-making and safeguards agricultural productivity in the face of climatic hazards in South Asia

By Prem Chand, ICAR-NIAP, India and Kaushik Bora, BISA-CIMMYT, India

Globally, climate extremes are adversely affecting agricultural productivity and farmer welfare. Farmers’ lack of knowledge about adaptation options may further exacerbate the situation. In the context of South Asia, which is home to rural farm-based economies with smallholder populations, tailored adaptation options are crucial to safeguard the region’s agriculture in response to current and future climate challenges. These resilience strategies encompass a range of risk reducing practices such as changing the planting date, conservation agriculture, irrigation, stress-tolerant varieties, crop diversification, and risk transfer mechanisms for example crop insurance. Practices such as enterprise diversification and community water conservation are also potential sector-specific interventions.

The Atlas of Climate Adaptation in South Asian Agriculture (ACASA) aims to identify hazard-linked adaptation options and prioritise them at a granular geographical scale. While doing so, it is paramount to consider the suitability of adaptation options from a socio-economic lens which varies across spatial and temporal dimensions. Further, calculation of scalability parameters such as economic, environmental benefit, and gender inclusivity for prioritized adaptation are important to aid climatic risk management and developmental planning in the subcontinent. Given the credibility of econometric and statistical methods, the key tenets of the approach that are being applied in ACASA are worth highlighting.

Evaluating the profitability of adaptation options

Profitability is among the foremost indicators for the feasible adoption of any technology. The popular metric of profitability evaluation is benefit-to-cost ratio. This is a simple measure based on additional costs and benefits because of adopting new technology. A benefit-to-cost ratio of more than one is considered essential for financial viability. Large-scale surveys such as cost of cultivation and other household surveys can provide cost estimates for limited adaptation options. Given the geographical and commodity spread, ACASA must resort to the meta-analysis of published literature or field trials for adaptation options. For example, a recent paper by International Food Policy Research Institute (IFPRI) based on meta-analysis shows that not all interventions result in a win-win situation with improvements in both tradable and non-tradable outcomes. While no-till wheat, legumes, and integrated nutrient management result in an advantageous outcome, there are trade-offs between the tradable and non-tradable ecosystem services in the cases of directed seed rice, organic manure, and agroforestry[1].

Quantification of adaptation options to mitigate hazards

Past studies demonstrate the usefulness of econometric methods when analyzing the effectiveness of adaptation options such as irrigation, shift in planting time, and crop diversification against drought and heat stress in South Asia. Compared to a simple cost-benefit approach, the adaptation benefits of a particular technology under climatic stress conditions can be ascertained by comparing it with normal weather conditions. The popular methods in climate economics literature are panel data regression and treatment-based models. Subject to data availability, modern methods of causal estimation and machine learning can be used to ascertain the robust benefits of adaptation options. Such studies, though available in literature, have compared limited adaptation options. A study by the Indian Council of Agricultural Research-National Institute of Agricultural Economics and Policy Research (ICAR-NIAP), based on ‘Situation Assessment Survey of Agricultural Households’ of National Sample Survey Office (NSSO), concluded that though crop insurance and irrigation effectively improve farm income and reduce farmers’ exposure to downside risk, irrigation is more effective than crop insurance[2].

Statistical models for spatial interpolation of econometric estimates

Since ACASA focuses on gridded analysis, an active area of statistical application is the spatial interpolation or downscaling of results to a more granular scale. Many indicators used for risk characterization are available at coarser geographical units or points from surveys. Kriging is a spatial interpolation method where there is no observed data. Apart from spatial interpolation of observed indicators, advanced Kriging methods can be potentially used to interpolate or predict the estimates of the econometric model.

 ACASA’s approach involves prioritizing adaptation options based on suitability, scalability, and gender inclusivity. Econometric and statistical methods play a crucial role in evaluating the profitability and effectiveness of various adaptation strategies from real world datasets. Despite challenges such as limited observational data and integration of econometric and statistical methods, ACASA can facilitate informed decision-making in climate risk management and safeguard agricultural productivity in the face of climatic hazards.

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[1] Kiran Kumara T M, Birthal PS, Chand D and Kumar A. 2024. Economic Valuation of Ecosystem Services of Selected Interventions in Agriculture in India. IFPRI Discussion Paper 02250, IFPRI-South Asia Regional Office, New Delhi.

[2] Birthal PS, Hazrana J, Negi DS and Mishra A. 2022. Assessing benefits of crop insurance vis-a-vis irrigation in Indian agriculture. Food Policy 112:102348. https://doi.org/10.1016/j.foodpol.2022.102348

Gridded crop modelling builds an understanding of how climate change impacts crops, helping researchers to adapt agricultural methods and combat food insecurity.

Global temperatures are projected to warm by between 1.5-2 degrees Celsius by the year 2050, and 2-4 degrees Celsius by 2100. This is likely to change precipitation patterns, which will impact crop yields, water availability, food security, and agricultural resilience.

To prepare for these challenges, the Atlas of Climate Adaptation in South Asian Agriculture (ACASA) project use process-based simulation models that can predict crop growth, development, and yield in order to understand the response of crops to climate change. Models such as Decision Support System for Agrotechnology Transfer (DSSAT), InfoCrop, and Agricultural Production Systems Simulator (APSIM) facilitate the field scale study of the biophysical and biochemical processes of crops under various environmental conditions, revealing how they are affected by changing weather patterns.

The ACASA team, along with experts from Columbia University and the University of Florida, met for a three-day workshop in January 2024 to boost the work on spatial crop modelling. The aim was to design modelling protocol through a hands-on demonstration on high-performance computers. . When scientifically executed, gridded spatial crop modelling – even though complex and data-intensive – can be a great way to frame adaptation and mitigation strategies for improving food security, which is one of the ACASA project’s goals.

Decisions on data

The group decided to use DSSAT, APSIM, and InfoCrop for simulating the impact of climatic risks on crops such as rice, wheat, maize, sorghum millet, pigeon pea, chickpea, groundnut, soybean, mustard, potato, cotton, and more. They chose harmonized protocols across all three models with standard inputs, such as conducting simulations at 0.05 degrees. The model input data about weather, soil, crop varietal coefficients and crop management are being collected and processed for model input formats at 5 kilometer (km) spatial resolution.

A Python version called DSSAT-Pythia is now available to accelerate spatial and gridded applications. The programming for implementing InfoCrop on the Pythia platform is in progress. InfoCrop has been proven in India for past yield estimations, climate change spatial impact, and adaptation assessments for 12 crops.

For other crucial modelling components, a work plan was created including developing regional crop masks; crop zones based on mega-commodity environments as defined by CGIAR; production systems; crop calendars; and irrigated areas by crop. Genetic coefficients will then be calculated from measured past values and recent benchmark data of varietal units.

With this information, several adaptation options will be simulated, including changes in planting dates, stress-tolerant varieties, irrigation, and nitrogen fertilizer (quantity, methods, and technology), residue/mulching, and conservation tillage. The team will evaluate impact and adaptation benefits on yields, water, and nitrogen use efficiency based on the reported percentage change from the baseline data.

As the project progresses, this work will make strides towards realizing food security for the planet and increasing the resilience of smallholder farming practices.

Authors: Anooja Thomas, University of Florida; Apurbo K Chaki, BARI, Bangladesh; Gerrit Hoogenboom, University of Florida; S Naresh Kumar, ICAR-IARI, India