An ex ante life cycle assessment of wheat with high biological nitrification inhibition capacity.

It is essential to increase food production to meet the projected population increase while reducing environmental loads. Biological nitrification inhibition (BNI)-enabled wheat genetic stocks are under development through chromosome engineering by transferring chromosomal regions carrying the BNI trait from a wild relative (Leymus racemosus (Lam.) Tzvelev) into elite wheat varieties; field evaluation of these newly developed BNI-wheat varieties has started. Ten years from now, BNI-enabled elite wheat varieties are expected to be deployed in wheat production systems. This study aims to evaluate the impacts of introducing these novel genetic solutions on life cycle greenhouse gas (LC-GHG) emissions, nitrogen (N) fertilizer application rates and N-use efficiency (NUE). Scenarios were developed based on evidence of nitrification inhibition and nitrous oxide (N2O) emission reduction by BNI crops and by synthetic nitrification inhibitors (SNIs), as both BNI-wheat and SNIs slow the nitrification process. Scenarios including BNI-wheat will inhibit nitrification by 30% by 2030 and 40% by 2050. It was assumed that N fertilizer application rates can potentially be reduced, as N losses through N2O emissions, leaching and runoff are expected to be lower. The results show that the impacts from BNI-wheat with 40% nitrification inhibition by 2050 are assessed to be positive: a 15.0% reduction in N fertilization, a 15.9% reduction in LC-GHG emissions, and a 16.7% improvement in NUE at the farm level. An increase in ammonia volatilization had little influence on the reduction in LC-GHG emissions. The GHG emissions associated with N fertilizer production and soil N2O emissions can be reduced between 7.3 and 9.5% across the wheat-harvested area worldwide by BNI-wheat with 30% and 40% nitrification inhibition, respectively. However, the present study recommends further technological developments (e.g. further developments in BNI-wheat and the development of more powerful SNIs) to reduce environmental impacts while improving wheat production to meet the increasing worldwide demand.

Projecting wheat demand in China and India for 2030 and 2050: Implications for food security.

Introduction: The combined populations of China and India were 2.78 billion in 2020, representing 36% of the world population (7.75 billion). Wheat is the second most important staple grain in both China and India. In 2019, the aggregate wheat consumption in China was 96.4 million ton and in India it was 82.5 million ton, together it was more than 35% of the world's wheat that year. In China, in 2050, the projected population will be 1294-1515 million, and in India, it is projected to be 14.89-1793 million, under the low and high-fertility rate assumptions. A question arises as to, what will be aggregate demand for wheat in China and India in 2030 and 2050? Methods: Applying the Vector Error Correction model estimation process in the time series econometric estimation setting, this study projected the per capita and annual aggregate wheat consumptions of China and India during 2019-2050. In the process, this study relies on agricultural data sourced from the Food and Agriculture Organization of the United States (FAO) database (FAOSTAT), as well as the World Bank's World Development Indicators (WDI) data catalog. The presence of unit root in the data series are tested by applying the augmented Dickey-Fuller test; Philips-Perron unit root test; Kwiatkowski-Phillips-Schmidt-Shin test, and Zivot-Andrews Unit Root test allowing for a single break in intercept and/or trend. The test statistics suggest that a natural log transformation and with the first difference of the variables provides stationarity of the data series for both China and India. The Zivot-Andrews Unit Root test, however, suggested that there is a structural break in urban population share and GDP per capita. To tackle the issue, we have included a year dummy and two multiplicative dummies in our model. Furthermore, the Johansen cointegration test suggests that at least one variable in both data series were cointegrated. These tests enable us to apply Vector Error Correction (VEC) model estimation procedure. In estimation the model, the appropriate number of lags of the variables is confirmed by applying the "varsoc" command in Stata 17 software interface. The estimated yearly per capita wheat consumption in 2030 and 2050 from the VEC model, are multiplied by the projected population in 2030 and 2050 to calculate the projected aggregate wheat demand in China and India in 2030 and 2050. After projecting the yearly per capita wheat consumption (KG), we multiply with the projected population to get the expected consumption demand. Results: This study found that the yearly per capita wheat consumption of China will increase from 65.8 kg in 2019 to 76 kg in 2030, and 95 kg in 2050. In India, the yearly per capita wheat consumption will increase to 74 kg in 2030 and 94 kg in 2050 from 60.4 kg in 2019. Considering the projected population growth rates under low-fertility assumptions, aggregate wheat consumption of China will increase by more than 13% in 2030 and by 28% in 2050. Under the high-fertility rate assumption, however the aggregate wheat consumption of China will increase by 18% in 2030 and nearly 50% in 2050. In the case of India, under both low and high-fertility rate assumptions, aggregate wheat demand in India will increase by 32-38% in 2030 and by 70-104% in 2050 compared to 2019 level of consumption. Discussions: Our results underline the importance of wheat in both countries, which are the world's top wheat producers and consumers, and suggest the importance of research and development investments to maintain sufficient national wheat grain production levels to meet China and India's domestic demand. This is critical both to ensure the food security of this large segment of the world populace, which also includes 23% of the total population of the world who live on less than US $1.90/day, as well as to avoid potential grain market destabilization and price hikes that arise in the event of large import demands.

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

Economic benefits of blast-resistant biofortified wheat in Bangladesh: The case of BARI Gom 33.

The first occurrence of wheat blast in 2016 threatened Bangladesh's already precarious food security situation. The Bangladesh Agricultural Research Institute (BARI), together with the International Maize and Wheat Improvement Center (CIMMYT) developed and released the wheat variety BARI Gom 33 that is resistant to wheat blast and other common diseases. The new variety provides a 5-8% yield gain over the available popular varieties, as well as being zinc enriched. This study examines the potential economic benefits of BARI Gom 33 in Bangladesh. First, applying a climate analogue model, this study identified that more than 55% of the total wheat-growing area in Bangladesh (across 45 districts) is vulnerable to wheat blast. Second, applying an ex-ante impact assessment framework, this study shows that with an assumed cumulative adoption starting from 2019-20 and increasing to 30% by 2027-28, the potential economic benefits of the newly developed wheat variety far exceeds its dissemination cost by 2029-30. Even if dissemination of the new wheat variety is limited to only the ten currently blast-affected districts, the yearly average net benefits could amount to USD 0.23-1.6 million. Based on the findings, international funder agencies are urged to support the national system in scaling out the new wheat variety and wheat research in general to ensure overall food security in Bangladesh and South Asia.

Averting wheat blast by implementing a 'wheat holiday': In search of alternative crops in West Bengal, India.

The emergence of wheat-blast in Bangladesh in the 2015-16 wheat (Triticum aestivum L.) crop threatens the food security of South Asia. A potential spread of the disease from Bangladesh to India could have devastating impacts on India's overall food security as wheat is its second most important staple food crop. West Bengal state in eastern India shares a 2,217 km-long border with Bangladesh and has a similar agro-ecology, enhancing the prospects of the disease entering India via West Bengal. The present study explores the possibility of a 'wheat holiday' policy in the nine border districts of West Bengal. Under the policy, farmers in these districts would stop wheat cultivation for at least two years. The present scoping study assesses the potential economic feasibility of alternative crops to wheat. Of the ten crops considered, maize, gram (chickpea), urad (black gram), rapeseed and mustard, and potatoes are found to be potentially feasible alternative crops. Any crop substitution would need support to ease the transition including addressing the challenges related to the management of alternative crops, ensuring adequate crop combinations and value chain development. Still, as wheat is a major staple, there is some urgency to support further research on disease epidemiology and forecasting, as well as the development and dissemination of blast-resistant wheat varieties across South Asia.

Threat of wheat blast to South Asia's food security: An ex-ante analysis.

New biotic stresses have emerged around the globe over the last decades threatening food safety and security. In 2016, scientists confirmed the presence of the devastating wheat-blast disease in Bangladesh, South Asia-its first occurrence outside South America. Severely blast-affected wheat fields had their grain yield wiped out. This poses a severe threat to food security in a densely-populated region with millions of poor inhabitants where wheat is a major staple crop and per capita wheat consumption has been increasing. As an ex ante impact assessment, this study examined potential wheat-blast scenarios in Bangladesh, India, and Pakistan. Based on the agro-climatic conditions in the epicenter, where the disease was first identified in Bangladesh in 2016, this study identified the correspondingly vulnerable areas in India, Pakistan and Bangladesh amounting to 7 million ha. Assuming a conservative scenario of 5-10% for blast-induced wheat production loss, this study estimated the annual potential wheat loss across the sampled countries to be 0.89-1.77 million tons, equivalent to USD 132-264 million. Such losses further threaten an already-precarious national food security, putting pressure on wheat imports and wheat prices. The study is a call for action to tackle the real wheat-blast threat in South Asia.

Factors influencing adoption of manure separation technology in The Netherlands.

Manure separation technologies are essential for sustainable livestock operations in areas with high livestock density as these technologies result in better utilization of manure and reduced environmental impact. Technologies for manure separation have been well researched and are ready for use. Their use, however, has been limited to the Netherlands. This paper investigates the role of farm and farmer characteristics and farmers' attitudes toward technology-specific attributes in influencing the likelihood of the adoption of mechanical manure separation technology. The analysis used survey data collected from 111 Dutch dairy farmers in 2009. The results showed that the age and education level of the farmer and farm size are important variables explaining the likelihood of adoption. In addition to farm and farmer characteristics, farmers' attitudes toward the different attributes of manure separation technology significantly affect the likelihood of adoption. The study generates useful information for policy makers, technology developers and distributors in identifying the factors that impact decision-making behaviors of farmers.