Rice blast (Magnaporthe oryzae) is a key concern in combating global food insecurity given the disease is responsible for approximately 30% of rice production losses globally—the equivalent of feeding 60 million people. These losses increase the global rice price and reduce consumer welfare and food security. Rice is the staple crop for more than half the world’s population so any reduction in rice blast would have substantial beneficial effects on consumer livelihoods. In 2012, researchers in the US began analyzing the feasibility of creating blast-resistant rice through cisgenic breeding. Correspondingly, our study evaluates the changes in producer, consumer, and environmental welfare, if all the rice produced in the Mid-South of the US were blast resistant through a process like cisgenics, using both international trade and environmental assessment modeling. Our results show that US rice producers would gain 69.34 million dollars annually and increase the rice supply to feed an additional one million consumers globally by eliminating blast from production in the Mid-South. These results suggest that blast alleviation could be even more significant in increasing global food security given that the US is a small rice producer by global standards and likely experiences lower losses from blast than other rice-producing countries because of its ongoing investment in production technology and management. Furthermore, results from our detailed life cycle assessment (LCA) show that producing blast-resistant rice has lower environmental (fossil fuel depletion, ecotoxicity, carcinogenics, eutrophication, acidification, global warming potential, and ozone depletion) impacts per unit of rice than non-blast resistant rice production. Our findings suggest that any reduction in blast via breeding will have significantly positive impacts on reducing global food insecurity through increased supply, as well as decreased price and environmental impacts in production.

Understanding extreme weather impacts on staple crops such as wheat is vital for creating adaptation strategies and increasing food security, especially in dryland cropping systems across Southern Africa. This study analyses heat impacts on wheat using daily weather information and a dryland wheat dataset for 71 cultivars across 17 locations in South Africa from 1998 to 2014. We estimate temperature impacts on yields in extensive regression models, finding that extreme heat drives wheat yield losses, with an additional 24 h of exposure to temperatures above 30 °C associated with a 12.5% yield reduction. Results from a uniform warming scenario of +1 °C show an average wheat yield reduction of 8.5%, which increases to 18.4% and 28.5% under +2 and +3 °C scenarios. We also find evidence of differences in heat effects across cultivars, which suggests warming impacts may be reduced through the sharing of gene pools amongst wheat breeding programs.

Determining a precise nitrogen fertilizer requirement for maize in a particular field and year has proven to be a challenge due to the complexity of the nitrogen inputs, transformations and outputs in the nitrogen cycle. Remote sensing of maize nitrogen deficiency may be one way to move nitrogen fertilizer applications closer to the specific nitrogen requirement. Six vegetation indices [normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), red-edge normalized difference vegetation index (RENDVI), triangle greenness index (TGI), normalized area vegetation index (NAVI) and chlorophyll index-green (CI_green)] were evaluated for their ability to detect nitrogen deficiency and predict grain maize grain yield. Strip trials were established at two locations in Arkansas, USA, with nitrogen rate as the primary treatment. Remote sensing data was collected weekly with an unmanned aerial system (UAS) equipped with a multispectral and thermal sensor. Relationships among index value, nitrogen fertilizer rate and maize growth stage were evaluated. Green NDVI, RENDVI and CI_green had the strongest relationship with nitrogen fertilizer treatment. Chlorophyll Index-green and GNDVI were the best predictors of maize grain yield early in the growing season when the application of additional nitrogen was still agronomically feasible. However, the logistics of late season nitrogen application must be considered.

Blockchain (BC) technology, defined as a shared information system to validate, secure, and permanently store transactions among multiple parties on a distributed ledger, presents many applications in agricultural and food industries. This study examines the application of BC in food traceability for beef in the United States using a choice experiment. Findings indicate that consumers value USDA certifications over BC traceability to guide their meat preferences. Our study suggests a number of industry implications, the most important of which suggests focusing business and consumer education on the value of product data, rather than on the value of the technologies that manage data.