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ARS Home » Pacific West Area » Pullman, Washington » WHGQ » Research » Publications at this Location » Publication #410076
Research Project: Wheat and Barley Adaptation to a Changing Climate - Discovery of Genetic and Physiological Processes for Improved Crop Productivity and Quality

Location: Wheat Health, Genetics, and Quality Research

Title: Harnessing enviromics to predict climate-impacted high-profile traits for informed decision

Author
item ZHANG, BOSEN - Washington State University
item HAUVERMAL, AMBER - Washington State University
item ZHANG, ZHIWU - Washington State University
item Thompson, Alison
item NEELY, CLARK - Washington State University
item ESSER, AARON - Washington State University
item PUMPHREY, MICHAEL - Washington State University
item Garland-Campbell, Kimberly
item YU, JIANMING - Iowa State University
item Steber, Camille
item Li, Xianran

Submitted to: Food and Energy Security
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/22/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Wheat falling number (FN) is a critical factor for determining end use quality in the wheat industry. Grains with FN lower than the standard threshold are sold with significant less price, which reduce growers profit. Furthermore, because of the nature of molecular causes of FN, a small amount of low FN grain will ruin a large quantity of sound, or high FN grain if mixed. Separate storage of low and high FN grain at elevators is critical to maximize crop values. However, FN quantification assay is time consuming and expensive, which cannot provide much needed information to guide the storage plane. This research, based on the fact that environmental conditions is a major contributor to FN variation, present an alternative strategy to predict FN trend with weather profile.

Technical Abstract: Modern agriculture is a complex system that demands real-time and large-scale quantification of trait values to make evidence-based decisions across all components. However, high-profile traits often lack high-throughput phenotyping technologies to achieve this objective. Recognizing that environmental conditions play a significant role in trait variations observed in crop production fields, we propose and demonstrate the viability of enviromics as a practical solution for capturing trait trends, thereby enabling informed decision-making.