Computational design for more engaged, impactful, and dynamic agricultural research DOI Creative Commons
Michael B. Kantar, Patrick M. Ewing, Jon Bančič

и другие.

Crop Science, Год журнала: 2025, Номер 65(2)

Опубликована: Март 1, 2025

Abstract Computational design in agriculture is the use of data‐driven systems and tools to propose evaluate alternative configurations agricultural systems. It unique from digital that it integrates computational crop science approaches formulate problems rather than mitigating by applying technologies. In this special issue, we highlight how could be used adapt better meet societal goals more rapidly at lower cost. Many disciplines within sciences are represented, breeding cropping agronomy. Using a symposium major scientific conference as case study, also demonstrate framing can facilitate transdisciplinary research. Critically, all participants highlighted potential stakeholder engagement through eliciting, formalizing, evaluating their values experiences. This especially important grand challenge contexts changing climates market demands, where intuition developed past may break down. By leveraging power design, make informed decisions create maximize productivity while minimizing environmental impact under current future environments.

Язык: Английский

Impacts of dairy forage management on soil carbon change and net-zero accounting DOI Creative Commons
Joshua D. Gamble, Jonathan Alexander

Journal of Dairy Science, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

The US Dairy Industry has pledged to achieve net zero greenhouse gas emissions (GHG) by 2050, but reliance on corn (Zea mays L.) silage as a primary forage source undermines progress toward this goal. Soils managed for production are significant of carbon (C) the atmosphere, with soil C losses ranging from 3.7 7.0 Mg ha-1 yr-1 (13.5 25.6 CO2 yr-1) reported in literature. However, biogenic loss not typically represented within C-footprints or life cycle inventories. Using an example dairy farm, we demonstrate that including associated under can increase C-footprint milk nearly 2-fold. We suggest approach represents more accurate estimate impact production, and gains GHG efficiency have come, part, at expense where rotations predominated corn. balance systems likely be improved advanced manure management technologies application strategies return manurial while minimizing N P loading. argue extensive changes cropping will also required. Expanding role perennials winter annual crops rotations; breeding forages greater yield, persistence, deeper root systems; additional creative solutions retain plant-derived soils necessary budgets net-zero targets.

Язык: Английский

Процитировано

0
Computational design for more engaged, impactful, and dynamic agricultural research DOI Creative Commons
Michael B. Kantar, Patrick M. Ewing, Jon Bančič

и другие.

Crop Science, Год журнала: 2025, Номер 65(2)

Опубликована: Март 1, 2025

Abstract Computational design in agriculture is the use of data‐driven systems and tools to propose evaluate alternative configurations agricultural systems. It unique from digital that it integrates computational crop science approaches formulate problems rather than mitigating by applying technologies. In this special issue, we highlight how could be used adapt better meet societal goals more rapidly at lower cost. Many disciplines within sciences are represented, breeding cropping agronomy. Using a symposium major scientific conference as case study, also demonstrate framing can facilitate transdisciplinary research. Critically, all participants highlighted potential stakeholder engagement through eliciting, formalizing, evaluating their values experiences. This especially important grand challenge contexts changing climates market demands, where intuition developed past may break down. By leveraging power design, make informed decisions create maximize productivity while minimizing environmental impact under current future environments.

Язык: Английский

Процитировано

0