Simulated Biomass, Climate Change Impacts, and Nitrogen Management to Achieve Switchgrass Biofuel Production at Diverse Sites in U.S.

Abstract

Switchgrass (Panicum virgatum L.) is a C4, warm season, perennial native grass that has been strongly recommended as an ideal biofuel feedstock. Accurate forecasting of switchgrass yield across a geographically diverse region and under future climate conditions is essential for determining realistic future ethanol production from switchgrass. This study compiled a switchgrass database through reviewing the existing literature from field trials across the U.S. Using observed switchgrass data, a process-based model (ALMANAC) was developed. The ALMANAC simulation results showed that crop management had more effect on yield than location. The ALMANAC model consists of functional relationships that provide a better understanding of interactions among plant physiological processes and environmental factors (water, soil, climate, and nutrients) giving realistic predictions in different climate conditions. This model was used to quantify the impacts of climate change on switchgrass yields. Simulated lowland switchgrass would have more yield increases between Illinois and Ohio in future (2021–2050) under both Representative Concentration Pathway (RCP) 4.5 and 8.5 pathways with low N fertilizer inputs than high N fertilizer inputs. There was no significant effect of climate variability on upland simulated yields, which means that N fertilization is a key factor in controlling upland switchgrass yields under future climate conditions.

An Efficient Structure of an Agrophotovoltaic System in a Temperate Climate Region

“…Polynomial regression is one of most popular supervised machine learning (ML) approaches due to its analytic capability [24,25]. Unlike other black-box ML approaches (e.g., deep learning and neural networks), it can identify the significance of independent variables [26]. Since independent variables have different influence on a response variable (i.e., Y), it is appropriate to utilize a polynomial regression as the modeling approach to understand the various relationships between independent variables and a response variable.…”

Simulated impacts of rainfall extremes on yield responses of various barley varieties in a temperate region

“…Since each person only needs a certain amount of food to live, overproduced grain has no value. Equation ( 5) is calibrated by the least square method, which estimates parameters (or constants) in order to minimize the estimation error of a given model (Kim et al, 2020). Based on the calibrated model, we could identify which scenario would be the best in terms of potential unit revenue.…”

“…Debeake et al (1997) used ALMANAC to demonstrate the diverse cropping systems associated with controlling weed growth in plots where various winter and spring wheat genotypes are grown. This model has been used to evaluate crop growth adaptations under different environmental conditions and different climate change scenarios (Behrman et al, 2014;Kim et al, 2020). Thus, ALMANAC simulations can help farmers to determine the best cropping management practices to help them to effectively adapt to frequent extreme weather events.…”

Crop Modeling Application to Improve Irrigation Efficiency in Year-Round Vegetable Production in the Texas Winter Garden Region

“…After successful model yield validation, the simulated WUE was calculated for all vegetables. Two types of WUE, WUE wet and WUE dry , were calculated as wet or dry weight of plant yield or marketable yield divided by the quantity of plant transpiration during the growing season [5]. Since ALMANAC simulated dry weight of marketable yield, when we calculated WUE wet, the simulated yields were divided by (1 − (moisture content/100)).…”