Quantifying and Validating Soybean Seed Emergence Model as a Function of Temperature

Alsajri, Firas Ahmed; Wijewardana, Chathurika; Krutz, L. Jason; Irby, J. Trenton; Golden, Bobby R.; Reddy, K. Raja

doi:10.4236/ajps.2019.101010

Cited by 6 publications

(6 citation statements)

References 21 publications

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“…The optimal Tbase also differed by cultivars (Figure 3, Table 4). Similar results have been observed by Alsajri et al [31] after comparing the optimal base temperatures of two soybean cultivars. For Pungsan, Soweon, and Heapum, CVs increased as T base increased at stage from sowing to flowering.…”

Section: Determination Of Optimal Base Temperatures For All Six Soybean Sprout Cultivarssupporting

confidence: 90%

Modeling the Impacts of Climate Change on Yields of Various Korean Soybean Sprout Cultivars

Yoon

Kim

Cho³

et al. 2021

Agronomy

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Soybean sprout is an important food ingredient in East Asian cuisine. Soybean growth is highly sensitive to temperature and photoperiod. Thus, it is important to determine the optimal base temperature for an accurate yield prediction. The optimal base temperature can be varied by cultivars. In this study, six soybean sprout cultivars that are commonly grown in Korea were planted in South Jeolla province, South Korea between 2003 and 2018. Data on phenology were collected from the field and used to determine the optimal base temperature for each cultivar. As a result, variations of optimal base temperatures of cultivars ranged from 0 °C to 15 °C. In simulation, three plant parameter sets, including Soy15, Soy6, and Soy0, were created. Soy15, Soy6, and Soy0 represented soybean cultivars with base temperatures of 15 °C, 6 °C, and 0 °C, respectively. In simulation results, the values of percent bias were under 15%, indicating that the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) could reasonably simulate soybean yields. Among these three cultivars, Soy15 had the smallest yield, while Soy6 had the highest yield. In climate change scenarios (SSP245 and SSP585), both maximum and minimum temperatures were increased by 1–3.3 °C. With increasing temperatures in the future period, grain yields for all cultivars decreased. The yield reduction might be because the high temperature shortened the length of growth period of the soybeans. Among the three cultivars, Soy6 was a promising cultivar that could have a high yield under climate change scenarios.

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Section: Determination Of Optimal Base Temperatures For All Six Soybean Sprout Cultivarssupporting

confidence: 90%

Modeling the Impacts of Climate Change on Yields of Various Korean Soybean Sprout Cultivars

Yoon

Kim

Cho³

et al. 2021

Agronomy

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“…Normalized values were fit to a simplified beta function representing the relative response to the temperature of these four growth and development categories: shoot growth, and development and root growth and development (Figure 8). Understanding potential growth and development under optimal conditions is useful when optimizing crop simulation models [36] and when creating simple models for field application [37,38]. The potential growth and development values for each parameter in this study were derived from the modified beta functions fit to the data at each harvest shown in Figures 4-6.…”

Section: Discussionmentioning

confidence: 99%

“…The functional algorithms could estimate potential corn shoot and root growth parameters at any given location for any given sowing dates. Additionally, the algorithms could improve the existing corn models [36][37][38][39][40] in enhancing their functionality. Both simple and complex crop simulation models will have potential utilization in emerging precision agriculture technology [41].…”

Section: Discussionmentioning

confidence: 99%

“…Estimated minimum shoot and root development temperatures were the lowest among the four groups, with an average T min of 5.5 and 3.7 • C, respectively, with shoot growth having the highest T min of 12.5 • C. Optimal temperatures also were significantly different. Shoot development was estimated to have the highest T opt at 32.6 • C, and root growth was estimated to have the lowest T opt at 28.3 • C. Maximum temperatures were the lowest for both shoot and root growth at 38.9 • C and the highest for shoot development at 46.0 • C.Understanding potential growth and development under optimal conditions is useful when optimizing crop simulation models[36] and when creating simple models for field application[37,38]. The potential growth and development values for each parameter in this study were derived from the modified beta functions fit to the data at each harvest shown in Figures4-6.…”

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confidence: 99%

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Temperature Effects on the Shoot and Root Growth, Development, and Biomass Accumulation of Corn (Zea mays L.)

Walne

Reddy

2022

Agriculture

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Temperature is a critical environmental factor regulating plant growth and yield. Corn is a major agronomic crop produced globally over a vast geographic region, and highly variable climatic conditions occur spatially and temporally throughout these regions. Current literature lacks a comprehensive study comparing the effects of temperature on above versus below-ground growth and development and biomass partitioning of corn measured over time. An experiment was conducted to quantify the impact of temperature on corn’s early vegetative growth and development. Cardinal temperatures (Tmin, Topt, and Tmax) were estimated for different aspects of above- and below-ground growth processes. Plants were subjected to five differing day/night temperature treatments of 20/12, 25/17, 30/22, 35/27, and 40/32 °C using sun-lit controlled environment growth chambers for four weeks post-emergence. Corn plant height, leaves, leaf area, root length, surface area, volume, numbers of tips and forks, and plant component part dry weights were measured weekly. Cardinal temperatures were estimated, and the relationships between parameters and temperature within these cardinal limits were estimated using a modified beta function model. Cardinal temperature limits for whole plant dry weight production were 13.5 °C (Tmin), 30.5 °C (Topt), and 38 °C (Tmax). Biomass resources were prioritized to the root system at low temperatures and leaves at high temperatures. Root growth displayed the lowest optimum temperature compared to root development, shoot growth, and shoot development. The estimated cardinal temperatures and functional algorithms produced in this study, which include both above and below-ground aspects of plant growth, could be helpful to update crop models and could be beneficial to estimate corn growth under varying temperature conditions. These results could also be applicable when considering management decisions for maximizing field production and implementing emerging precision agriculture technology.

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“…The AEMs triggered soybean sowing each season between 15 March and 15 May when air temperature exceeded 9°C (7 days moving average) and soil temperature exceeded 7°C (5 days moving average). This is a one degree lower threshold, as known for later MGs (III–V; Alsajri et al, 2019), owing to the cold‐temperature adaptation of the earlier MGs (Ritter & Bykova, 2021). Harvest was triggered at simulated maturity.…”

Section: Methodsmentioning

confidence: 77%

Future area expansion outweighs increasing drought risk for soybean in Europe

Nendel

Reckling

Schulz

et al. 2023

Global Change Biology

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The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare selfsufficiency targets for plant-based proteins, but detailed strategies are still lacking.Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks. Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO 2 levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP | 1341 NENDEL et al.

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Quantifying and Validating Soybean Seed Emergence Model as a Function of Temperature

Cited by 6 publications

References 21 publications

Modeling the Impacts of Climate Change on Yields of Various Korean Soybean Sprout Cultivars

Modeling the Impacts of Climate Change on Yields of Various Korean Soybean Sprout Cultivars

Temperature Effects on the Shoot and Root Growth, Development, and Biomass Accumulation of Corn (Zea mays L.)

Future area expansion outweighs increasing drought risk for soybean in Europe

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