Soybean maturity group selection: Irrigation and nitrogen fixation effects on returns

Wegerer, Ryan; Popp, Michael P.; Hu, Xiaoyan; Purcell, Larry C.

doi:10.1016/j.fcr.2015.05.002

Cited by 11 publications

(13 citation statements)

References 15 publications

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“…Secondly, this study characterized both shoots as well as root growth and development to determine the temperature tolerance in the soybean cultivars. The present study evaluated soybean cultivars belonging to MG III, IV, and V, which are recommended ideal for the US Midsouth environments based on previous literature describing the interactive effects of agronomic practices, environments, and MG [2,16,19,20,[34][35][36]. The present study showed vigorous seedling growth in cultivars belonging MG IV and V when compared to MG III, which supports recent studies that favored MG IV and V to utilize under ESPS in the US Midsouth [2,19].…”

Section: Discussionsupporting

confidence: 86%

Evaluating Soybean Cultivars for Low- and High-Temperature Tolerance During the Seedling Growth Stage

et al. 2019

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Soybean (Glycine max L.) seedlings may be exposed to low or high temperatures under early or conventional soybean production systems practiced in the US Midsouth. However, a wide range of soybean cultivars commonly grown in the region may inherit diverse tolerance to degrees of temperatures. Therefore, a study was conducted in a controlled-environment facility to quantify 64 soybean cultivars from Maturity Group III to V, to low (LT; 20/12 °C), optimum (OT; 30/22 °C), and high (HT; 40/32 °C) temperature treatments during the seedling growth stage. Several shoot, root, and physiological parameters were assessed at 20 days after sowing. The study found a significant decline in the measured root, shoot, and physiological parameters at both low and high temperatures, except for root average diameter (RAD) and lateral root numbers under LT effects. Under HT, shoot growth was significantly increased, however, root growth showed a significant reduction. Maturity group (MG) III had significantly lower values for the measured root, shoot, and physiological traits across temperature treatments when compared with MG IV and V. Cultivar variability existed and reflected considerably through positive or negative responses in growth to LT and HT. Cumulative stress response indices and principal component analysis were used to identify cultivar-specific tolerance to temperatures. Based on the analysis, cultivars CZ 5225 LL and GS47R216 were identified as most sensitive and tolerant to LT, while, cultivars 45A-46 and 5115LL identified as most tolerant and sensitive to HT, respectively. The information on cultivar-specific tolerance to low or high temperatures obtained in this study would help in cultivar selection to minimize stand loss in present production areas.

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Section: Discussionsupporting

confidence: 86%

Evaluating Soybean Cultivars for Low- and High-Temperature Tolerance During the Seedling Growth Stage

et al. 2019

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“…In this case, rainfed treatments yielded 63% with respect to irrigated ones. Wegerer et al (2015) evaluated different soybean maturity groups under low-and full-irrigated conditions in Arkansas. They showed also no management × water availability crossover interaction, and reduced water availability treatments yielded 65% of full-irrigated ones.…”

Section: Total Canopy N Uptake N Use Efficiency and Harvest Indexmentioning

confidence: 99%

“…These strategies can be implemented through simple management options, like growth cycle, row spacing or stand densities changes. For example, longer maturity groups can better cope intermittent water shortages by having an extended growing season compared to shorter maturity group cultivars (Egli, 1993;Wegerer, Popp, Hu, & Purcell, 2015). Wider row spacing can help conserve water early in the season (Reicosky, Warnes, & Evans, 1985).…”

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confidence: 99%

Exploring soybean management options for environments with contrasting water availability

Mauro

Borrás

Rugeroni³

et al. 2019

J Agronomy Crop Science

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Soybean is commonly cultivated under rainfed conditions being water availability the main constraint. We evaluated the performance of different managements under contrasting water availability to test possible trade‐offs among managements, and to determine physiological variables explaining these yield differences. Four treatments were designed through specific combinations of cultivar, row spacing and stand density. They were classified as stress tolerance or yield potential strategies and were evaluated under two contrasting water availability treatments. Treatments ranged from 349 to 954 mm total water availability. Water stress treatments yielded 72% and 59% of the well‐watered treatment each year, similar to frequent soybean water stress levels for our production region. Management treatments showed significant yield differences (p < 0.05), but the management × water availability interaction did not (p = 0.42). No management option helped reduce negative water stress effects. Highest yields were achieved using 0.25 m row spacing, a stand density of 60 pl per m2, and a high yield potential genotype. Yield variations were explained by differences in harvested seeds per unit area (R2 = 0.75; p < 0.001) and total N uptake at maturity (R2 = 0.93; p < 0.001) across environments. Because management strategies specifically tailored to cope with water shortages showed limited value, farmers need to target yield potential management options.

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“…Overall, the optimum harvest time resulted from the WOFOST simulation corresponded to the average harvest time of the Indonesian soybean varieties which ranges from 66 to 110 days (Balitkabi, 2016). The soybean optimum harvest time refers to its maturity level that affected by variety (Mourtzinis, Gaspar, Naeve, & Conley, 2017;Poerwoko, 2016;Wegerer, Popp, Hu, & Purcell, 2015) and altitude (Smidt, Conley, Zhu, & Arriaga, 2016). The soybean varieties that used were adaptive from European region which may caused in its adaptive performance in the simulation due to their respective crop parameters especially the assimilate partitioning inputs namely: fraction of total dry matter to root (FRTB); fraction of above ground dry matter to leave (FLTB); fraction of above ground dry matter to stem (FSTB); and the fraction of above ground dry matter to storage organ (FOTB).…”

Section: Optimum Harvest Timementioning

confidence: 99%

Preliminary Study of WOFOST Crop Simulation in Its Prospect for Soybean (Glycine max L.) Optimum Harvest Time and Yield Gap Analysis in East Java

Abadi¹,

Tastra²,

Koentjoro³

2018

Agrivita.J.Agr.Sci

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Optimum harvest time and yield gap information are important aspects of grain quality optimization and production development. The World Food Studies (WOFOST) crop simulation model was studied in its application for soybean optimum harvest time and yield gap analysis in East Java, Indonesia. Data inputs were local weather of solar irradiance and daily temperature, with given soybean varieties provided in the WOFOST simulation. The simulation result was validated with the actual data using homogeneity test of regression coefficient. Result showed that differences between simulation and actual yield were insignificant (α=0.05), for each tested locations and soybean varieties. The average potential yield was 1,716 kg ha -1 , where the highest was obtained from S-France 904 variety located in Malang Regency. The optimum root mean square error was 49.42 kg ha -1 with correlation coefficient of 0.918. Meanwhile, the optimum harvest time and yield gap have corresponded to the actual data where harvest time was at the shortest in Blitar Regency using N-France 901 and N Spain 903 varieties, while the average yield gap was 33%. In conclusion, WOFOST simulation model has a prospect to be applied further using local soybean varieties followed by validation in the whole East Java region.

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Soybean maturity group selection: Irrigation and nitrogen fixation effects on returns

Cited by 11 publications

References 15 publications

Evaluating Soybean Cultivars for Low- and High-Temperature Tolerance During the Seedling Growth Stage

Evaluating Soybean Cultivars for Low- and High-Temperature Tolerance During the Seedling Growth Stage

Exploring soybean management options for environments with contrasting water availability

Preliminary Study of WOFOST Crop Simulation in Its Prospect for Soybean (Glycine max L.) Optimum Harvest Time and Yield Gap Analysis in East Java

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