In silico assessment of sowing dates and nitrogen management in common bean crops

ABSTRACT The demonstration of yield potential of crops depends on genetic factors, favorable conditions of envi ronment, and management. The sowing time can significantly affect the common bean grain yield. The aim of this research was to study the behavior of Brazilian cultivars and sowing times on the yield components and grain yield of common bean grown in the environmental conditions of Lichinga, Province of Niassa, Mozambique. The field trial was performed for two growing seasons, using the experimental as a randomized block in factorial 5 × 3 × 2, with four replications. The treatments consisted of the combination of five common bean cultivars (BRS Pontal, BRS Agreste, Perola, and BRS Requinte, developed by Brazilian Agricultural Research Corporation (Embrapa), and a local variety, Encarnada) with three sowing dates (beginning of the rainy season, and 15 and 30 days after), during two growing seasons. The Brazilian cultivar of common beans BRS Pontal was the most productive in all sowing times, followed by BRS Agreste, which was not the most productive only in the second sowing time of 2013/2014 growing season. The cultivar Encarnada, from Mozambique, was the less productive cultivar in all sowing times and in all growing seasons. The best sowing time for common bean cultivars is in the beginning of the rainy season. The use of technologies such as use of seeds of new cultivars, proper sowing time, fertilization, and control of weeds allow significant increase of common bean grain yield in Lichinga, Mozambique.

HighlightsGood applicability of DSSAT was validated in simulating summer maize yield in the Guanzhong Plain, China.Optimal sowing dates of summer maize were obtained for different climatic years.The optimal irrigation and nitrogen management strategy conserved water and nitrogen. Abstract. Agricultural system models play an important role in simulating crop growth processes and water and fertilizer regulation in arid regions. To solve the current problems of optimizing the sowing date in different climatic years and the fertilizer application in low-precipitation conditions in the Guanzhong Plain, China, this study used two years (2016-2017) of experimental summer maize field data to calibrate and validate Decision Support System for Agro-technology Transfer (DSSAT) model parameters. The validated DSSAT model was then used to simulate and optimize sowing dates, irrigation, and fertilization of summer maize crops in the Guanzhong Plain. The relative root-mean-square error (nRMSE) between the measured and simulated values of summer maize crop yield was 8.57%, proving that the established DSSAT model and crop parameters were highly reliable. The nRMSE values for soil water content and nitrate-nitrogen were 7.86% and 8.72%, respectively, which indicated better simulation results. The optimal sowing date for summer maize in the Guanzhong Plain were mid- to late June, mid-June, and early to mid-June in wet, general, and dry years, respectively. The irrigation and nitrogen strategies for summer maize in the climatic years were as follows: 60 mm and 180 kg ha-1 in wet years, 60 mm and 180 kg ha-1 in general years, and 150 mm and 150 kg ha-1 in dry years. This study provides a scientific decision-making method for the production of summer maize to conserve water and fertilizer. Keywords: . Climatic year, DSSAT, Guanzhong Plain, Sowing date, Summer maize.

According to most recent findings, growth regulating factors (GRFs) are plant-specific transcription factors (TFs) that play important roles in many processes, including abiotic and biotic stress response mechanisms. Completion of the common bean (Phaseolus vulgaris) genome project has provided researchers with the opportunity to identify all GRF genes in this species. With this aim, a genome-wide in silico study was performed and 10 GRF proteins (called PhvGRFs) were identified in the common bean genome. Conserved and mandatory motifs (QLQ and WRC) were confirmed in all identified PhvGRFs and two segmental duplication events were determined. Most of the PhvGRFs were found to be more similar to Arabidopsis thaliana GRFs than to Zea mays GRFs in a phylogenetic tree. According to the expression analysis of 10 PhvGRFs, inversely related expression patterns were observed in the roots of Yakutiye and Zulbiye cultivars based on their capacity to adopt to drought stress. After drought treatment of the Zulbiye cultivar, a drought-sensitive common bean cultivar, PhvGRF1, PhvGRF2, PhvGRF3, PhvGRF5, PhvGRF6, PhvGRF9 and PhvGRF10 genes were upregulated 2- to 4-fold in root tissues, as compared to the untreated control. The trend of PhvGRF1, PhvGRF2, PhvGRF3, PhvGRF5, PhvGRF6, PhvGRF7, PhvGRF9 and PhvGRF10 genes showed a consistent decline of 2- to 6-fold in root tissues of the drought-tolerant Yakutiye cultivar subjected to 24 h of drought stress. We demonstrated that the expression patterns of the identified PhvGRFs correlated with the drought-stress response in a cultivar-specific manner in the common bean. We suggest that members of the GRF family can also be used for genetic engineering applications in the common bean.