Oil content and economic water productivity of soybean cultivars under different water availability conditions

Rodrigues, Silvana Antunes; Robaina, Adroaldo Dias; Peiter, Márcia Xavier; Bruning, Jhosefe; Piroli, Jéssica Dariane; Gollo, Elisa de Almeida

doi:10.1590/0103-8478cr20210836

Cited by 3 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite a rapid upsurge in production and coverage, soybean still suffers adversely on the productivity front. A possible increase in the exploitation of natural resources in the coming decades indicates increasing demand for sustaining the productivity of soybean (Rodrigues et al 2023). This prognostication pushes us to look for alternative methods to increase the soybean yield and the challenge is to produce more soybeans strategically and sustainably.…”

Section: Introductionmentioning

confidence: 99%

Effect of UV exclusion and AMF inoculation on photosynthetic parameters of Glycine max

Laad¹,

Patel²,

Guruprasad³

et al. 2023

Photosynt.

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Effect of UV exclusion and AMF inoculation on photosynthetic parameters of Glycine max

Laad¹,

Patel²,

Guruprasad³

et al. 2023

Photosynt.

View full text Add to dashboard Cite

show abstract

Potential of the hazelnut tree search–ELM hybrid approach in estimating yield and water productivity

et al. 2023

View full text Add to dashboard Cite

Wheat plays a vital role in the food security of society, and early estimation of its yield will be a great help to macro-decisions. For this purpose, wheat yield and water productivity (WP) by considering soil data, irrigation, fertilizer, climate, and crop characteristics and using a novel hybrid approach called hazelnut tree search algorithm (HTS) and extreme machine learning method (ELM) was examined under the drip (tape) irrigation. A dataset including 125 wheat yield data, irrigation and meteorological data of Mahabad plain located southeast of Lake Urmia, Iran, was used as input parameters for crop year 2020–2021. Eighty percentage of the data were used for training, and the remaining 20% for model testing. Nine different input scenarios were presented to estimate yield and WP. The efficiency of the proposed model was calculated with the statistical indices coefficient of determination (R2), root-mean-square error (RMSE), normalized root-mean-square error, and efficiency criterion. Sensitivity analysis result showed that the parameters of irrigation, rainfall, soil moisture, and crop variety provide better results for modeling. There was good agreement between the practical values (field management data) and the estimated values with the HTS–ELM model. The results also showed that the HTS–ELM method is very efficient in selecting the best input combination with R2 = 0.985 and RMSE = 0.005. In general, intelligent hybrid methods can enable optimal and economical use of water and soil resources.

show abstract

Influence of Water Deficit on the Chemical Composition of Soybean Grains

Petrova¹,

MATEV²,

Delibaltova³

et al. 2023

RAR

View full text Add to dashboard Cite

With relation to the present issue about the influence of the periodic water deficit on the content and yield of the main chemical components, summarized annual data have been used including years of different characteristics, with droughts in different vegetation phenophases of soybean: very dry, averagely dry and average. The experiment was conducted at the Agricultural University of Plovdiv. The experiment was set in 4 repetitions with a size of experimental plots - 30 m 2 , and the crop plots - 10 m 2 . Criteria for watering performance was pre-watering moisture of soil at option 5-80% under-soil moisture for the layer 0-60 cm. The irrigation norm for all options was 50 mm. The irrigation norm for option 5 was 150 mm, and for options 2, 3 and 4-100 mm. Irrigation was performed gravitative along short closed furrows. After the completion of all experimental options, there were established the content and yield of the main chemical components in soybean grains - raw fat content, raw protein, raw fibres, raw ash and non-nitrogen extracted substances. Watering cancellations in the period of seed filling decrease the raw protein content. Watering cancellation in the bean formation period has a negative influence on protein content in soybean or does not influence it at all. Watering cancellation during the reproductive period decreases raw protein yield, which leads to a decrease in grain yield. Regarding raw fats, the most favourable is the water cancellation in the period of seed filling which favours growth in their content. Watering cancellation in the period of seed filling leads to a more significant decrease in lysine content. Despite the watering cancellation in a particular phase, the application of the other two waterings increases carbohydrate content in soybean grains compared to that obtained in non-watering conditions.

show abstract

Oil content and economic water productivity of soybean cultivars under different water availability conditions

Cited by 3 publications

References 20 publications

Effect of UV exclusion and AMF inoculation on photosynthetic parameters of Glycine max

Effect of UV exclusion and AMF inoculation on photosynthetic parameters of Glycine max

Potential of the hazelnut tree search–ELM hybrid approach in estimating yield and water productivity

Influence of Water Deficit on the Chemical Composition of Soybean Grains

Contact Info

Product

Resources

About