The relationship between grain and ovary size in wheat: An analysis of contrasting grain weight cultivars under different growing conditions

Benincasa, Paolo; Reale, Lara; Tedeschini, Emma; Ferri, Valentina; Cerri, Martina; Ghitarrini, Sofia; Falcinelli, Beatrice; Frenguelli, Giuseppe; Ferranti, Francesco; Ayano, B.E.; Porfiri, O.; Rosati, A.

doi:10.1016/j.fcr.2017.05.019

Cited by 30 publications

(18 citation statements)

References 37 publications

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“…Other studies have confirmed the importance of carpel size in determining the size of the mature grain (e.g. Calderini et al , 1999 , 2001 ; Xie et al , 2015 ), although carpel/ovary volume may be influenced by environmental as well as developmental factors ( Calderini et al , 1999 ; Simmonds et al , 2016 ; Benincasa et al , 2017 ). Second, a QTL responsible for 7% variation in grain weight has been shown to act by altering the length of pericarp cells, which in turn affects the maximum length to which the grain can grow ( Brinton et al , 2017 ).…”

Section: Discussionmentioning

confidence: 82%

Final grain weight is not limited by the activity of key starch-synthesising enzymes during grain filling in wheat

Fahy

Siddiqui

David

et al. 2018

Journal of Experimental Botany

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Section: Discussionmentioning

confidence: 82%

Final grain weight is not limited by the activity of key starch-synthesising enzymes during grain filling in wheat

Fahy

Siddiqui

David

et al. 2018

Journal of Experimental Botany

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“…Although satellite data do show advantages in monitoring crop biomass, final yield is determined by grain weight, which is related to grain number in the flowering period and individual grain size in the grain-filling period [85]. Additionally, numerous agronomy experiments have shown that drought and heat in the above periods have a greater impact on crop growth [86,87]. These findings have explained why adding the silking or maturity stage of climate factors significantly improved crop yield prediction in current study.…”

Section: Integrating Multi-source Data To Predict Large-scale Crop Yieldmentioning

confidence: 69%

Combining Optical, Fluorescence, Thermal Satellite, and Environmental Data to Predict County-Level Maize Yield in China Using Machine Learning Approaches

Zhang

Luo

et al. 2019

Remote Sensing

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Maize is an extremely important grain crop, and the demand has increased sharply throughout the world. China contributes nearly one-fifth of the total production alone with its decreasing arable land. Timely and accurate prediction of maize yield in China is critical for ensuring global food security. Previous studies primarily used either visible or near-infrared (NIR) based vegetation indices (VIs), or climate data, or both to predict crop yield. However, other satellite data from different spectral bands have been underutilized, which contain unique information on crop growth and yield. In addition, although a joint application of multi-source data significantly improves crop yield prediction, the combinations of input variables that could achieve the best results have not been well investigated. Here we integrated optical, fluorescence, thermal satellite, and environmental data to predict county-level maize yield across four agro-ecological zones (AEZs) in China using a regression-based method (LASSO), two machine learning (ML) methods (RF and XGBoost), and deep learning (DL) network (LSTM). The results showed that combining multi-source data explained more than 75% of yield variation. Satellite data at the silking stage contributed more information than other variables, and solar-induced chlorophyll fluorescence (SIF) had an almost equivalent performance with the enhanced vegetation index (EVI) largely due to the low signal to noise ratio and coarse spatial resolution. The extremely high temperature and vapor pressure deficit during the reproductive period were the most important climate variables affecting maize production in China. Soil properties and management factors contained extra information on crop growth conditions that cannot be fully captured by satellite and climate data. We found that ML and DL approaches definitely outperformed regression-based methods, and ML had more computational efficiency and easier generalizations relative to DL. Our study is an important effort to combine multi-source remote sensed and environmental data for large-scale yield prediction. The proposed methodology provides a paradigm for other crop yield predictions and in other regions.

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“…Besides, the high yield of HL was also attributed to its heavier seeds, but seed weight primarily depends on seed size especially during the process before seed filling, indicating a crucial role for seed size in evaluation of yield of Euryale ferox Salisb. during the growth of its reproductive organs [39,40]. Seeds of aquatic plants often have higher moisture water, which induces a large error in seed weight [41].…”

Section: Discussionmentioning

confidence: 99%

Small Auxin Up RNAs influence the distribution of indole-3-acetic acid and play a potential role in increasing seed size in Euryale ferox Salisb

et al. 2020

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Background: Aquatic Euryale ferox Salisb. is an economically important crop in China and India. Unfortunately, low yield limitations seriously hinder market growth. Unveiling the control of seed size is of remarkable importance in improvement of crops. Here, we generated a new hybrid line (HL) with larger seeds by crossing South Gordon Euryale and North Gordon Euryale (WT) which hasn't been reported before. However, the functional genes and molecular mechanisms controlling the seed size in Euryale ferox Salisb. remain unclear. In this study, we focused on the differentially expressed genes in the auxin signal transduction pathway during fruit development between HL and WT to explore candidate regulatory genes participated in regulating seed size. Results: Both concentration and localization of indole-3-acetic acid (IAA) at two growth stages of fruits of WT and HL were detected by LC-MS and immunofluorescence. Although IAA content between the two lines did not differ, IAA distribution was significantly different. To elucidate the mechanism and to seek the key genes underlying this difference, RNA-seq was performed on young fruits at the two selected growth stages, and differentially expressed genes related to the auxin transduction pathway were selected for further analysis. Conclusion: Hybrid Euryale ferox Salisb. expressed significant heterosis, resulting in non-prickly, thin-coated, large seeds, which accounted for the significantly larger yield of HL than that of WT. Our study indicated that Small Auxin Up RNAs (SAURs)-mediated localization of IAA regulates seed size in Euryale ferox Salisb. We found that some SAURs may act as a positive mediator of the auxin transduction pathway, thereby contributing to the observed heterosis.

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The relationship between grain and ovary size in wheat: An analysis of contrasting grain weight cultivars under different growing conditions

Cited by 30 publications

References 37 publications

Final grain weight is not limited by the activity of key starch-synthesising enzymes during grain filling in wheat

Final grain weight is not limited by the activity of key starch-synthesising enzymes during grain filling in wheat

Combining Optical, Fluorescence, Thermal Satellite, and Environmental Data to Predict County-Level Maize Yield in China Using Machine Learning Approaches

Small Auxin Up RNAs influence the distribution of indole-3-acetic acid and play a potential role in increasing seed size in Euryale ferox Salisb

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