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      An Interdisciplinary Approach to Study the Performance of Second-generation Genetically Modified Crops in Field Trials: A Case Study With Soybean and Wheat Carrying the Sunflower HaHB4 Transcription Factor

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          Abstract

          Research, production, and use of genetically modified (GM) crops have split the world between supporters and opponents. Up to now, this technology has been limited to the control of weeds and pests, whereas the second generation of GM crops is expected to assist farmers in abiotic stress tolerance or improved nutritional features. Aiming to analyze this subject holistically, in this presentation we address an advanced technology for drought-tolerant GM crops, upscaling from molecular details obtained in the laboratory to an extensive network of field trials as well as the impact of the introduction of this innovation into the market. Sunflower has divergent transcription factors, which could be key actors in the drought response orchestrating several signal transduction pathways, generating an improved performance to deal with water deficit. One of such factors, HaHB4, belongs to the homeodomain-leucine zipper family and was first introduced in Arabidopsis. Transformed plants had improved tolerance to water deficits, through the inhibition of ethylene sensitivity and not by stomata closure. Wheat and soybean plants expressing the HaHB4 gene were obtained and cropped across a wide range of growing conditions exhibiting enhanced adaptation to drought-prone environments, the most important constraint affecting crop yield worldwide. The performance of wheat and soybean, however, differed slightly across mentioned environments; whereas the improved behavior of GM wheat respect to controls was less dependent on the temperature regime (cool or warm), differences between GM and wild-type soybeans were remarkably larger in warmer compared to cooler conditions. In both species, these GM crops are good candidates to become market products in the near future. In anticipation of consumers’ and other stakeholders’ interest, spectral analyses of field crops have been conducted to differentiate these GM crops from wild type and commercial cultivars. In this paper, the potential impact of the release of such market products is discussed, considering the perspectives of different stakeholders.

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          The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution

          The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought. Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives, including numerous extremophile species. Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences and required single-molecule real-time sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade and a sunflower-specific whole-genome duplication around 29 million years ago. An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs.
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            Number of kernels in wheat crops and the influence of solar radiation and temperature

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              Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review

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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/275739
                URI : https://loop.frontiersin.org/people/830019
                URI : https://loop.frontiersin.org/people/861318
                URI : https://loop.frontiersin.org/people/866265
                URI : https://loop.frontiersin.org/people/913443
                URI : https://loop.frontiersin.org/people/829416
                URI : https://loop.frontiersin.org/people/274895
                URI : https://loop.frontiersin.org/people/49069
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                06 March 2020
                2020
                : 11
                : 178
                Affiliations
                [1] 1 Estación Experimental Pergamino, INTA, CITNOBA, CONICET-UNNOBA , Pergamino, Argentina
                [2] 2 CIFASIS, Universidad Nacional de Rosario—CONICET , Rosario, Argentina
                [3] 3 Instituto de Agrobiotecnología Rosario (INDEAR)/BIOCERES , Rosario, Argentina
                [4] 4 CONICET , Buenos Aires, Argentina
                [5] 5 Instituto de Agrobiotecnología del Litoral, Universidad Nacional del Litoral—CONICET, Facultad de Bioquímica y Ciencias Biológicas , Santa Fe, Argentina
                [6] 6 CONICET-INTA-FAUBA, Estación Experimental Pergamino, Facultad de Agronomía Universidad de Buenos Aires , Pergamino, Argentina
                Author notes

                Edited by: Domenico De Martinis, Energy and Sustainable Economic Development (ENEA), Italy

                Reviewed by: Daisuke Todaka, The University of Tokyo, Japan; Renata Fuganti-Pagliarini, Embrapa Soybean, Brazil

                *Correspondence: María Elena Otegui, otegui@ 123456agro.uba.ar ; Raquel Lía Chan, rchan@ 123456fbcb.unl.edu.ar

                This article was submitted to Crop and Product Physiology, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2020.00178
                7069416
                a73a9358-d9e7-4f40-a5c9-6a9399e85aae
                Copyright © 2020 González, Rigalli, Miranda, Romagnoli, Ribichich, Trucco, Portapila, Otegui and Chan

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 October 2019
                : 05 February 2020
                Page count
                Figures: 6, Tables: 5, Equations: 1, References: 72, Pages: 15, Words: 7855
                Funding
                Funded by: Fondo para la Investigación Científica y Tecnológica 10.13039/501100006668
                Categories
                Plant Science
                Hypothesis and Theory

                Plant science & Botany
                transgenic wheat,transgenic soybean,hahb4,sunflower transcription factor,drought tolerance,grain yield determination

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