4
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Discrimination of responses of corn genotypes to drought through physiological, growth, and yield traits Translated title: Discriminação das respostas de genótipos de milho à seca por meio de características fisiológicas e de crescimento e produção

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Abstract: The objective of this work was to evaluate different traits of four corn (Zea mays) genotypes with contrasting responses to drought and to determine the main traits associated to such responses. The experiment was carried out in a greenhouse. The plants were grown in pots subjected to full irrigation. Drought was imposed to plants at 54 days after sowing and kept constant for 12 consecutive days; however, a group of plants remained under full irrigation. Traits related to leaf gas exchange, photochemical apparatus, growth, and yield were assessed, and data were subjected to hierarchical agglomerative clustering and principal component analysis. DKB 390 distinguishes from the other genotypes for growth and yield traits, while 2B-707 and DKB 390 discriminate from 'BRS 1030' and 'BRS 1010' for physiological traits. Ear length, kernel number per ear, above-ground dry matter, shoot dry matter, and plant height are the most important growth and yield traits to discriminate genotype-dependent drought tolerance. Among the physiological traits, the most important are: chlorophyll content, absorptivity, leaf temperature, maximum fluorescence in the dark-adapted state, minimum fluorescence in the dark-adapted state, water-use efficiency, and intercellular CO2 concentration.

          Translated abstract

          Resumo: O objetivo deste trabalho foi avaliar diferentes características de quatro genótipos de milho (Zea mays) com respostas contrastantes à seca e determinar as principais características associadas a tais respostas. O experimento foi realizado em casa de vegetação. As plantas foram cultivadas em vasos submetidos à irrigação plena. A seca foi imposta às plantas aos 54 dias após a semeadura e mantida constante por 12 dias consecutivos; no entanto, um grupo de plantas permaneceu sob irrigação plena. Avaliaram-se as características relacionadas às trocas gasosas foliares, ao aparato fotoquímico, ao crescimento e à produção. Os dados foram submetidos a agrupamento hierárquico e análise de componentes principais. DKB 390 distingue-se dos demais genótipos quanto às características de crescimento e produção, enquanto 2B-707 e DKB 390 distinguem-se dos genótipos 'BRS 1030' e 'BRS 1010' quanto às características fisiológicas. O comprimento da espiga, o número de grãos por espiga, a matéria seca da parte aérea e do caule e a altura de planta são as características de crescimento e produção mais importantes para discriminar os genótipos de milho quanto à tolerância à seca. Entre as características fisiológicas, as mais importantes são: conteúdo de clorofila, absortividade, temperatura da folha, fluorescência máxima no escuro, fluorescência mínima no escuro, eficiência no uso de água e concentração intercelular de CO2.

          Related collections

          Most cited references 28

          • Record: found
          • Abstract: found
          • Article: not found

          Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

           M Mukaka (2012)
          Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Any trait or trait-related allele can confer drought tolerance: just design the right drought scenario.

            Most traits associated with drought tolerance have a dual effect, positive in very severe scenarios and negative in milder scenarios, or the opposite trend. Their effects also depend on other climatic conditions such as evaporative demand or light, and on management practices. This is the case for processes associated with cell protection and with avoidance, but also for the maintenance of growth or photosynthesis, high water use efficiency, large root systems or reduced abortion rate under water deficit. Therefore, spectacular results obtained in one drought scenario may have a limited interest for improving food security in other geographical areas with water scarcity. The most relevant questions on drought tolerance are probably, 'Does a given allele confer a positive effect on yield in an appreciable proportion of years/scenarios in a given area or target population of environment (TPE)?'; 'In a given site or TPE, what is the trade-off between risk avoidance and maintained performance?'; and 'Will a given allele or trait have an increasingly positive effect with climate change?' Considerable progress has already occurred in drought tolerance. Nevertheless, explicitly associating traits for tolerance to drought scenarios may have profound consequences on the genetic strategies, with a necessary involvement of modelling.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis.

              Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. © 2014 American Society of Plant Biologists. All rights reserved.
                Bookmark

                Author and article information

                Journal
                pab
                Pesquisa Agropecuária Brasileira
                Pesq. agropec. bras.
                Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira (Brasília, DF, Brazil )
                0100-204X
                1678-3921
                2021
                : 56
                Affiliations
                Campinas São Paulo orgnameEmbrapa Informática Agropecuária Brazil thiago.santos@ 123456embrapa.br
                Brasília Distrito Federal orgnameEmbrapa Agroenergia Brazil casari.raphael@ 123456gmail.com
                Teresina Piauí orgnameEmbrapa Meio-Norte Brazil carlos.antonio@ 123456embrapa.br
                Lavras Minas Gerais orgnameUniversidade Federal de Lavras Brazil viviannybiologa@ 123456gmail.com
                Article
                S0100-204X2021000102301 S0100-204X(21)05600002301
                10.1590/s1678-3921.pab2021.v56.01948

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 28, Pages: 0
                Product
                Product Information: website
                Categories
                Plant Physiology

                Comments

                Comment on this article