Phenomics in Crop Plants: Trends, Options and Limitations

Kumar, Jitendra; Pratap, Aditya; Kumar, Shiv

doi:10.1007/978-81-322-2226-2

Cited by 48 publications

(5 citation statements)

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“…According to Kumar et al (2015), lower temperature of the plant canopy is frequently associated with higher grain yield, with a deeper root system, and with greater stomatal conductance in environments subjected to high temperature. Therefore, selection for temperature of the plant canopy, combined with greater initial vigor and delayed senescence to improve interception of light, as well as greater stability of the membrane, the presence of photoprotective pigments, and wax to improve the efficiency of the use of radiation, are desirable for making selection for heat tolerance.…”

Section: Resultsmentioning

confidence: 99%

Effect of heat stress on common bean under natural growing conditions in three locations in different climate zones in the state of So Paulo, Brazil

Silva¹,

Reis²,

Gonçalves³

et al. 2018

J. Plant Breed. Crop Sci.

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Common bean (Phaseolus vulgaris L.) originated in medium to high altitude regions and is sensitive to high temperatures. Climate changes from an increase in global temperatures are foreseen, and therefore better understanding of the mechanisms of heat tolerance is necessary. In this context, the aim of this study was to investigate the effects of heat stress on twelve common bean genotypes under natural growing conditions in three locations (Campinas, Votuporanga, and Ribeirão Preto, SP, Brazil) and in two growing seasons (fall-winter 2016 and summer 2016/2017). Data were analyzed by combined analysis of variance in a 2 × 3 × 12 factorial arrangement, considering two crop seasons, three locations, and twelve genotypes as factors. This was followed by the Scott-Knott mean comparison test (P<0.05), genetics, genetics×environment (GGE)-biplot analysis for grain yield and Pearson correlation for the summer season. Significant differences were found for the crop season, location, and genotype for most of the traits evaluated. It was found that the high temperatures, reached in summer, negatively affected the performance of cultivars, resulting in a reduction of 40% in grain yield. Votuporanga, which reached the highest temperatures during the summer, was considered as the most unfavorable environment. The genotypes that proved to be more productive in the summer for the locations of Campinas were BRS Agreste and FT Nobre; for Votuporanga, the genotypes Pérola and IPR Tangará; and for Ribeirão Preto, the genotypes SEA 5 and BRS Estilo. The highlighted correlations observed by the Pearson test were the highest leaf temperature reducing grain yield and, the highest relative index of chlorophyll contributed to higher productivity.

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Section: Resultsmentioning

confidence: 99%

Effect of heat stress on common bean under natural growing conditions in three locations in different climate zones in the state of So Paulo, Brazil

Silva¹,

Reis²,

Gonçalves³

et al. 2018

J. Plant Breed. Crop Sci.

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show abstract

“…In the case of plants, phenomics correlates growth, performance and composition with genetic, epigenetic and environmental factors. Therefore, phenomics integrated with other omics unveils cellular biochemical or bio-physical networks that result in the final desirable phenotype [ 282 ]. As most phenotypic traits are determined by the interactions between genes and the environment (G × E), collections of large numbers of phenotypic data across multiple environmental conditions revealed the relationships between phenotypic traits and prevailing abiotic stresses [ 283 , 284 ].…”

Section: Phenomicsmentioning

confidence: 99%

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant’s Abiotic Stress Tolerance Responses

Roychowdhury

Das²,

Gupta

et al. 2023

Genes

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The present day’s ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant’s innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the ‘omics’ toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant’s genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence ‘multi-omics’) integrated-omics approaches can decipher the plant’s abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop’s variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

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“…Modern breeding methods apply this knowledge to increase the genetic gain of the breeding process and accelerate the development of improved cultivars. However, while genotypic information is now readily available due to nextgeneration sequencing methods, there is a lack of large amounts of accurate phenotypic data (Yol et al, 2015). The reason for this is that phenotyping is still mainly a manual process, which is time-consuming (Gehan & Kellogg, 2017) and this tends to lead to subjective data because of perception and interpretation differences among experts and experiments (L. Li et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Digital plant phenotyping methods mainly use computer vision to collect accurate and objective phenotypic data. The accuracy and measurement speed of these methods can match and surpass human experts (Yol et al, 2015). The most widespread methods apply two-dimensional (2D) red, green, and blue (RGB) imaging to measure morphological properties of plants.…”

Section: Introductionmentioning

confidence: 99%

“…The effectiveness of the breeding process can be further improved by studying the relationship between genotype, phenotype and environment (Houle et al, 2010) for these aspects. These studies require high quality genotypic, phenotypic and environmental datasets (Yol et al, 2015). Current phenotypic measurements, however, are mainly based on human observation and therefore tend to be subjective and descriptive, limiting the quantity and the quality of the observations (Gehan & Kellogg, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Digital plant phenotyping in three dimensions: what’s the point?

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Phenomics in Crop Plants: Trends, Options and Limitations

Cited by 48 publications

References 0 publications

Effect of heat stress on common bean under natural growing conditions in three locations in different climate zones in the state of So Paulo, Brazil

Effect of heat stress on common bean under natural growing conditions in three locations in different climate zones in the state of So Paulo, Brazil

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant’s Abiotic Stress Tolerance Responses

Digital plant phenotyping in three dimensions: what’s the point?

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