Genetic Parameters, Multivariate Analysis and Tolerance Indices of Rice Genotypes under Normal and Drought Stress Environments

Drought is the most challenging abiotic stress for rice production in the world. Thus, developing new rice genotype tolerance to water scarcity is one of the best strategies to achieve and maximize high yield potential with water savings. The study aims to characterize 16 rice genotypes for grain and agronomic parameters under normal and drought stress conditions, and genetic differentiation, by determining specific DNA markers related to drought tolerance using Simple Sequence Repeats (SSR) markers and grouping cultivars, establishing their genetic relationship for different traits. The experiment was conducted under irrigated (normal) and water stress conditions. Mean squares due to genotype × environment interactions were highly significant for major traits. For the number of panicles/plants, the genotypes Giza179, IET1444, Hybrid1, and Hybrid2 showed the maximum mean values. The required sterility percentage values were produced by genotypes IET1444, Giza178, Hybrid2, and Giza179, while, Sakha101, Giza179, Hybrid1, and Hybrid2 achieved the highest values of grain yield/plant. The genotypes Giza178, Giza179, Hybrid1, and Hybrid2, produced maximum values for water use efficiency. The effective number of alleles per locus ranged from 1.20 alleles to 3.0 alleles with an average of 1.28 alleles, and the He values for all SSR markers used varied from 0.94 to 1.00 with an average of 0.98. The polymorphic information content (PIC) values for the SSR were varied from 0.83 to 0.99, with an average of 0.95 along with a highly significant correlation between PIC values and the number of amplified alleles detected per locus. The highest similarity coefficient between Giza181 and Giza182 (Indica type) was observed and are susceptible to drought stress. High similarity percentage between the genotypes (japonica type; Sakha104 with Sakha102 and Sakha106 (0.45), Sakha101 with Sakha102 and Sakha106 (0.40), Sakha105 with Hybrid1 (0.40), Hybrid1 with Giza178 (0.40) and GZ1368-S-5-4 with Giza181 (0.40)) was also observed, which are also susceptible to drought stress. All genotypes are grouped into two major clusters in the dendrogram at 66% similarity based on Jaccard’s similarity index. The first cluster (A) was divided into two minor groups A1 and A2, in which A1 had two groups A1-1 and A1-2, containing drought-tolerant genotypes like IET1444, GZ1386-S-5-4 and Hybrid1. On the other hand, the A1-2 cluster divided into A1-2-1 containing Hybrid2 genotype and A1-2-2 containing Giza179 and Giza178 at coefficient 0.91, showing moderate tolerance to drought stress. The genotypes GZ1368-S-5-4, IET1444, Giza 178, and Giza179, could be included as appropriate materials for developing a drought-tolerant variety breeding program. Genetic diversity to grow new rice cultivars that combine drought tolerance with high grain yields is essential to maintaining food security.

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Over-Optimistic Projected Future Wheat Yield Potential in the North China Plain: The Role of Future Climate Extremes

Agronomy ◽

10.3390/agronomy12010145 ◽

2022 ◽

Vol 12 (1) ◽

pp. 145

Author(s):

Rui Yang ◽

Panhong Dai ◽

Bin Wang ◽

Tao Jin ◽

Ke Liu ◽

...

Keyword(s):

Drought Stress ◽

North China Plain ◽

North China ◽

Crop Yields ◽

Wheat Yield ◽

Yield Potential ◽

Severe Drought ◽

The North ◽

The North China Plain ◽

Stress Environments

Global warming and altered precipitation patterns pose a serious threat to crop production in the North China Plain (NCP). Quantifying the frequency of adverse climate events (e.g., frost, heat and drought) under future climates and assessing how those climatic extreme events would affect yield are important to effectively inform and make science-based adaptation options for agriculture in a changing climate. In this study, we evaluated the effects of heat and frost stress during sensitive phenological stages at four representative sites in the NCP using the APSIM-wheat model. climate data included historical and future climates, the latter being informed by projections from 22 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) for the period 2031–2060 (2050s). Our results show that current projections of future wheat yield potential in the North China Plain may be overestimated; after more accurately accounting for the effects of frost and heat stress in the model, yield projections for 2031-60 decreased from 31% to 9%. Clustering of common drought-stress seasonal patterns into key groups revealed that moderate drought stress environments are likely to be alleviated in the future, although the frequency of severe drought-stress environments would remain similar (25%) to that occurring under the current climate. We highlight the importance of mechanistically accounting for temperature stress on crop physiology, enabling more robust projections of crop yields under future the burgeoning climate crisis.

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Morphological Characterization of Different Rice Genotypes under Drought Stress Conditions

International Journal of Current Microbiology and Applied Sciences ◽

10.20546/ijcmas.2021.1002.267 ◽

2021 ◽

Vol 10 (2) ◽

pp. 2243-2252

Author(s):

Ritika Yadav ◽

Gurdeep Bains

Keyword(s):

Drought Stress ◽

Morphological Characterization ◽

Stress Conditions ◽

Rice Genotypes

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Discrimination of drought tolerance in a worldwide collection of safflower (Carthamus tinctorius L.) genotypes based on selection indices

Acta agriculturae Slovenica ◽

10.14720/aas.2021.117.1.1656 ◽

2021 ◽

Vol 117 (1) ◽

pp. 1

Author(s):

Pooran GOLKAR ◽

Esmaeil HAMZEH ◽

Seyed Ali Mohammad MIRMOHAMMADY MAIBODY

Keyword(s):

Drought Stress ◽

Drought Tolerance ◽

Geometric Mean ◽

Resistance Index ◽

Stability Index ◽

Carthamus Tinctorius ◽

Tolerance Index ◽

Breeding Programs ◽

Drought Tolerance Indices ◽

Tolerance Indices

Improvement of elite safflower genotypes for drought-tolerance is hampered by a deficiency of effective selection criteria. The present study evaluated 100 genotypes of safflower in terms of their drought tolerance over a period of three years (2016–2018) under both non-stress and drought-stress conditions. The eight drought-tolerance indices of tolerance index (TOL), mean productivity (MP), geometric mean productivity (GMP), stress susceptibility index (SSI), stress tolerance index (STI), yield stability index (YSI), drought resistance index (DI), and harmonic mean (HARM) were calculated based on seed yield under drought (Ys) and non-drought (Yp) conditions. A high genetic variation was found in drought tolerance among the genotypes studied. The MP, GMP, and STI indices were able to discriminate between tolerant and drought-sensitive genotypes. Plots of the first and second principal components identified drought-tolerant genotypes averaged over the three study years. Cluster analysis divided the genotypes into three distinct groups using the drought tolerance indices. Ultimately, eight genotypes (namely, G3, G11, G13, G24, G33, G47, G58, and G61) from different origins were detected as more tolerant to drought stress suitable for use in safflower breeding programs in drought-affected areas. The most tolerant and susceptible genotypes could be exploited to produce mapping populations for drought tolerance breeding programs in safflower.

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Evaluation of Drought Tolerance Indices in Rice Genotypes (Oryza Sativa L.)

Journal of Crop Breeding ◽

10.29252/jcb.10.25.7 ◽

2018 ◽

Vol 10 (25) ◽

pp. 7-18

Author(s):

Sanam Safaei Chaeikar ◽

Babak Rabiei ◽

Mehdi Rahimi ◽

◽

...

Keyword(s):

Oryza Sativa ◽

Drought Tolerance ◽

Oryza Sativa L ◽

Rice Genotypes ◽

Drought Tolerance Indices ◽

Tolerance Indices

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Estimation of Genetic Parameters for Peak Yield, Yield and Persistency Traits in Murciano-Granadina Goats Using Multi-Traits Models

Animals ◽

10.3390/ani9070411 ◽

2019 ◽

Vol 9 (7) ◽

pp. 411

Author(s):

Judith C. Miranda ◽

José M. León ◽

Camillo Pieramati ◽

Mayra M. Gómez ◽

Jesús Valdés ◽

...

Keyword(s):

Multivariate Analysis ◽

Selection Criteria ◽

Genetic Parameters ◽

Genetic Correlations ◽

Multiple Trait ◽

Lactation Curve ◽

Derivative Free ◽

Selection For ◽

Estimated Breeding Values ◽

Estimation Of Genetic Parameters

This paper studies parameters of a lactation curve such as peak yield (PY) and persistency (P), which do not conform to the usual selection criteria in the Murciano-Granadina (MG) breed, but are considered to be an alternative to benefit animal welfare without reducing production. Using 315,663 production records (of 122,883 animals) over a period of 24 years (1990–2014), genetic parameters were estimated with uni-, bi- and multivariate analysis using multiple trait derivative free restricted maximum likelihood (MTDFREML). The heritability (h2)/repeatability (re) of PY, yield (Y) and P was estimated as 0.13/0.19, 0.16/0.25 and 0.08/0.09 with the uni-trait and h2 of bi- and multi-traits analysis ranging from 0.16 to 0.17 of Y, while that of PY and Y remained constant. Genetic correlations were high between PY–Y (0.94 ± 0.011) but low between PY–P (–0.16 ± 0.054 to –0.17 ± 0.054) and between Y–P (–0.06 ± 0.058 to –0.05 ± 0.058). Estimates of h2/re were low to intermediate. The selection for Y–PY or both can be implemented given the genetic correlation between these traits. PY–P and Y–P showed low to negligible correlation values indicating that if these traits are implemented in the early stages of evaluation, they would not be to the detriment of PY–Y. The combination of estimated breeding values (EBVs) for all traits would be a good criterion for selection.

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A Comparative Study for Assessing the Drought-Tolerance of Chickpea Under Varying Natural Growth Environments

Frontiers in Plant Science ◽

10.3389/fpls.2020.607869 ◽

2021 ◽

Vol 11 ◽

Author(s):

Anjuman Arif ◽

Najma Parveen ◽

Muhammad Qandeel Waheed ◽

Rana Muhammad Atif ◽

Irem Waqar ◽

...

Keyword(s):

Drought Stress ◽

Drought Tolerance ◽

Seed Yield ◽

Linear Models ◽

Field Conditions ◽

Sufficient Evidence ◽

Breeding Lines ◽

Drought Tolerance Indices ◽

Tolerance Indices ◽

Main Effects

This study was planned with the purpose of evaluating the drought tolerance of advanced breeding lines of chickpea in natural field conditions. Two methods were employed to impose field conditions; the first: simulating drought stress by growing chickpea genotypes at five rainfed areas, with Faisalabad as the non-stressed control environment; and the second: planting chickpea genotypes in spring to simulate a drought stress environment, with winter-sowing serving as the non-stressed environment. Additive main effects and multiplicative interaction (AMMI) and generalized linear models (GLM) models were both found to be equally effective in extracting main effects in the rainfed experiment. Results demonstrated that environment influenced seed yield, number of primary and secondary branches, number of pods, and number of seeds most predominantly; however, genotype was the main source of variation in 100 seed weight and plant height. The GGE biplot showed that Faisalabad, Kallur Kot, and Bhakkar were contributing the most in the GEI, respectively, while Bahawalpur, Bhawana, and Karor were relatively stable environments, respectively. Faisalabad was the most, and Bhakkar the least productive in terms of seed yield. The best genotypes to grow in non-stressed environments were CH39/08, CH40/09, and CH15/11, whereas CH28/07 and CH39/08 were found suitable for both conditions. CH55/09 displayed the best performance in stress conditions only. The AMMI stability and drought-tolerance indices enabled us to select genotypes with differential performance in both conditions. It is therefore concluded that the spring-sown experiment revealed a high-grade drought stress imposition on plants, and that the genotypes selected by both methods shared quite similar rankings, and also that manually computed drought-tolerance indices are also comparable for usage for better genotypic selections. This study could provide sufficient evidence for using the aforementioned as drought-tolerance evaluation methods, especially for countries and research organizations who have limited resources and funding for conducting multilocation trials, and performing sophisticated analyses on expensive software.

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