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Information flow diagram for iPASTIC software.

Information flow diagram for iPASTIC software.

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Premise of the Study: In crop breeding programs, breeders use yield performance in optimal and stressful environments as key indicator for screening the most tolerant genotypes. Over four decades, several yield-based indices have been suggested for evaluating stress tolerance in crops. Despite the well-established use of these indices in agronomy a...

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Context 1
... addition to the web application, iPASTIC is available in R language for more advanced users. Figure 1 shows the information flow of this software. The software reads standard Microsoft Excel formats, hence it is easy and approachable even for users with limited knowledge of computer programming languages. ...
Context 2
... addition to the web application, iPASTIC is available in R language for more advanced users. Figure 1 shows the information flow of this software. The software reads standard Microsoft Excel formats, hence it is easy and approachable even for users with limited knowledge of computer programming languages. ...
Context 3
... addition to the web application, iPASTIC is available in R language for more advanced users. Figure 1 shows the information flow of this software. The software reads standard Microsoft Excel formats, hence it is easy and approachable even for users with limited knowledge of computer programming languages. ...

Citations

... Additionally, iPASTIC [54], an online toolset, calculated the stress tolerance index (STI) to screen better-performing genotypes under water stress conditions, and the genotypes with the lowest average sum of rankings (ASR) were considered the most tolerant. ...
... Using iPastic, an online toolbox created by Pour et al. [54], drought stress indices were calculated based on dry matter. According to the STI bar graph (Figure 5 ...
... Using iPastic, an online toolbox created by Pour et al. [54], drought stress indices were calculated based on dry matter. According to the STI bar graph ( ...
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Drought tolerance of Brassica crops can be genetically improved by establishing plant ideotypes with improved yield responses associated with agronomic traits and biochemical markers. The objective of this study was to compare 20 Brassica oleracea L. accessions grown under two different water treatments (100% and 35% reintegration of evapotranspiration by irrigation) to select potential tolerant genotypes for organic cultivation based on several agronomic and biochemical parameters measured in response to drought stress. Significant differences were registered for the genotype and the irrigation regime and for their interaction (p < 0.0001 ***). A principal component analysis was performed to summarize the correlations among the analyzed phytochemicals and the stressed and not stressed genotypes and highlighted the importance of the antioxidant compounds as stress biomarkers. The present results showed that drought significantly reduces growth parameters and increases the amount of ascorbic acid and polyphenols compared to the irrigated control. Additionally, the results show that antioxidant metabolism increased by drought in some genotypes while others maintained a good biomass production by increasing the value of growth parameters considered. Based on the average sum of ranks (ASR) of morpho-physiological and biochemical parameters, the genotypes CR, CC, and BH were determined to be the most drought tolerant, whereas CI5, BU, and CV1 were determined to be the most susceptible. Due to the potential of these genotypes, further molecular and cellular research will be carried out to identify the genetic marker associated with the water stress response.
... The percentage changes in antioxidant profiles and dry biomass were estimated as used by Pour-Aboughadareh et al. [9]. To identify the most tolerant individuals from each species, the stress tolerance index (STI) was calculated using the iPASTIC toolkit [41]. To group the measured traits and to study the relationships among biochemical features with dry biomass, principal component analysis (PCA) was performed using the 'factoextra', 'ggdendro', and 'ggplot2' packages of R software [40]. ...
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In the present study, we estimated genetic diversity and population structure in 186 accessions of Triticum and Aegilops species using 24 simple sequence repeat markers (SSR). Furthermore, an association analysis was performed for antioxidant activities, including guaiacol peroxidase (GPX), ascorbate peroxidase (APX), peroxidase (POX), catalase (CAT), and dry matter (DM) under two control and drought stress conditions. Our findings showed that drought treatment significantly decreased DM, whereas activities of all antioxidant enzymes were increased compared to the control conditions. The results of correlation analysis indicated that, under drought stress conditions, all biochemical traits had a positive and significant association with each other and with dry matter. In the molecular section, the results of the analysis of molecular variance (AMOVA) indicated that the molecular variation within species is more than within them. The dendrogram obtained by cluster analysis showed that grouping the investigated accessions was in accordance with their genomic constitutions. The results of association analysis revealed 8 and 9 significant marker-trait associations (MTA) under control and drought stress conditions, respectively. Among identified MTAs, two associations were simultaneously found in both growing conditions. Moreover, several SSR markers were associated with multiple traits across both conditions. In conclusion, our results could provide worthwhile information regarding marker-assisted selection for the activity of antioxidant enzymes in future breeding programs.
... Similarly, other studies have shown the negative effect of stress on various phenotypic traits grown under stress and non-stress environments (Arif et al., 2021;Jeffrey et al., 2021;Jha et al., 2021). Yield is a crucial trait and an important indicator to define tolerance between stress and non-stress conditions and has been used to describe the performance of any genotype while screening in various environments (Kaloki et al., 2019;Pour-Aboughadareh et al., 2019). Moreover, in the current study seed yield was among the phenotypic traits measured in all years, locations, and seeding dates. ...
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Chickpea is a cool season crop that is highly vulnerable to abiotic stresses such as heat and drought. High temperature during early flowering and pod development stages significantly reduces the crop yield. The wild relatives of chickpeas can be potential donors for the introgression of heat and drought tolerance into cultivated chickpeas for crop improvement. Initially, 600 interspecific lines were derived from crosses between two elite cultivars, CDC Leader (kabuli chickpea) and CDC Consul (desi chickpea), and 20 accessions of Cicer reticulatum. The F5 interspecific lines were tested for agronomic and seed quality traits including reaction to ascochyta blight disease under field conditions at two locations in 2018. A subset of 195 lines were selected based on resistance to ascochyta blight and acceptable seed quality. These lines were evaluated for their performance under suboptimal conditions at Lucky Lake (2019 and 2020) and Moose Jaw (2019), Saskatchewan, Canada, and Yuma, Arizona, United States (2019–2020). The lines were grown and evaluated at two seeding dates, normal (SD1) and late (SD2) seeding dates, at each location and year. The same lines were genotyped using Cicer60K Axiom® SNP chip. The population structure was determined based on 35,431 informative SNPs using fastStructure, and the interspecific lines were clustered at a k-value of 15. Significant marker-trait associations were identified for seed yield from SD1 and SD2 seeding dates, and stress tolerance indices (ATI, K1STI, MP, SSPI, and TOL) using phenotypic values both from individual locations and combined analyses based on BLUP values. SNP marker Ca2_34600347 was significantly associated with yield from both the seeding dates. This and other SNP markers identified in this study may be useful for marker-assisted introgression of abiotic stress tolerance in chickpea.
... These indices have been used to identify tolerant genotypes for a variety of abiotic stresses, such as drought, heat and salt stress (Bouslama and Schapaugh, 1984;Dhanda and Munjal, 2006;Morton et al., 2019). To compound the information obtained by single screening indices which proved there usability in the past, toolkits such as iPASTIC or other composite selection index have been developed to enhance the detecting power of yield-based screenings (Pour-Aboughadareh et al., 2019;Sabouri et al., 2022). ...
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Modern plant cultivars often possess superior growth characteristics, but within a limited range of environmental conditions. Due to climate change, crops will be exposed to distressing abiotic conditions more often in the future, out of which heat stress is used as example for this study. To support identification of tolerant germplasm and advance screening techniques by a novel multivariate evaluation method, a diversity panel of 14 tomato genotypes, comprising Mediterranean landraces of Solanum lycopersicum, the cultivar “Moneymaker” and Solanum pennellii LA0716, which served as internal references, was assessed toward their tolerance against long-term heat stress. After 5 weeks of growth, young tomato plants were exposed to either control (22/18°C) or heat stress (35/25°C) conditions for 2 weeks. Within this period, water consumption, leaf angles and leaf color were determined. Additionally, gas exchange and leaf temperature were investigated. Finally, biomass traits were recorded. The resulting multivariate dataset on phenotypic plasticity was evaluated to test the hypothesis, that more tolerant genotypes have less affected phenotypes upon stress adaptation. For this, a cluster-analysis-based approach was developed that involved a principal component analysis (PCA), dimension reduction and determination of Euclidean distances. These distances served as measure for the phenotypic plasticity upon heat stress. Statistical evaluation allowed the identification and classification of homogeneous groups consisting each of four putative more or less heat stress tolerant genotypes. The resulting classification of the internal references as “tolerant” highlights the applicability of our proposed tolerance assessment model. PCA factor analysis on principal components 1–3 which covered 76.7% of variance within the phenotypic data, suggested that some laborious measure such as the gas exchange might be replaced with the determination of leaf temperature in larger heat stress screenings. Hence, the overall advantage of the presented method is rooted in its suitability of both, planning and executing screenings for abiotic stress tolerance using multivariate phenotypic data to overcome the challenge of identifying abiotic stress tolerant plants from existing germplasms and promote sustainable agriculture for the future.
... A more detailed explanation of different stress indices can be found in review papers such as Morton et al. [165]. Pour-Aboughadareh et al. [166] developed a user-friendly software-iPASTIC-to facilitate the different stress indices calculations when using large datasets. New VIs and stress indices will continue to be developed, which will greatly broaden abiotic stress research areas. ...
Article
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Farmers and breeders aim to improve crop responses to abiotic stresses and secure yield under adverse environmental conditions. To achieve this goal and select the most resilient genotypes, plant breeders and researchers rely on phenotyping to quantify crop responses to abiotic stress. Recent advances in imaging technologies allow researchers to collect physiological data non-destructively and throughout time, making it possible to dissect complex plant responses into quantifiable traits. The use of image-based technologies enables the quantification of crop responses to stress in both controlled environmental conditions and field trials. This paper summarizes phenotyping imaging technologies (RGB, multispectral and hyperspectral sensors, among others) that have been used to assess different abiotic stresses including salinity, drought and nitrogen deficiency, while discussing their advantages and drawbacks. We present a detailed review of traits involved in abiotic tolerance, which have been quantified by a range of imaging sensors under high-throughput phenotyping facilities or using unmanned aerial vehicles in the field. We also provide an up-to-date compilation of spectral tolerance indices and discuss the progress and challenges in machine learning, including supervised and unsupervised models as well as deep learning.
... Calculating all of the indices individually and then analysing them for superior genotype identification takes a long time. Pour Aboughadareh et al. (2019) created Plant Abiotic Stress Index Calculator (iPLASTIC) a GUI based programme to address this issue. Recently, the iPLASTIC software was used to screen genotypes and germplasm for drought tolerance in barley (Lateef et al., 2021); wheat and wheat for metal tolerance (Belay et al., 2021). ...
Article
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Drought, in addition to adverse climatic change, is a primary driver of yield loss in essential grain crops. An essential plant breeding goal and the goal of this experiment was to develop drought-tolerant post-rainy season sorghum lines for higher yield under both well-water and water stress situations. Drought stress indices are one of the methods for identifying and selecting superior genotypes that are stable, high-yielding, and drought tolerant. The Plant Abiotic Stress Index Calculator (iPASTIC), an online software that calculates common stress tolerance and susceptibility indices for various crop traits, was used to find superior genotypes using tolerance index (TOL), mean productivity (MP), harmonic mean (HM), yield stability index (YSI), geometric mean productivity (GMP), stress susceptibility index (SSI), stress tolerance index (STI), relative stress index (RSI), and yield index (YI). In this work, 45 Near isogenic lines (NILs) from crosses (SPV86 × E36-1, SPV570 × E36-1 and M35-1 × E36-1) were screened with the nine drought stress indices and all genotypes were differentiated under well-water and water stress conditions. NILs 34, 21, 44, 7 and 9 were identified as the top five superior high yielding and drought tolerant genotypes based on these indices, correlation and principal component analysis. These improved genotypes can be used in further field evaluation and advanced breeding efforts to generate drought-tolerant cultivars.
... The differences between genotype means across trials were visualized using barplots with error bars in ggplot2 [27] We computed nine stress tolerance indices, namely the tolerance index (TOL), relative stress index (RSI), mean productivity (MP), harmonic mean (HM), yield stability index (YSI), geometric mean productivity (GMP), stress susceptibility index (SSI), stress tolerance index (STI), and yield index (YI). We generated the ranking patterns of the genotypes based on each stress index and computed the average sum rank for all indices to identify heat tolerant genotypes [28]. The lower the average sum rank, the more heat-tolerant the genotype. ...
... Pearson correlation between indices and fruit weight per plant under optimal and heat stress conditions were generated and visualized using a correlogram. All the analyses related to the stress indices were performed in iPASTIC [28].We explored the relationship between genotypes and stress tolerance indices through a principal component analysis with a biplot of genotypes and indices and fruit weight per plant under optimal and stress conditions using the package factoextra [29] in R 4.0.5 [30]. ...
... There were discrepancies in the ranking of the genotypes between indices. This supports the idea of using several stress tolerance indices to increase the likelihood of identifying highly performing genotypes [28,44,45]. Besides, the differences in genotype ranking in the long-term heat stress conditions indicates that the genotypes responded differently to the heat stress conditions in terms of their fruit weight per plant. ...
Article
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Tomato production in coastal areas in West Africa is constrained by heat stress. There is currently limited empirical evidence on the extent of the effect of heat stress on tomato yield in the sub-region. In this study, we assessed the effects of heat stress on yield and yield components among 16 tomato genotypes with varying heat tolerance status and explored the potential of stress tolerance indices to identify heat tolerant genotypes. The experiments were conducted under three temperature and humidity regimes, namely optimal season (28.37/23.71 °C and 71.0/90.4% day/night), long-term mild and humid (greenhouse, 30.0/26.2 °C and 77.6/97.2%), and long-term mild and dry (open field, 31.50/28.88 °C and 66.72/77.82%) heat stress (HS). All genotypes exhibited significantly higher fruit set percentage, fruit number per plant, fruit weight, and fruit weight per plant in the optimal season compared to both heat stress conditions. In general, the genotypes demonstrated higher performance under dry HS (i.e., HS in open field HSO) than humid HS (i.e., HS in greenhouse HSG). Fruit set decreased by 71.5% and 68.3% under HSG and HSO, respectively, while a reduction of 75.1% and 50.5% occurred in fruit weight per plant under HSG and HSO, respectively. The average sum of ranks values from nine stress tolerance indices and fruit weight per plant (used as proxy trait of yield) identified CLN2498D, CLN3212C, CLN1621L, and BJ01 as heat tolerant under HSG and BJ01, BJ02, Fla.7171, and P005 as heat tolerant under HSO. Fruit weight per plant under long-term heat stress (Ys) and optimal growing conditions (Yp) were suitable to select high performing genotypes under HSO, HSG, and optimal conditions while relative stress index, yield stability index, yield index, stress susceptibility index, and harmonic mean were suitable to select heat tolerant genotypes under either HSG or HSO. Our findings shed light on the extent of the effect of HS on tomato production in the off-season in coastal areas in West Africa and provide new insight concerning the heat tolerance status of the evaluated tomato genotypes.
... To validate the results and also to determine the performance of genotypes with a high SCY and good fiber quality across normal and heat stress, 3D scatterplots were constructed based on stress tolerance indices, including mean performance (MP), geometric mean performance (GMP), and stress tolerance index (STI) for normal and heat stress with the help of the freely available online software package iPASTIC developed by Pour-Aboughadareh et al. (2019). To rank and identify the best genotypes having stable and better yields across both conditions, the representative trait was used according to the method given by Ketata et al. (1989). ...
Article
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The ever-changing global environment currently includes an increasing ambient temperature that can be a devastating stress for organisms. Plants, being sessile, are adversely affected by heat stress in their physiology, development, growth, and ultimately yield. Since little is known about the response of biochemical traits to hightemperature ambiance, we evaluated eight parental lines (five lines and three testers) and their 15 F1 hybrids under normal and high-temperature stress to assess the impact of these conditions over 2 consecutive years. The research was performed under a triplicate randomized complete block design including a split-plot arrangement. Data were recorded for agronomic, biochemical, and fiber quality traits. Mean values of agronomic traits were significantly reduced under heat stress conditions, while hydrogen peroxide, peroxidase, total soluble protein, superoxide dismutase, catalase (CAT), carotenoids, and fiber strength displayed higher mean values under heat stress conditions. Under both conditions, high genetic advance and high heritability were observed for seed cotton yield (SCY), CAT, micronaire value, plant height, and chlorophyll-a and b content, indicating that an additive type of gene action controls these traits under both the conditions. For more insights into variation, Pearson correlation analysis and principal component analysis (PCA) were performed. Significant positive associations were observed among agronomic, biochemical, and fiber quality-related traits. The multivariate analyses involving hierarchical clustering and PCA classified the 23 experimental genotypes into four groups under normal and high-temperature stress conditions. Under both conditions, the F1 hybrid genotype FB-SHAHEEN � JSQ WHITE GOLD followed by Ghuari-1, CCRI-24, Eagle-2 � FB-Falcon, Ghuari-1 � JSQ White Gold, and Eagle-2 exhibited better performance in response to high-temperature stress regarding the agronomic and fiber quality-related traits. The mentioned genotypes could be utilized in future cotton breeding programs to enhance heat tolerance and improve cotton yield and productivity through resistance to environmental stressors.
... To validate the results and also to determine the performance of genotypes with a high SCY and good fiber quality across normal and heat stress, 3D scatterplots were constructed based on stress tolerance indices, including mean performance (MP), geometric mean performance (GMP), and stress tolerance index (STI) for normal and heat stress with the help of the freely available online software package iPASTIC developed by Pour-Aboughadareh et al. (2019). To rank and identify the best genotypes having stable and better yields across both conditions, the representative trait was used according to the method given by Ketata et al. (1989). ...
Article
Full-text available
The ever-changing global environment currently includes an increasing ambient temperature that can be a devastating stress for organisms. Plants, being sessile, are adversely affected by heat stress in their physiology, development, growth, and ultimately yield. Since little is known about the response of biochemical traits to high-temperature ambiance, we evaluated eight parental lines (five lines and three testers) and their 15 F 1 hybrids under normal and high-temperature stress to assess the impact of these conditions over 2 consecutive years. The research was performed under a triplicate randomized complete block design including a split-plot arrangement. Data were recorded for agronomic, biochemical, and fiber quality traits. Mean values of agronomic traits were significantly reduced under heat stress conditions, while hydrogen peroxide, peroxidase, total soluble protein, superoxide dismutase, catalase (CAT), carotenoids, and fiber strength displayed higher mean values under heat stress conditions. Under both conditions, high genetic advance and high heritability were observed for seed cotton yield (SCY), CAT, micronaire value, plant height, and chlorophyll-a and b content, indicating that an additive type of gene action controls these traits under both the conditions. For more insights into variation, Pearson correlation analysis and principal component analysis (PCA) were performed. Significant positive associations were observed among agronomic, biochemical, and fiber quality-related traits. The multivariate analyses involving hierarchical clustering and PCA classified the 23 experimental genotypes into four groups under normal and high-temperature stress conditions. Under both conditions, the F 1 hybrid genotype FB-SHAHEEN × JSQ WHITE GOLD followed by Ghuari-1, CCRI-24, Eagle-2 × FB-Falcon, Ghuari-1 × JSQ White Gold, and Eagle-2 exhibited better performance in response to high-temperature stress regarding the agronomic and fiber quality-related traits. The mentioned genotypes could be utilized in future cotton breeding programs to enhance heat tolerance and improve cotton yield and productivity through resistance to environmental stressors.
... Correlation between drought tolerance indices (heat-map), genotypes rank due to drought tolerance indices and principal component analysis based on correlation matrix were estimated using Plant Abiotic Stress Index Calculator (iPASTIC) online toolkit program developed by Pour-Aboughadareh et al. [33]. ...
Article
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Drought is one of the biggest obstacles facing the cultivation and production of the sesame crop, especially in areas where there is shortage of water or unequal rain. An investigation was done to assess the effect of deficit irrigation on agro-morphological, yield traits and stress tolerance indices of eight sesame genotypes and their twenty-eight (F 1) crosses. The parents selected for a half-diallel crosses were unique and diverse. The experiment was conducted during the summer season, 2017 and 2018 at Field Crops Research Institute, ARC, Giza, Egypt. Deficit irrigation was induced by preventing two irrigations, at initial of flowering and before maturity; while normal irrigation applied as recommended. Nine stress tolerance indices were deeply estimated as selection criteria for identification of drought tolerant genotypes under moderate level of drought stress (Stress Intensity SI=0.25). Data revealed that irrigation regimes affected all studied traits significantly. Genotypes and interaction between irrigation regimes x genotypes were highly significant for all morphological, yield and seed chemical composition traits. Among the parents, P5(N.A.604), P6(Shandweel 3) and P4(Um Shagera) and the crosses, G16(P 2 XP 3), G35(P 6 XP 8), G27(P 4 XP 5), G36(P 7 XP 8), G10(P 1 XP 3) and G26(P 3 XP 8) were obtained the highest seed yield. According to drought tolerance indices rank average, the parents, P4(Um Shagera), P7(B21-3) and P5(N.A.604); and the F 1 , G22(P 3 XP 4), G16(P 2 XP 3), G34(P 6 XP 7), G23(P 3 XP 5), G35(P 6 XP 8) and G36(P7XP8) were the most drought tolerant genotypes performed will under both stress and non-stress conditions, with minimum reduction in seed yield under stress condition. In addition, the parents P4(Um Shagera), P7(B21-3), and P1(N.A.373); and the F 1 G28(P 4 XP 6), G34(P 6 XP 7), G22(P 3 XP 4), Brima et al. 68 G23(P 3 XP 5), G14(P 1 XP 7) and G25(P 3 XP 7) scored the highest yield stability index and relative stress index. So, the drought tolerant parents were recommended for further breeding program; also, selection should be focused on F 1 progenies that performed well under both stress and non-stress conditions in the coming segregating generations to select drought tolerant lines.