Geometric Mean Productivity Research Articles

Applying an artificial neural network approach for drought tolerance screening among Iranian wheat landraces and cultivars grown under well-watered and rain-fed conditions

In the current study, an α-lattice design was used to investigate 320 Iranian bread wheat cultivars and landraces under non-stressed and rain-fed conditions, according to phenological, morphological and physiological parameters. An artificial neural network (ANN) was trained to evaluate the relative importance of different drought tolerance indices (DTIs) using a multilayer perceptron model. Our findings suggest that the Iranian wheat germplasm harbors large genetic diversity for all the studied traits. Correlation analyses highlighted the important role of seed number per spike, thousand kernel weight, leaf greenness and canopy temperature in predicting grain yield under both non-stressed and rain-fed conditions. Moreover, correlations between stressed-yield (Ys) and yield index (YI, r = 1**), harmonic mean (HM, r = 0.94**), geometric mean productivity (GMP, r = 0.86**), and stress tolerance index (STI, r = 0.86**) were all large, which was further confirmed by the results of ANN and a principal component analysis. A hierarchical clustering, visualized using a heatmap plot, classified cultivars and landraces into four separate groups, where high-yielding and drought-tolerant genotypes clustered in the same group. The result of ANN indicated that MP and YI had the highest relative importance for screening compatible genotypes for well-watered and rain-fed conditions, respectively. Overall, the selection of genotypes according to agronomic and physiological traits in association with an appropriate DTI can identify favorable wheat genotypes in a field trial to breed for well-watered and water-limited environments. Furthermore, the ANN successfully evaluated the relative importance of different DTIs in wheat.

Tolerance Indices and Cluster Analysis to Evaluate Some Bread Wheat Genotypes under Water Deficit Conditions

The present study was carried-out at the Experimental Farm of Sakha Agricultural Research Station, during2017/2018 and 2018/2019 seasons to evaluate eighteen bread wheat genotypes including fourteen promising lines and fourcultivars namely; Sakha 93, Sakha 95, Giza 171 and Shandaweel 1 under normal irrigation and deficit conditions.Additionally, six selection indices were used to identify the best genotypes that might be grown under water deficitcondition using different drought indices namely; Mean Productivity (MP), Harmonic Mean (HM), Geometric MeanProductivity (GMP), Stress Tolerance Index (STI), Yield Index (YI), and Modified Stress Tolerance Index (MSTI). Theresults indicated that, the effect of the irrigation treatments, genotypes and their interactions were significantly different inmost studied characteristics. The means of all genotypes significantly decreased in all characters except for, prolinecontent that was increased in the two growing seasons under water deficit conditions compared with to normal condition.Genotype 5 recorded the highest number of spikes /m², while the heaviest 1000-kernel weight was produced from Giza171 under normal and water deficit condations. Sakha 95 gave the highest values for grain yield under both conditions.Based on drought indices HM, GMP, STI, YSI and MSTI, genotype 3 followed by Sakha 95, Shandweel 1, genotype 5and Giza 171 were identified as suitable genotypes for water deficit conditions. The cluster analysis classified the testedgenotypes into five main different groups, each group contained similar genotypes similar based on grain yield and stresstolerance indices. The fifes cluster consisted of one genotype (Sakha 95) that recorded high grain yield and stresstolerance degree followed by the third cluster which consisted of genotypes 3, 5, Giza 171 and Shandaweel 1 which had amoderate grain yield and tolerance to water deficit genotypes. So these genotypes might be used as parents in breedingprogrames to produce new genotypes with desirable characters related to drought tolerance.

IPASTIC: An online toolkit to estimate plant abiotic stress indices.

PremiseIn crop breeding programs, breeders use yield performance in both optimal and stressful environments as a key indicator for screening the most tolerant genotypes. During the past 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 and plant breeding, a user‐friendly software that would provide access to these methods is still lacking.Methods and ResultsThe Plant Abiotic Stress Index Calculator (iPASTIC) is an online program based on JavaScript and R that calculates common stress tolerance and susceptibility indices for various crop traits including 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). Along with these indices, this easily accessible tool can also calculate their ranking patterns, estimate the relative frequency for each index, and create heat maps based on Pearsonʼs and Spearmanʼs rank‐order correlation analyses. In addition, it can also render three‐dimensional plots based on both yield performances and each index to separate entry genotypes into Fernandezʼs groups (A, B, C, and D), and perform principal component analysis. The accuracy of the results calculated from our software was tested using two different data sets obtained from previous experiments testing the salinity and drought stress in wheat genotypes, respectively.Conclusions iPASTIC can be widely used in agronomy and plant breeding programs as a user‐friendly interface for agronomists and breeders dealing with large volumes of data. The software is available at https://mohsenyousefian.com/ipastic/.

Genetic Behavior of Some Rice Genotypes under Normal and High Temperature Stress

Thirteen rice genotypes were grown in the two successive rice seasons 2017 and 2018 to assess the presence of variability for desired traits and estimate genetic parameters and correlations for traits under normal and heat stress conditions. Analysis of variance revealed significant differences due to environments, genotypes and their interaction for all studied characteristics in both seasons. The estimates of genotypic (GCV) and phenotypic (PCV) coefficient of variation were highly significant for all studied traits and generally, the PCV values were higher than GCV values, in both seasons. Leaf rolling and sterility percentage increased under heat stress, while days to heading, plant height, number of tillers and number of panicles / plant, 100-grainweight and grain yield/plant decreased under heat stress in comparison to normal condition. As mean performance Giza 179, Giza 178 and Sakha 101 surpassed other genotypes in grain yield and its important attributes, while WAB56-50/Sakha101-1, WAB56-50/Sakha101-2 and IR65907-206-7-8/Gyehwa71 gave the lowest grain yield in both seasons. Giza178 and WAB56-50/Sakha101-1 recorded the lowest values of geometric mean productivity, stress susceptibility index and yield index which refer to those genotypes highly tolerance to heat stress, while Giza 177 and Sakha 101 gave the highest values to be the most heat susceptible genotypes under study. Highly positive and significant phenotypic correlations were observed between yield index and leaf rolling, sterility percentage, geometric mean productivity and stress susceptibility index, otherwise number of tillers/plant, number of panicles/panicle and panicle weight, as yield attributes had highly significant negative correlation with the yield index. From the results we can conclude that, the genotypes can be scored as heat tolerant, based on days to heading, leaf rolling, tillering productivity and spikelets sterility percentage.

Evaluation of Yield-Based Low Nitrogen Tolerance Indices for Screening Maize (Zea mays L.) Inbred Lines

To screen the desired criterion to identify desirable genotypes and select genotypes best suited to limited nitrogen availability in order to facilitate the practice of low-nitrogen-tolerant breeding in maize, the response of 31 maize inbred lines, containing four control inbred lines (PH6WC, PH4CV, Zheng58, and Chang7-2) and others selected from the Shaan A and Shaan B heterotic groups cultivated at Northwest A&F University (Yangling, Shaanxi, China), were evaluated. The experiment was conducted following a split plot design with two replications during three growing seasons (2015, 2016, and 2017) under both high nitrogen (HN) and low nitrogen (LN) conditions at the Yulin and Yangling in Shaanxi Province, China. Seven screening indices, based on grain yield under two contrasting nitrogen (N) conditions, the stress susceptibility index (SSI), yield stability index (YSI), mean productivity (MP), geometric mean productivity (GMP), stress tolerance index (STI), harmonic mean (HM), and low nitrogen tolerance index (LNTI), were computed to assess the overall index that accurately screened the desirable genotypes. The results of the correlation analyses and principal component analysis showed that MP, GMP, HM and STI were correlated with grain yield significantly and positively under contrasting N conditions, and were able to accurately discriminate the desirable genotypes. Compared with the control inbred lines, many inbred lines selected from the Shaan A and Shaan B groups showed a higher LN tolerance. This shows that we can effectively improve the LN tolerance of maize inbred lines through LN screening. Based on the screening indices, the three-dimensional diagram and genotype and genotype × environment (GGE) biplots are agreed with this results, and we identified KA105, KB081, KA225, 91227, and 2013KB-47 as the desired genotypes that have the potential to be used to breed a high yield and stable hybrid.

Assessment of Variability for Drought Tolerance Indices in Some Wheat ( Triticum aestivum L.) Genotypes

Estimation of nine yield-based drought tolerance indices was studied in ten wheat genotypes and identification of best index and best drought tolerant genotype. Nine drought tolerance indices comprising stress tolerance index (STI), tolerance index (TOL), stress susceptibility index (SSI), geometric mean productivity (GMP), mean productivity (MP),harmonic mean (HAM), yield index (YI), yield stability index (YSI) and drought resistance index (DRI) were each estimated based on yield under non-stress (Yp) and stress condition (Ys). The results of the genetic analysis for all drought tolerance indices studied demonstrated that GMP, MP and HAM had less variation between phenotypic coefficients of variability and genotypic coefficient of variability corresponded to high heritability. GMP, MP and HAM werenominated as the best useful indices that looking for drought tolerant genotypes. Also, they had positive correlation with Yp and Ys. The genotypes 1, 6 and 10 were considered drought tolerant while genotypes 3, 4, 5, 7 and 9 as drought susceptible. Genotype 8 was identified as highly drought susceptible. The studied genotypes showed considerable variation in performance and tolerated various drought conditions that could be exploited in further investigation.

Evaluating drought tolerance of castor ecotypes in the center of Iran

In order to study the reaction of six castor ecotypes to drought stress, a split plot experiment was carried out in randomized complete blocks. Eight indices including stress sensitivity index (SSI), tolerance index (TOL), mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HARM), stress tolerance index (STI), sensitivity drought index (SDI) index and yield index (YI) were calculated for ecotypes by using seed yield in normal condition and under stress. After that, correlations between indices were calculated and dendrogram and biplot results were drawn. Normal yield and stress yield had positive significant correlations with MP, GMP, STI, and HARM indices in mild, moderate and severe stresses. Biplot analysis showed that Isfahan and Naein ecotypes had desirable yield under mild and average stress and Naein had desirable yield under severe stress and also normal condition.

Yield and seed quality parameters of common bean cultivars grown under water and heat stress field conditions

Drought and heat stress strongly influence common bean development. The aim of this work was to study the effect of water stress on yield and quality traits of four common bean cultivars under xerothermic Mediterranean conditions. The field experiments were conducted under normal and water stress (50% of the normal) conditions applied 25 days after seed emergence (first flower buds visible). Agronomic, physiomorphological, quality traits and drought indices were assessed. Water stress reduced the number of pods plant−1 (53%), seeds pod−1 (9.7%), harvest index (49%) and seed yield (58%). Cultivar ‘Cannellino’ provided the higher performance both under normal and water stressed conditions and exhibited the lower drought susceptibility index and the highest mean productivity and geometric mean productivity across water treatments. These results were attributed primarily to the earliness of the cultivar ‘Cannellino’ which enabled avoidance of very high temperatures and severe drought and to the robustness and quick pod set. Valuable genetic variability was also observed for important quality seed traits (cooking time, protein). In conclusion, water stress is a significant limiting factor for seed yield and quality traits eventhough, suitable cultivars (i.e. ‘Cannellino’, ‘G. Northern’) were indentified in the course of this study. It is suggested that breeders select for early-flowering and quick pod-setting varieties to reduce the negative effects of water and heat stress in these environments.

WHEAT (TRITICUM AESTIVUM L.) PRODUCTION UNDER DROUGHT AND HEAT STRESS – ADVERSE EFFECTS, MECHANISMS AND MITIGATION: A REVIEW

Heat and drought stresses are the most important abiotic factors that reduce crops productivity by affecting various physiological and biochemical processes. Thus, selecting cultivars with better drought or heat stress tolerance or breeding for stress tolerance will be helpful in enhancing crop productivity under harsh environments. This review elaborates the physiological basis of high temperature and drought stress tolerance in wheat which can be used as selection criteria in wheat breeding program. In addition, some agronomic selection criteria which are valid and useful in selecting stress tolerant wheat species and cultivars. The review also discussed the valid usage of stress tolerance indices (such as mean productivity (MP), geometric mean productivity (GMP), yield index (YI), yield stability index (YSI), relative productivity (RP%), stress susceptibility index (SSI), and the tolerance index (TOL)) to scan the genotypes against drought and heat stress. Beside these, exogenous application of stress signaling compounds, osmolytes, or certain inorganic salts play a vital role for alleviating adverse effects of abiotic stresses for sustainable wheat production. In addition, applications for soil amendments will also helpful in increasing wheat crop productivity under stressful conditions. All these strategies may be helpful to meet the food demands of the increasing population.

Canopy Temperature and Chlorophyll Content are Effective Measures of Drought Stress Tolerance in Durum Wheat

Durum wheat (Triticum durum L.) is used for the preparation of multiple food products, including pasta and bread. Its production is restricted due to diverse environmental stresses i.e. drought and heat stress. Here, comparative analysis of durum wheat varieties was done by studying canopy temperature depression (CTD) and chlorophyll content (CHL), yield and yield contributing traits to evaluate their performance under stress and low stress conditions. Twelve durum wheat genotypes were studied under stressful and low-stress conditions in Gachsaran region of Iran. CTD and CHL were measured at two stages, from the emergence of fifty percent of inflorescence (ZGS 54) to watery ripe stage (ZGS 71). According to stress tolerance index (STI), mean productivity (MP) and geometric mean productivity (GMP) indices, genotype G10 exhibited the most, while genotype G6, the least relative tolerance, respectively. Based on MP and GMP, genotype G10 was found to be drought tolerant, while genotype G2 displayed the lowest amount of MP and GMP. Therefore these genotypes are recommended to be used as genitors in artificial hybridization for improvement of drought tolerance in other cultivars. All indices had high correlation with grain yield under stress and non-stress condition, indicating more suitability of these indices for selection of resistant genotype. Results of the present study showed that among drought tolerance indices, harmonic mean (HM), GMP, CTD and modified STI index (K2STI) can be used as the most suitable indicators for screening drought tolerant cultivars.

Determining the best drought tolerance indices using Artificial Neural Network (ANN): Insight into application of intelligent agriculture in agronomy and plant breeding

In the present study, efficiency of the artificial neural network (ANN) method to identify the best drought tolerance indices was investigated. For this purpose, 25 durum genotypes were evaluated under rainfed and supplemental irrigation environments during two consecutive cropping seasons (2011–2013). The results of combined analysis of variance (ANOVA) revealed that year, environment, genotype and their interaction effects were significant for grain yield. Mean grain yield of the genotypes ranged from 184.93 g plot–1 under rainfed environment to 659.32 g plot–1 under irrigated environment. Based on the ANN results, yield stability index (YSI), harmonic mean (HM) and stress susceptible index (SSI) were identified as the best indices to predict drought-tolerant genotypes. However, mean productivity (MP) followed by geometric mean productivity (GMP) and HM were found to be accurate indices for screening drought tolerant genotypes. In general, our results indicated that genotypes G9, G12, G21, G23 and G24 were identified as more desirable genotypes for cultivation in drought-prone environments. Importantly, these results could provide an evidence that ANN method can play an important role in the selection of drought tolerant genotypes and also could be useful in other biological contexts.

Evaluation of eight white maize inbred lines and their diallel crosses to study the variation in response to water deficit

A half diallel was done among eight white maize inbred lines. Two experiments were laid out in randomized complete block design (RCBD) with three replications to evaluate the eight parental lines and their 28 crosses at both normal and drought stress conditions at Mallawi Agricultural Research Station, Minia, Egypt. Data were recorded for the following traits from 10 guarded plants of each genotype: silking and tassel date to estimate anthesis-silking interval (ASI), plant height (cm), leaf senescence, leaf proline content (mg/g) and grain yield per plant (g) which was adjusted for 15.5% moisture. The effect of irrigation treatments was highly significant for all traits under study except for anthesis-silking interval (ASI), indicating that these traits were affected by water stress. All studied materials were affected by water stress. Nine crosses were selected based on the percentage of yield reduction, three crosses out of them, i.e. Gz-6×Gz-7, Gz-5×Gz-7 and Gz-5×Sd-3 were performed as best crosses under both irrigation systems and selected as tolerant crosses based on mean productivity (MP), stress tolerance index (STI), Geometric mean productivity (GMP) and harmonic mean (MHAR) indices. While, based on drought sensitive index (DSI) and stress tolerance indices, the crosses Gz-6×Sd-3, Gz-2×Gz-4 and Gz-4×Sd-2 were identified as tolerant crosses. Thus, we can use to detect crosses which had high performance under water stress or which had less yield reduction in drought maize breeding programs and can be cultivated in new lands under drip or sprinkler irrigation system.

GENETIC VARIATION AND INTERRELATIONSHIPS AMONG AGRONOMIC TRAITS IN BREAD WHEAT GENOTYPES UNDER WATER DEFICIT AND NORMAL IRRIGATION CONDITIONS

Water deficit is one of the major stresses that reducing wheat production particularly under current climate change. The aim of this study was to investigate the genotypic variation of thirty bread wheat genotypes under water deficit and normal irrigation conditions. In addition, to clarify the association between grain yield and the other important agronomic traits, and to determine the interrelationships among the tested traits under both conditions. Two field experiments were carried out in New Valley, Agricultural Research Station conditions, Agricultural Research Center, Egypt during 2014-2015 and 2015-2016 growing seasons. Thirty bread wheat genotypes were evaluated under two irrigation regimes. The normal irrigation was used every 15 days (NI) with total nine irrigation times per season (2900 m3/fad.). The other irrigation regime was applied every 30 days giving in total five irrigation times (1900 m3/fad.) providing water deficit conditions (WD). The experimental design was laid out in a spilt-plot in which irrigation treatments were in the main plots and genotypes were randomized in the sub-plots, in three replications. All evaluated traits were affected significantly by irrigation treatments. The genotypes; G1, G2, G17, G21, G22, G23, G24 and G27 exhibited good grain yield/plant and its components under both conditions. Tolerance indices; mean productivity (MP), geometric mean productivity (GMP), stress tolerance index (STI) and yield index (YI) were calculated based on grain yield/plant under both conditions. The highest indices were observed for G21, G2 and G1 genotypes followed by G23, G27 and G24 genotypes. Based on these indices, the genotypes were classified into three groups A (drought tolerant), B (moderate drought-tolerant) and C (drought-sensitive) with 8, 18 and 4 genotypes, respectively. Furthermore, phenotypic and genotypic correlation coefficients were estimated and it was observed strong and significant positive correlation between grain yield and 100-grain weight, grain weight/spike, biological yield/plant and harvest index under both conditions. Additionally, path analysis was calculated and it was found that biological yield and harvest index exhibited the highest positive direct effect on grain yield under both conditions. On the other hand, the highest indirect effects on grain yield were assigned for number of spikes/plant followed by flag leaf area, grain weight/spike and 100-grain weight under both conditions. Which demonstrates the importance of these traits in improving grain yield under both conditions.

Evaluation of Guar (Cyamopsis tetragonoloba L.) genotypes performance under different irrigation water salinity levels: Growth parameters and seed yield

Water scarcity and salinity are the major challenges faced by arid regions such as Thar Desert in Pakistan. Developing information on salt tolerance of genotypes and appropriate salinity management practices are necessary to ensure long-term viability of agriculture in these stressed environments. This study evaluated growth and seed yield of 25 different guar genotypes irrigated with waters having varying salinity (control – 0.6, 3, 6 and 9 dS m−1) under field conditions to characterize their salt tolerance. Results indicated salinity levels had significant influence on growth and yield of guar crop. At the highest salinity level of 9 dS m−1, out of 26 genotypes three genotypes (S-6005, S-8885 and 2/1) showed less than 20% reduction in plant height, one genotype (BR 90) had 15% reduction in number of branches and two genotypes (S-6049 and S-5611) produced 70% of the branches compared to control. Seed yields of genotypes ranged from 0.94 to 1.82 Mg ha−1 under control salinity but at 9 dS m−1 it ranged from 0.28 to 0.89 Mg ha−1. BR 99 produced highest seed yield under both control and highest salinity levels. Straw yield ranged from 0.89 to 3.34 Mg ha−1 under control and the range was reduced to 0.57 to 1.4 Mg ha−1 at 9 dS m−1. Sodium concentration increased whereas K concentration and K/Na ratio decreased with increasing salinity levels in both straw and seed samples of all the guar genotypes evaluated in this study. Based on salinity tolerance index (STI) and geometric mean productivity (GMP), out of 25 guar genotypes only four (BR-99, S-5608, 2/1, S-5615 and S-8885) were considered as tolerant. Results of our study indicated that select genotypes of guar can be appropriate for water scarce and salt affected arid regions of the world.

Effect of Drought Stress on Growth and Yield of Wheat Genotypes

A pot experiment on screening of wheat genotypes against drought stress was conducted at the research field of Sher-e-Bangla Agricultural University in earthen pots during rabi season of 2013-2014. Fifteen (15) wheat genotypes were evaluated under drought (stress was imposed by withdrawing irrigation after emergence) and well irrigated (control) condition. Exposure of plants to drought led to remarkable reduction in yield contributing characters which ultimate caused in reduced yield in all the genotypes. However, genotypes showed remarkable variability in yield reduction due to drought. The highest relative yield was observed in genotype SATYN-25 followed by SATYN-2, BARI Gom-26 and BARI Gom-28. However, yield reduction was less in SATYN-25 (about 20%) followed by BARI Gom-26 (21%) and SATYN-2 (25%). Besides yield performance of the genotypes, some drought tolerance indices like Geometric Mean Productivity (GMP), Stress Tolerance Index (STI), Yield Stability Index (YSI) and Stress Susceptible Index (SSI) were used to select the desirable genotypes. Among the genotypes, BARI Gom-26, BARI Gom-28 and SATYN-25 gave better yield with higher STI, GMP and YSI with lower SSI indicating that these genotypes would be suitable for growing under drought prone areas.Bangladesh Agron. J. 2017, 20(2): 97-105

Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r2 ≥ 0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.

Heat tolerance indices and their role in selection of heat stress tolerant chickpea (Cicer arietinum) genotypes

Given the current scenario of global climate change, high temperature stress is appearing as a major challenge limiting crop productivity including chickpea (Cicer arietinum L.). Evidences of significant yield loss in chickpea due to high temperature stress encountering during reproductive stage has been recorded. Therefore, to sustain chickpea productivity, identification of heat stress (HS) tolerant chickpea via recruiting ‘breeder’s friendly’ selection criteria based on yield traits under field condition is urgently needed. In our current study, we evaluated 78 chickpea genotypes (including 3 checks) in 5 blocks in augmented design under normal and late sown condition during 2015-16. Various HS tolerance indices, viz. mean productivity (MP), geometric mean productivity (GMP), yield index (YI), tolerance index (TOL), stress susceptibility index (SSI) and superiority measure (SM) were employed for identifying chickpea genotype based on grain yield under normal and HS conditions. Based on the important selection indices, viz. YI, MP, GMP and SSI the following genotypes RVG 203, RSG 888, JAKI 9218, GNG 469, IPC 06-11 showed higher to moderate heat tolerance. Positive and high significant correlation of Yp with Ys, MP, YI, GMP, SSI and TOL was recorded. Likewise, Ys showed positive and high significant correlation with MP and GMP. While, YI indicated significant and high positive correlation with MP and GMP, but it showed negative correlation with SSI. Importantly, MP and GMP both showed high and positive correlation with SSI and TOL, respectively. Importantly, principal component analysis lowered all the six indices into 2 components PC1 explaining 61.9% and PC2 explaining 37.1% of total variation. While, 3-D scatter plot analysis grouped all the genotypes into four groups. Likewise, considering cluster analysis, four distinct clusters were generated based on above-mentioned various indices. Towards this end, correlation analysis, 3-D scatter plot and cluster analysis explained that the most effective and efficient selection indices for identifying heat tolerant genotype are MP, YI, GMP and SSI.

EVALUATION OF DROUGHT TOLERANCE IN NEW COTTON CULTIVARS USING STRESS TOLERANCE INDICES

Drought is a wide-spread problem seriously influencing production and quality ofcotton (Gossypium hirsutum L.), but development of resistant cultivars is hamperedby the lack of effective selection criteria. The objective of this study was toevaluate the ability of several selection indices to identify drought tolerant cultivarsunder different environmental conditions. Thirteen cotton cultivars were evaluatedunder both moisture stress (2016) and non-stress (2013) field environments using arandomized complete block design for each environment. Six drought toleranceindices including stress susceptibility index (SSI), stress tolerance index (STI),tolerance index (TOL), mean productivity (MP), geometric mean productivity(GMP) and mean harmonic productivity (HMP) were used. The significant andpositive correlation of yield of genotype under non-stress condition (Yp) and MP,GMP and STI showed that these indices were more effective in identifying highyielding cultivars under different moisture conditions. The results of calculatedgain from indirect selection in moisture stress environment would improve yieldbetter than selection from non moisture stress environment. Coton breeders should,therefore, take into account the stress severity of the environment in choosing anindex. The varieties Viki and Avangard-264 had the highest yields under non-stressconditions. Vega and Chirpan-539 varieties had a low yield potential and showed ahigh stress tolerance to drought.

Multivariate approach to identify and characterize bread wheat (Triticum aestivum) germplasm for waterlogging tolerance in India

An experiment was conducted for evaluating the performance of 149 elite Indian and Australian germplasm lines under normal and waterlogged soil conditions over two years (2014–15 and 2015–16), revealed significant differences for all the studied traits under waterlogged as well as under normal soil conditions. Waterlogging adversely affected thousand kernel weight, tillers per meter, biological yield and grain yield. The three morphological traits namely; biological yield, tillers per meter and plant height significantly contributed towards waterlogging tolerance. The geometric mean productivity (GMP), harmonic mean (HM), stress tolerance index (STI), mean productivity (MP) and mean relative performance (MRP), were significantly and positively correlated with grain yield under waterlogged (Ys) as well as under normal soil conditions (Yp). Whereas, yield stability index (YSI) was found positively correlated with grain yield only under waterlogged soil conditions (Ys) in both years as well as over the years. Besides, GMP, HM, MP, MRP and STI were also significantly correlated with each other in individual year as well as across years, indicating thereby that any one of these parameters might be used as an alternative option to each other for selecting high yielding genotypes under both the conditions (waterlogging and normal). The promising lines identified based on GMP, STI, MP, HM and MRP could also be rated as tolerant being high yielding particularly for waterlogging condition. The two parameters (YSI and reduction percentage) identified as effective selection indices clearly discriminated the per se performance of genotypes based on stable performance under waterlogged conditions, and thus these could be used an indicative approach of germplasm lines possessing waterlogging tolerance genes. The correlation values also supported results and indicated strong association of biological yield with yield stability index. The germplasm lines namely; UP 2584, TINCURRIN, SSD-C2-172, SSD-C2-151, SSD-C2 204, SSD-C2 140, RW 3684, NW 4098, KRL 105, K 307, HD 3086, HD 2329, DUCULA 4 and CUNDERIN were identified to be capable of producing highest biomass and also higher values for YSI among all lines taken for this study. Based on both YSI and biological yield, lines CUNDERIN, DUCULA 4, HD 3086, KRL 105 and RW 3684 were identified to as tolerant and could be utilized as potential donor for increasing waterlogging tolerance of future wheat genotypes. Our research findings also imply that tolerant lines eventually would lead to higher productivity under stress situations, where heavy rainfall and stagnation of water for a prolonged period adversely affect the wheat crop. The results of the present study based on field screening technique and the selection criteria based upon indices will be rewarding for increasing grain yield of wheat under such harsh environments.

Differential Response to Salt Stress Within and Among Iranian Melilotus Species

ABSTRACTThis paper explores the salt-tolerance response of Melilotus species, a forage legume, based on tolerance/susceptibility indices, leaf water relations, leaf/root ion concentrations and multivariate (factor and function discriminate) analyses. In a greenhouse experiment, salinity-susceptibility of 12 accessions of Melilotus (M. albus, M. indicus, M. officinalis) in addition, two controls (alfalfa and Persian clover) were evaluated at 0 mM, 100 mM, 200 mM, and 300 mM of sodium chloride (NaCl). The experiment was conducted in a split plot design with two replications. Stress tolerance score (STS) was calculated based on tolerance/susceptibility indices. Salt-tolerant accessions were identified. An extracted bi-plot based on factor analysis confirmed the results of tolerance/susceptibility indices. There were significant correlations between STS and multivariate statistics. Root potassium cation (K+) concentration was higher in Melilotus species than the control species in all the salinity treatments. STS, root K+ concentration, leaf turgidity, and leaf succulence characteristics can be used for screening salinity-tolerance in Melilotus accessions. In all treatments, M. officinalis, M. indicus, and M. albus were salinity-tolerant species in descending order.Abbreviations: Total biomass yield under control (Yp) and stress (Ys) mediums, geometric mean productivity (GMP), leaf area (LA), leaf tissue density (LTD), linear regression coefficient (b), mean productivity (MP), relative water content (RWC%), Succulence (S), specific leaf area (SLA), stress susceptibility index (SSI), stress tolerance index (STI), tolerance (TOL), water content at saturation (WCS), water saturation deficit (WSD), sodium chloride (NaCl), potassium cation (K+), sodium cation (Na+), analysis of variance (ANOVA), least significant difference (LSD), alfalfa control accession (CHA), Persian clover control accession (CHC), coefficient of variation (CV), statistics of factor (F) and discriminate function (D)