High-yielding Genotypes Research Articles

Current Insights into Various In Vitro Dihaploidization Techniques Used in Brassica Oil Crops

Brassicas are considered the third most important source of vegetable oil globally. With the escalating production of Brassica varieties, there is growing demand for high-yielding genotypes. Doubled haploid (DH) techniques have become very popular in various Brassica breeding programs. Such DH techniques can play a significant role in plant breeding by accelerating the production of homozygous lines and increasing selection efficiency. Among these methods, isolated microspore culture stands out as the most effective, facilitating the generation of a higher number of embryos compared to conventional methods of plant breeding. Different chemical compounds such as herbicides, brassinosteroids, and polyethylene glycol have an antimitotic effect and have been found to generate DH plants and improve microspore embryogenesis in Brassica species. Colchicine and trifluralin have proven to be efficient chromosome-doubling agents as well as important supplements that can increase the rate of embryogenesis. This review serves as a comprehensive summary and effectiveness evaluation of the latest research findings in the Brassica oil crops to help increase efficiency of the future research focusing on DH methods and application of antimitotic agents in the various oilseed species of the genus Brassica.

Development of Bread Wheat (Triticum aestivum L.) Varieties for Lowland Areas of Ethiopia and Registration of the “Asgori” Variety

Identifying improved crop varieties is crucial for Ethiopia's diverse agroecologies, as different crops respond differently. To meet food grain demand, stable, high-yielding genotypes and resistance to diverse factors are needed. Conducting trials in multiple locations is essential. Multi-location trials in Ethiopia from 2020-2021 involved 75 advanced bread wheat genotypes across 13 environments. The finest genotype, exhibiting high grain yield and stability, was selected based on its performance across different locations. In comparison to the Control Ogolcho, Hawi, Kakaba, Kingbird, Deka, Abay, Dursa, Balcha, and EBW192369, Asgori demonstrated significantly improved agronomic characteristics and enhanced yield by 121.6%, 53.9%, 29.6 %, 29.2%, 14.8%, 13.6%, 9.6%, 5.3%, and 4.1%, respectively. The newly chosen and released genotype, named Asgori, with the pedigree of MUTUS*2/HARIL#1/3/SWSR22T.B./2*BLOUK#1//WBLL1*2/KURUKU/4/MUTUS*2/HARIL#1, was officially developed by the Kulumsa Agricultural Research Center, Ethiopia Institute of Agricultural Research in 2023. Asgori is a widely adaptable, high-yielding, medium, erect cultivar with excellent end-use qualities. It is resistant to leaf rust, yellow rust, and stem rust, and has been approved for cultivation under rain-fed conditions.

Genetic analyses of advanced breeding lines of rice for yield-attributing traits and salinity stress tolerance

The development of advanced rice breeding lines and their evaluation for yield-attributes and salinity stress tolerance offers a significant opportunity to identify high-yielding salt-tolerant genotypes exhibiting desired traits. The present study aimed to examine the morpho-genetic variability of thirty-six advanced breeding lines of rice, with a focus on features that contribute to yield and salinity stress tolerance. Three replications of a randomized complete block design were used in the first experiment. Significant variability was observed among the lines for the studied quantitative traits. Based on yield attributing traits, the advanced breeding lines viz., Line 10, Line 21, Line 22, Line 23, Line 24 and Line 25 showed better performances in terms of earliness and yield. In yield-related variables such as the number of effective tillers per plant, plant height, and grain yield per plant exhibited high heritability coupled with high genetic advance as percentage of mean. The results of PCA biplot showed that the PC1 and PC2 accounted for the greatest variability of advanced Line 10, Line 11, Line 18, Line 21, Line 22, Line 23, Line 24, Line 25, Nerica 10, Begunipata, and Binadhan-14 with significant influence of the studied traits. Cluster analysis reflected that the high-yielding genotypes were placed in cluster II and VI. Highest genetic distance was observed among the genotypes of cluster III and cluster VI. In the second experiment, four advanced breeding lines along with salt tolerant and susceptible checks were assessed for salinity tolerance at the reproductive stage. The plants were cultivated in a large plastic-tub filled with field soil. During the late booting stage, saline (EC=10 dS/m) irrigation water was applied to the plants and continued for three weeks. While Lines 10 and 12 demonstrated a reduced decline, salt stress caused a significant loss in yield and yield-attributing characteristics in all genotypes. Line 10 and Line 12 which showed a reasonable degree of salt tolerance as well as early maturity were placed in the respective quadrant of the biplot. Stress tolerance indices also reflecting the better salt tolerance phenomena of the advanced Line 10 and Line 12. Considering all of the traits, Line 10 and Line12 could be selected as desired advanced rice lines for the development of early, high-yielding and salt tolerant rice varieties.

Maize yield is associated with abscisic acid and water potential under reduced soil water supply but with indoleacetic acid in genotypic renewal

Irrigation and breeding are important practices for improving yield and water use efficiency of maize (Zea mays L.) in arid regions. However, the physiological mechanisms of yield under varying water supplies and genotypes remain unclear. Here, we examine the different physiological mechanisms underlying maize yield responses to varying soil water supplies and three genotypes (MC670, ZD958, and ZD2#) cultivated in northwestern China over the past five decades. The declining water supply significantly reduced maize leaf hydraulic transport, stomatal conductance (gs), net photosynthetic rate (A), yield, kernel number, biomass, and evapotranspiration (ET). Conversely, it led to an increase in abscisic acid (ABA), hydrogen peroxide, intrinsic water use efficiency, and water productivity. Interestingly, there was no significant impact on indoleacetic acid (IAA), thousand kernel weight, or harvest index (HI). Breeding efforts increased leaf IAA levels, biomass, thousand kernel weight, yield, HI, and water productivity without altering physiological traits or ET. The superior yield of MC670 could be attributed to a simultaneous enhancement in both kernel number and thousand kernel weight, while ZD958 exhibited greater yield stability. ABA and hydraulic traits (predawn leaf water potential, leaf water potential, and whole-plant hydraulic conductance) coordinated gs under reduced soil water supply, while ABA and predawn leaf water potential regulated yield by modulating gs to affect both A and ET. Breeding for yield gains was associated with IAA-induced enhancements in biomass and HI, independent of key physiological traits (e.g., gs and A) and ET. The observed increase in water productivity primarily stemmed from notable yield improvements rather than alterations in ET. Hence, the selection of high-yielding genotypes under water-limited and well-watered conditions requires consideration of water-related physiological traits and IAA levels, respectively.

Approaches for Genetic Analysis of Chickpea Genotypes under Late Sown Condition

Investigation of the genetic potential of chickpeas is crucial in order to achieve durable and high-yielding genotypes. The goal of this study is to identify the genetic potential and personality traits associated. Evaluation of thirty-six desi genotypes of chickpea under late sown condition revealed that substantial degree of variation was present, while three traits viz., Leaf pattern, flower colour, seed shape and plant pigmentation were found monomorphic, whereas foliage colour, seed surface were dimorphic,polymorphic traits were noted in leaflet size, plant growth habit, plant height, seed colouring, days to 50% flowering and days to maturity. Magnitude of genotypic coefficient ofvariations, high heritability along with high genetic advance as percentage of mean recorded forharvest index, number of seeds per plant, number of pods per plant and number of effective pods per plant.Correlation and path analysis revealed biological yield, 100 seed weight, seed per plant, harvest Index and plant height are the mostimportant characters,while imparting selection as these exhibited strong association and maximum positive direct effects on seed yield per plant.Intra cluster D2 values showed that most diverse genotypes were Phule G13110 and PG 0104, hybridization program between these genotypes may generate desirable sergeants for various yield attributing traits. Genotypes GL 12021, PG 158, PG 0104, JG 24, H 12-62, IPC 2010-134, GNG 2261, GL29098, BG 3067, IPC 2012-98, Phule G13110 and RVSSG 38 were present in more than one PCs hence contributed maximum towards yield and can be used in various breeding programmes for yield improvement under late sown condition.

Evaluation of Bread Wheat (Triticum aestivum L.) Germplasm for Wheat Rust Diseases Resistance and Yield Performance

The most important biotic constraints for wheat production in Ethiopia are Wheat rust diseases, insects, and weeds. Among wheat rust diseases, stem rust and yellow rust are the more limiting factors for yield. A study was undertaken at Kulumsa and Melkasa in alpha lattice design with two replications from July to December 2023 to evaluate the performance of introduced bread wheat materials from CIMMYT for wheat rust diseases and yield. Data were collected for stem rust, yellow rust, and agronomic traits, including grain yield. The ANOVA showed high and significant genotypic variation (p<0.05) on Days to heading (DTH), Hectoliter weight (HLW), Thousand kernels weight (TKW), and Yield (YLD). Then, the result from LSD mean comparision revealed genotypes: EBW222102 YLD=7.7 t ha-1, EBW222106 YLD= 7.61 t ha-1, EBW222108 YLD=7.66 tha-1, EBW222136 YLD= 7.76 t ha-1 to be significantly higher than the check variety Daka YLD= 6.22 t ha-1 (p<0.05) at Kulumsa. Genotypes: EBW222108, EBW222109, EBW222111, EBW222112, EBW222114, EBW222125, EBW222142, and EBW222143 showed resistance to moderate resistance for yellow rust and stem rust across both locations. About eighteen genotypes were susceptible to stem rust diseases with the coefficient of infection YRCI≥30 at Melkasa. Genotypes EBW222111, EBW222126, EBW222129, EBW222134, and EBW222142 delivered high yield, greater than or equal to 2 t ha-1 at Melkasa. Generally, selection for disease resistance and high-yielding genotypes enable the development and release of noble varieties for wheat-producing farmers.

Characterization of high-yielding aman rice genotypes through genetic and agronomic analysis

ABSTRACT Rice (Oryza sativa L.) holds immense global significance, serving as a staple food crop that sustains billions of people and supports livelihoods across diverse cultures and economies, including Bangladesh. For food security in Bangladesh, there is a significant demand for high-yielding Aman rice varieties. We assessed genetic variability of 16 Aman rice genotypes, including 11 promising Aman lines and 5 established Aman cultivars in Bangladesh, with the aim of identifying high-yielding genotypes through a three-year field experiment. The examined genotypes displayed notable variations in both yield and agronomic traits contributing to yield, as evidenced by their greater range of coefficients of variance and genetic variability components. Traits such as effective tillers per hill (ET), filled grains per panicle (FG), plant height (PH) at 80 days after transplanting, and panicle length (PL) demonstrated notable correlations with grain yield (GY) throughout the three-year evaluation. Moreover, the higher broad-sense heritability (H 2) observed in ET, FG, PH, and PL traits suggested a substantial influence of genetic factors on the variability of the Aman rice genotypes. Principal component analysis based biplot and heatmap analyses revealed that the advanced lines BU acc4 and BU acc5 had higher harvest index and relatively greater GY compared to the other Aman rice varieties. These promising Aman lines could prove to be valuable materials for future multi-location yield trials or ongoing and forthcoming breeding programs aimed at enhancing high-yielding Aman rice cultivars.

Graphical Analysis of Multi-environmental Trials for Bread Wheat (Triticum aestivum L.) Grain Yield Based on GGE Bi-Plot Analysis

Bread wheat (Triticum aestivum L.) is a crucial crop in Ethiopia, and breeders test newly developed elite lines for superiority to existing cultivars to boost national productivity. The study was undertaken during the 2021–22 to 2022–23 cropping seasons at seven environments in optimum moisture areas of Ethiopian using 36 diverse and advanced bread wheat genotypes to evaluate the GEI by the graphical method of GGE biplot and to identify the genotypes with high mean yield performance and stability. Field experiments were conducted at the Adet, Asasa, Kulumsa, and Sinana research centers in Ethiopia. The experiments were planted in an alpha lattice design replicated three times in six rows of 2.5m long. Row-to-row distance and distance between blocks were 0.2m and 1.5m, respectively. The analysis of variance revealed that genotype, environment, and their interaction showed a highly significant effect on the yield as reflected in the GGE model and the GGE model indicated the suitability of the genotypes EBW202136 (33), Boru (1), and EBW202172 (12), with high mean yield and stability, whereas the genotypes EBW202185 (16) and Deka (36) produced high mean yield, but unstable. Likewise, the genotypes EBW202164 (27) and EBW202192 (29) produced low mean yield and unstable. The AMMI analysis of variance for grain yield across the environments showed that 17.26% of the total variation was attributed to genotypic effects, 64.03% to environmental effects, and 18.71% to GEI effects. Two mega environments were identified based on GGE biplot analysis and the which-won–model indicated the adaptation of genotypes Boru (1), EBW202159 (4), EBW202172 (12), EBW202171 (19), and EBW202136 (33) to first mega-environment and genotypes EBW202157 (3), EBW202166 (5), EBW202160 (6), EBW202162 (9), EBW202185 (16), Dursa (17) and Deka (36) in the second. These approaches allowed the identification of stable and high-yielding genotypes (EBW202136 (33) and EBW202172 (12)) which can be included in the national verification program, with a plan to release a new variety, and other genotypes with high yield could be utilized in breeding programs to further improve grain yield in bread wheat.

Evaluation of Kabuli Chickpea Genotypes for Tropical Adaptation in Northern Australia

Chickpea is one of the economically important legume crops adapted for winter season production in tropical climates. This study evaluated the physiological, morphological, and biochemical traits of eight Kabuli chickpea genotypes in an Australian tropical environment. The result revealed significant differences between genotypes for seed emergence, plant height, primary shoots, leaf number, leaf area index, gas-exchange parameters, seed yield, carbon discrimination (Δ13C), and natural abundance for nitrogen fixation. Among the tested genotypes, AVTCPK#6 and AVTCPK#19 exhibited late flowering (60–66 days) and late maturity (105–107 days), and had higher leaf photosynthetic rate (Asat) (28.4–31.2 µmol m−2 s−1), lower stomatal conductance (gsw) (516–756 mmol m−2 s−1), were associated with reduced transpiration rate (T) (12.3–14.5 mmol m−2 s−1), offered greater intrinsic water-use efficiency (iWUE) (2.1–2.3 µmol m−2 s−1/mmol m−2 s−1), and contributed a higher seed yield (626–746 g/m2) compared to other genotypes. However, a larger seed test weight (>60 g/100 seed) was observed for AVTCPK#24, AVTCPK#8, and AVTCPK#3. Similarly, a high proportion (45%) of larger seeds (>10–11 mm) was recorded for AVTCPK#24. Furthermore, a higher %Ndfa in AVTCPK#6 (71%) followed by AVTCPK#19 (63%) indicated greater symbiotic nitrogen fixation in high-yielding genotypes. Positive correlation was observed between %Ndfa and seed protein, as well as between seed yield and plant height, primary shoots, leaf count, leaf area index, leaf photosynthesis, stomatal conductance, transpiration rate at pod filling stage, biomass, and harvest index. An inverse correlation between (Δ13C) and iWUE, particularly in AVTCPK#6 and AVTCPK#19, indicates greater heat and drought tolerance, required for high-yielding Kabuli chickpea production in northern Australia.

Dependence of the yield in late-generation lines on the spike productivity in original segregating populations of spring bread wheat

Background. An ascertained possibility of culling segregating populations on the basis on their yield or grain weight per spike as a character closely correlated with yield can increase the efficiency of breeding practice with spring bread wheat. Materials and methods. Sixteen F2 –F4 segregating populations of spring bread wheat were assessed for their grain weight per spike, average grain weight per spike among the top 10%, coefficient of variation for grain weight per spike, and yield. The pedigree method was applied to select 2 to 3 F7 lines from each population. The obtained lines were tested for their yield in F8 and F9 . The data of grain weight per main spike in the parents that had been crossed to produce the studied segregating populations were retrospectively taken into account while the results were processed. Results Segregating populations persistently differed in their average grain weight per spike and the coefficient of its variation in different years of research. None of the 36 late-generation lines significantly surpassed the reference cultivar in yield. All the considered indicators of segregating populations had no significant correlations with the yield of late-generation lines. Average values of grain weight per main spike in the parent genotypes and the best parent as well as the differences between the parents in the average grain weight per main spike tended to have a negative correlation with the yield of late-generation lines (r up to –0.58). Conclusion. The culling of segregating populations based solely on the yield or grain weight per spike is associated with a risk of losing high-yielding genotypes. Late-generation lines with high yields occur in combinations where the grain weight per main spike in one parent or on average among the parents is not expressed to its highest level or when both parents differ only slightly from each other in the expression of this character.

Estimation of genetic variability for seed yield and yield related traits in mungbean [Vigna radiata (L.) Wilczek

Genetic variability is the most important factor for the success of any crop improvement program. Hence, the evaluation of genotypes has to be conducted as a preliminary step to study the extent of variability available in the genotypes and to identify suitable high-yielding genotypes that can be utilized in the crop improvement program. The present investigation was carried out to estimate genetic variability, heritability, and genetic advance for yield and yield contributing characters among 38 genotypes of mungbean for eleven quantitative traits. Significant differences were observed among genotypes for all eleven characters studied. The high degree of genetic variability along with high heritability and high genetic advance as percent of mean were recorded for seed yield per plant, harvest index, number of pods per plant, plant height, and the number of branches per plant which indicates that these characteristics were under the control of additive gene action and therefore, form the basis of selection for the mungbean improvement program.

Contrasted agronomical and physiological responses of five Coffea arabica genotypes under soil water deficit in field conditions.

Breeding programs have developed high-yielding Coffea arabica F1-hybrids as an adaptation against adverse conditions associated with climate change. However, theresponse to drought of coffee F1 hybrids has seldom been assessed. A trial was established with five C. arabica genotypes (2 pure lines: Catimor and Marsellesa and 3 F1 hybrids: Starmaya, Centroamericano and Mundo Maya) planted under the leguminous tree species Leuceana leucocephala. Coffee growth, yield and physiological responses were assessed under a rain-fed (control: CON) and a rainfall reduction treatment (RR) for 2 years. The RR treatment created a long-term rainfall deficit in a region with suboptimal temperature similar to those predicted by climate change scenarios. Moreover, the RR treatment reduced soil water content by 14% over 2 successive years of production and increased hydric stress of the three F1-hybrids (leaf water potentials averaged -0.8 MPa under RR compared with -0.4 MPa under CON). Under RR, coffee yields were reduced from 16 to 75% compared to CON. Mundo Maya F1 hybrid was the sole high-yielding genotype apable of sustaining its yield under RR conditions. Our results suggested that its significant increase in fine root density (CON = 300 and RR = 910 root.m-2) and its maintenance of photosynthetic rate (2.5 - 3.5 mmol CO2 m-2 s-1) at high evaporative demand might explain why this genotype maintained high yield under RR condition. This work highlights a possible drought tolerance mechanism in fruit bearing adult coffee trees where the plant fine root number increases to intake more water in order to preserve turgor and sustainphotosynthesis at high ETo and therefore conserves high yield in dry conditions.

Relationships between flowering behavior and seed yield in mungbean mutants

Flower is the prime sink that produces pods and yield depends on numbers and size of pods in legume crops. Flowering behavior affects the synchrony of pod maturity, which is crucial for efficient harvesing that regulates the yield. Thus, it is essential to study the relationship between flowering behavior and pod yield in mungbean mutants. This experiment was conducted using a Randomized Complete Block Design (RCBD) with three replications at the BINA headquarters physiology pot yard. The aim was to assess the relationship between flowering patterns, flowering duration, and seed yield in ten mungbean mutants/varieties. Results indicated that high-yielding mutant (MM-1) produced more opened flowers (38.0 flowers per plant) and had a longer flowering duration (12 days) compared to low-yielding varieties/mutants (13.1-18.0 flowers per plant and 7-9 days). Additionally, high-yielding varieties exhibited higher flower production rates over time, with peak flower production occurring within 5-8 days, while low-yielding varieties peaked within 3-4 days. High-yielding mungbean mutants/varieties exhibit lower pod set and reproductive efficiency (48.7-55.0%) compared to low-yielding ones (63.2-70.9%), indicating potential for yield improvement in high-yielding genotypes through enhanced pod set. Pod number, a key yield parameter, has a significant positive correlation with flower number (r = 0.56**), while pod number is also dependent on flowers per plant (r = 0.68**). Additionally, seed yield shows a strong positive relationship with the harvest index (r = 0.62**). These findings suggest that future breeding efforts should focus on synchronizing flower production to increase mungbean yield. Bangladesh J. Nuclear Agric, 38(1): 111-117, 2024

Genetic variability, character association and path coefficient analysis in okra

A study was conducted to investigate the genetic architecture of different lines for fruit yield and its associated traits in okra. Fourteen parents, consisting of twelve lines and two testers, were crossed using a Line × Tester mating design in the spring-summer season of 2019-20 at Vegetable Research Farm, CCSHAU, Hisar. The resulting twenty-four hybrids were cultivated in a randomized block design with three replications during the rainy season of 2020-21. Fruit yield/hectare showed a significant range from 87.86 to 150.18 quintals with an average of 117.73 quintals. The phenotypic coefficient of variation ranged from 3.91% (test weight) to 20.23% (Number of branches per plant), slightly surpassing the genotypic coefficient of variation which ranged from 1.98% (test weight) to 12.15% (fruit yield) with high estimate of PCV for the number of branches per plant (20.23%) and a moderate estimate of both PCV and GCV for fruit yield (14.67%, 12.15%), number of fruits per plant (14.34%, 12.06%), respectively. This suggests that the traits studied were more influenced by genetic factors than environmental factors. High heritability coupled with high genetic advance as percentage of mean for traits such as number of fruits/plant (70.74%, 20.89%) and fruit yield/hectare (68.65%, 20.74%) suggested that additive genes play a major role in determining these traits respectively. This indicates that it is possible to select high-yielding genotypes by selecting parents with desirable traits. Fruit yield/hectare displayed positive and significant associations with most of the traits like number of fruits per plant (0.95) and plant height (0.36) at phenotypic levels. The number of fruits per plant, 1000 seeds test weight, fruit diameter, and number of branches per plant had the most significant positive effect on fruit yield. Ultimately, such analysis has the potential to assist breeders in formulating their selection strategies aimed at enhancing fruit yield.

Image Analysis Artificial Intelligence Technologies for Plant Phenotyping: Current State of the Art

Modern agriculture is characterized by the use of smart technology and precision agriculture to monitor crops in real time. The technologies enhance total yields by identifying requirements based on environmental conditions. Plant phenotyping is used in solving problems of basic science and allows scientists to characterize crops and select the best genotypes for breeding, hence eliminating manual and laborious methods. Additionally, plant phenotyping is useful in solving problems such as identifying subtle differences or complex quantitative trait locus (QTL) mapping which are impossible to solve using conventional methods. This review article examines the latest developments in image analysis for plant phenotyping using AI, 2D, and 3D image reconstruction techniques by limiting literature from 2020. The article collects data from 84 current studies and showcases novel applications of plant phenotyping in image analysis using various technologies. AI algorithms are showcased in predicting issues expected during the growth cycles of lettuce plants, predicting yields of soybeans in different climates and growth conditions, and identifying high-yielding genotypes to improve yields. The use of high throughput analysis techniques also facilitates monitoring crop canopies for different genotypes, root phenotyping, and late-time harvesting of crops and weeds. The high throughput image analysis methods are also combined with AI to guide phenotyping applications, leading to higher accuracy than cases that consider either method. Finally, 3D reconstruction and a combination with AI are showcased to undertake different operations in applications involving automated robotic harvesting. Future research directions are showcased where the uptake of smartphone-based AI phenotyping and the use of time series and ML methods are recommended.

Stability analysis and identification of high-yielding Amaranth accessions for varietal development under various agroecologies of Malawi

AbstractAmaranth, with its high genetic variability, holds promise for global food security, income generation and climate resilience. Developing stable, high-yielding genotypes is essential for sustainable production. In this study, stability analysis was conducted on five Amaranth accessions over two seasons at three Malawian sites. Significant trait variations, including grain yield, plant height and leaf characteristics, underscored the dynamic nature of Amaranth cultivation. Notably, LL-BH-04 consistently exhibited superior grain yield, while others showed variable performance, highlighting the importance of stability analysis. Employing the Eberhart and Russell model, stable accessions in leaf and grain yield were identified. Additionally, AMMI (Additive Main effects and Multiplicative Interaction) biplot analysis revealed genetic diversity and stability patterns, aiding resilient cultivar selection. Consequently, LL-BH-04 and PE-UP-BH-01, identified as stable genotypes, were recommended for release, thereby enhancing agricultural sustainability and food security. These findings emphasize the need for site-specific breeding evaluations for sustainable productivity and underscore the importance of selecting stable cultivars to address agricultural challenges. LL-BH-04 and PE-LO-BH-01 were proposed for release to boost Amaranth production in Malawi, serving as the foundation for tailored breeding efforts aimed at improving productivity and resilience. This study contributes valuable insights into the stability and performance of Amaranth cultivars, offering guidance for sustainable crop production and variety development strategies.

Genotype by environment interaction effect and fresh root yield stability of cassava genotypes under contrasting nitrogen regimes

Nitrogen (N) is an important nutrient element needed by cassava for optimum yield and it is a vital component of nucleotides (nucleic acids), enzymes, amino acids (proteins), chlorophyll molecules and hormones, among other essential compounds required for growth and development of cassava. Nitrogen stress is a major cassava production constraint, the study aimed to examine genotype by environment interaction (GEI) effects and fresh root yield stability of 203 diverse cassava clones to identify genotypes with stable performance under low and optimum nitrogen regimes across environments using AMMI and GGE biplot analysis. Experiments were conducted using an augmented block design with three replications for two years in three locations in Nigeria. There were significant differences (p < 0.001) in the genotype’s mean performances as well as significant differences (p < 0.001) in the environment’s mean performances for all the traits measured in both nitrogen regimes. The AMMI analysis of variance showed significant effects (p < 0.001) for genotypes, environments and the interactions for fresh root yield in both nitrogen regimes. The biplot analysis showed that for fresh root yield in the optimum nitrogen regime, the principal component accounted for 81.54% of the G + GE (Genotype plus and Genotype by Environment) variation. The G + GE for fresh root yield in the low nitrogen regime accounted for a total of 71.64% of the variation. Ten genotypes were identified as the best genotypes under the optimum nitrogen regime, while eleven genotypes were the best under the low nitrogen regime. Three genotypes under optimum nitrogen regimes were high-yielding. Still, they were unstable in their fresh root yield performance across the environments and can be recommended as specifically adapted to the environments they performed best. Three other genotypes were high-yielding genotypes under low nitrogen but were highly unstable in their fresh root yield mean performance across the environments. The environments Otobi_YR1, Igbariam_YR2, and Umudike_YR1 were identified as the most discriminatory among the test environments. The environments Umudike_YR2 and Igbariam_YR1 were identified as the most representative of the test environments and can represent a mega-environment. The best 21 genotypes that performed above the grand mean for fresh root yield in both nitrogen regimes can be further evaluated on the farmer’s field for possible advancement.

Leveraging genetic resource diversity and identification of trait-enriched superior genotypes for accelerated improvement in linseed (Linum usitatissimum L.)

Linseed or flaxseed, native to the Indian subcontinent, had undergone domestication, edaphic selection and evolutionary processes that may have resulted in huge genetic variability in Indian genotypes. To understand the hitherto unexplored genetic diversity for sustainable flaxseed production amid challenges of climate fluctuation and identify trait-specific high-yielding genotypes, 2576 unique linseed accessions were comprehensively evaluated for 36 traits for up to six environments representing two major agroecological zones in India. A wide range of variability was recorded for days to initiation of flowering (42.86–114.99), plant height (43.31–122.88 cm), capsules/plant (64.62–375.87), seed size (6.06–14.44 cm2), thousand seed weight (2.80–11.86 g), seed yield (2.93–17.28 g/plant), oil content (30.14–45.96%) and fatty acid profile especially the key constituent omega-3 fatty acid (25.4–65.88%). Most of the traits such as plant height, flowering time, seed yield, seed and capsule size showed a high or moderately high level of variance coupled with high broad sense heritability indicating precise capturing of less heritable quantitative traits. The infraspecific classification of the tested collection revealed the seed/oil type (2498 accessions) as the dominant morphotype over dual-purpose/fiber flax (78 accessions) in the conserved collection. Correlation analysis indicated a significant positive association between flowering time, plant height, days to maturity and oil content. Trait-specific superior genotypes for earliness (50% flowering in < 60 days, maturity in < 122 days), bold seeds with high thousand seed weight (> 11 g), capsules/plant (> 350), oil content (> 45%) and fatty acid composition (> 65% alpha-linolenic acid) were identified to aid genetic improvement of linseed and to broaden the narrow genetic base.

Exploring genotype by environment interaction in sunflower using genotype plus genotype by environment interaction (GGE) and best linear unbiased prediction (BLUP) approaches

Sunflower is important for food, feed and ornamentals, faces rising demand for quality oil. Identifying resilient high-yielding genotypes is essential. Multi-environmental trials and integrated approaches to evaluate genotype by environment interactions (GEI) enhance accuracy and comprehensiveness of breeding programs. This study assess the representativeness and discriminative power of tested environments; classify mega-environments for genotype recommendations and evaluate how GGE and BLUP methods identify stable and superior sunflower genotypes. The experiment used a randomized complete block design with three replications across six locations for two seasons. The pooled analysis of variance for GEI on seed yield showed significant variability (p < 0.05) with mean values from 1171 to 2564 kg ha−1, indicating inconsistent genotypes performance across environments. The study identified E11, E2, and E6 as key discriminating and representative environments and grouped test locations into four mega-environments. Genotypes G6, G1, and G4 are the most desirable based on stability and seed yield. E11 and G6 are identified as ideal environment and genotype, respectively. GGE biplot and BLUP methods consistently identify stable and ideal sunflower genotypes. However, GGE stability indices differ somewhat in assessing genotypes stability possibly due to low number of genotypes, testing environment, and year in the dataset. The study confirmed that simultaneous consideration of GGE and BLUP models for GEI analysis helps to select more stable and adaptable sunflower genotypes across environments. It also clarifies GEI pattern, identifying mega-environments, and aiding genotype selection in sunflower production. However, validating these mega-environments and exploring the genetic basis of adaptability and stability remains essential.

Genotype-Specific Activation of Autophagy during Heat Wave in Wheat.

Recycling of unnecessary or dysfunctional cellular structures through autophagy plays a critical role in cellular homeostasis and environmental resilience. Therefore, the autophagy trait may have been unintentionally selected in wheat breeding programs for higher yields in arid climates. This hypothesis was tested by measuring the response of three common autophagy markers, ATG7, ATG8, and NBR1, to a heat wave under reduced soil moisture content in 16 genetically diverse spring wheat landraces originating from different geographical locations. We observed in the greenhouse trials that ATG8 and NBR1 exhibited genotype-specific responses to a 1 h, 40 °C heat wave, while ATG7 did not show a consistent response. Three genotypes from Uruguay, Mozambique, and Afghanistan showed a pattern consistent with higher autophagic activity: decreased or stable abundance of both ATG8 and NBR1 proteins, coupled with increased transcription of ATG8 and NBR1. In contrast, three genotypes from Pakistan, Ethiopia, and Egypt exhibited elevated ATG8 protein levels alongside reduced or unaltered ATG8 transcript levels, indicating a potential suppression or no change in autophagic activity. Principal component analysis demonstrated a correlation between lower abundance of ATG8 and NBR1 proteins and higher yield in the field trials. We found that (i) the combination of heat and drought activated autophagy only in several genotypes, suggesting that despite being a resilience mechanism, autophagy is a heat-sensitive process; (ii) higher autophagic activity correlates positively with greater yield; (iii) the lack of autophagic activity in some high-yielding genotypes suggests contribution of alternative stress-resilient mechanisms; and (iv) enhanced autophagic activity in response to heat and drought was independently selected by wheat breeding programs in different geographic locations.