G1 Genotype Research Articles

First Case Report of Cystic Echinococcosis Caused by G7 Genotype Echinococcus intermedius Confirmed by Genetic Sequencing - Southern China, December 2023.

Echinococcosis exhibits a global distribution. In China, the primary endemic area is the northwest region. In December 2023, we documented a case of echinococcosis in an individual lacking any travel or residential history in endemic regions. This is the first laboratory-confirmed case of hepatic echinococcosis reported in Guangdong Province, associated with the G7 genotype of Echinococcus granulosus (E. granulosus). The most probable mode of transmission is a local infection resulting from E. granulosus introduced from endemic regions. As the circulation of agricultural products increases, it is essential to enhance the quarantine and management of livestock from epidemic areas to prevent and control the spread of echinococcosis to non-epidemic regions.

Improving productivity of arabica coffee genotype G1 through potassium fertilization

Abstract One of the determinants of coffee productivity is the availability of nutrients in the soil, with potassium being among the essential nutrients required to enhance productivity. Therefore, this study aimed to determine the optimal potassium fertilizer dosage needed to increase the productivity of Arabica coffee plants of the G1 genotype. This study was conducted in the experimental garden of Syiah Kuala University in Bener Meriah Regency, Aceh Province, Indonesia using a Non-Factorial Randomized Block Design (RBD). A total of 132 Arabica coffee trees of genotype G1 were randomly selected based on specific criteria, such as 8 years of age, planted with a spacing of 2.5 x 2.5 m, pruned properly, grown under moderately dense shade of Leucaena trees, and well-maintained. The treatments included a control group without potassium fertilizer and multiple groups receiving potassium fertilizers at 29, 58, 87, 116, and 145 kg K2O per hectare. These potassium sources were derived from potassium chloride (KCl) fertilizer containing 58% K2O and Rice Husk Ash containing 2% K2O, respectively. This resulted in 11 treatment units, each comprising 3 coffee trees replicated 4 times, for a total of 44 treatment units. The results showed that potassium fertilization from KCl and Rice Husk Ash had a significant effect on the increased productivity of Arabica coffee genotype G1. The effect was observed based on the number of productive branches per tree, clusters per branch, fruits per cluster, fruits per tree, the weight of red cherries per tree, parchment coffee per tree, green beans per tree, and the green beans yield at 14% moisture content. The optimal potassium fertilizer dosage was 145 kg K2O per hectare, equivalent to 250 kg KCl or 156.25 g KCl per tree. Additionally, it was observed that potassium sourced from KCl was more effective than potassium from Rice Husk Ash due to the longer time the latter takes to improve the productivity of Arabica coffee.

Improvement in the physical quality of genotype G1 arabica coffee beans as a result of applying rice husk ash and KCl fertilizer

Abstract Arabica Gayo coffee has earned global acclaim for its exceptional flavor profile. Its exports primarily consist of green coffee beans, making the physical quality a crucial criterion. Several factors are considered in assessing the physical quality of coffee beans, including shape (normal, single, and damaged) beans as well as size. Therefore, this study aimed to find out the improvement in the genotype G1 arabica coffee beans physical quality through the potassium from rice husk ash and KCI fertilizer. A total of 132 genotype G1 arabica coffee were selected randomly with specific criteria including eight years of age, a 2.5 m x 2.5 m planting distance, well-pruned, grown under shade from lamtoro trees with slightly dense density, and adequately maintained. Moreover, a non-factorial randomized block design was used. The treatments comprised a control, and the potassium application at doses of 29, 58, 87, 116, and 145 kg K2O ha−1 from KCl fertilizer (containing 58% K2O) and rice husk ash (containing 2% K2O), totaling 11 treatment units. Each unit was replicated four times and consisted of three coffee trees, resulting in a total of 132. The research results showed that the potassium fertilizer application from both KCl and rice husk ash increased the 100 beans weight (water content 14-18%), the normal beans percentage, single beans, small and medium beans size, but can reduce the damaged beans percentage and large beans size. The application of 250 kg ha−1 KCl, equivalent to 156.25 g of KCl per coffee trees was found to be the best potassium fertilizer dose for improving all the quality variables of genotype G1 Arabica coffee beans.

First report of Echinococcus granulosus genotype 1 in a wild boar (Sus scrofa) from China.

Echinococcosis is a worldwide disease endemic to the western region of China. In 2023, echinococcosis was detected in one of 27 wild boars (Sus scrofa) in Yili Prefecture, Xinjiang, northwestern China. Histopathological staining and full sequence mitochondrial (mt) analysis were used to determine the infection genotype. Echinococcus granulosus was detected in the wild boar liver, and the cystic lesion characteristics indicated the E. granulosus genotype (G1). This case is the first confirmation of wild boar serving as a transmitter for the G1 genotype of E. granulosus within China. These findings suggest that surveillance is needed to assess the risk of E. granulosus sensu lato transmission to humans and wild animals.

Performance Evaluation of Different Sorghum Genotypes (Sorghum bicolour (L.) Moench) Using GGE Bi-plot Stability Analysis

Sorghum (Sorghum bicolor (L.) Moench) is an important essential cereal crop in Ethiopia. Conversely, its productivity is low due to numerous biotic and abiotic factors. There are diverse and dynamic environmental conditions which needs detail and continue study on genotypes by environment interaction (GEI) to develop stable genotypes. The objective of this study was to determine the magnitude of GEI for grain yield of forty two sorghum genotypes and to identify stable and high yielding genotypes across locations. The experiments were laid out at three locations for two growing seasons using alpha lattice design with three replications. The plot size 5 m x 0.75 m x 2 rows (7.5 m<sup>2</sup>) and distance between block, replication, and plot was 1m, 1.5m, and 0.75m, respectively. Phonologic, agronomic, diseases and grain yield data were collected but only grain yield was used for stability analysis. The ANOVA revealed highly significant variation (p <0.01) among sorghum genotypes across locations and seasons. Mean grain yield of genotypes ranged from 1.29 to 3.69 with mean grain yield of 2.36, while environment range from 1.18 to 3.63 t/ha. The genotype G1 showed good performance across all test sites which range 5<sup>th</sup> at E1,3<sup>rd</sup> at E3 and E4, 15<sup>th</sup> and 7<sup>th</sup> at E5 and E6 and maximum grain yield was harvested from E3. Yield data were also analyzed using the GGE (that is, G, genotype +GEI, genotypes-by- environment interaction) bi-plot method. The first two principal components (PC1 and PC2) were used to create a 2- dimensional GGE bi-plot and explained 59.67 and 13.48 % of GGE sum of squares, respectively. GGE bi- plot identified G16, G4, and G1 high yielders and stable and G34 and G25 was the lowest yielding and least stable across locations. On the other hand, the environment E6, E4 and E1 were the most suitable to select desirable genotypes.

Genotype-by-environment interaction analysis for grain yield of barley genotypes in the warm climate of Iran

In the present study, multi-environmental trials were performed on 19 newly developed barley genotypes at five test regions across the warm climate in Iran for two consecutive years. The results of additive main effects and multiplicative interaction (AMMI), GGE biplot (GGE) model, and several BLUP-based stability parameters and integrated models (WAASB and WAASBY) were used to reveal GEI patterns and identify superior genotypes with stable grain yield across test environments. Statistical analyses revealed that grain yield was influenced by significant environments (E), genotypes (G), and GEI effects. Among AMMI-, BLUP-, and grain mean-based stability parameters, the harmonic means of genotypic values (HMGV), relative performance of genotypic value (RPGV), and harmonic mean of RPGV parameters indicated a dynamic concept of stability. Moreover, results of GGE biplot analysis identified three mega-environments with different winner genotypes in test environments. Regardless of the different years, the Ahvaz, Darab, and Moghan regions were identified as Type-II environments due to their highest discrimination power and representative ability. The grouping pattern considerably followed the ranking of genotypes in GGE biplot analysis and WAASB model. In conclusion, our results revealed that genotypes G9 and G10 had grain yield higher than the reference genotype and relative stability in specific environments with favorable environmental conditions. Genotype G5 had general adaptability and stability across all test environments. This genotype can be recommended for cultivation in a wide range of environments in the warm climate of Iran.

Screening of Wheat Genotypes for Water Stress Tolerance Using Soil–Water Relationships and Multivariate Statistical Approaches

Drought stress constricts crop production around the world. Employing high-yielding cultivars with drought tolerance might be the ideal professional approach to coping with its detrimental outcomes. As a result, the current study was performed to investigate the sensitivity and tolerance of nine wheat genotypes to drought stress. In a randomized block design experiment, nine wheat genotypes were subjected to four water treatments: 100%, 85%, 70%, and 55% of the available water (AW). Four water regimes in two growing seasons were counted as eight environmental zones. The leaf’s water relations and photosynthetic pigment were estimated, as well as growth and yield parameters. Univariate and multivariate statistical approaches, including the new method of multi-trait genotype–ideotype distance (MGIDI), were used for evaluation. The analysis of variance revealed that genotype, environment, and their interactions had a highly significant effect on all traits. The same trend was shown by the additive main effects and multiplicative interaction (AMMI) analysis of variance for grain yield across the environments. The AMMI biplot study indicated that the G8 genotype is the most stable in terms of water stress. The G7 genotype can withstand droughts up to 55% of the available water, while the G8 and G3 genotypes can withstand droughts up to 70% of the available water. Based on all examined traits, this index was used to identify the stable genotypes G7, G8, and G3, which can therefore be suggested for cultivation during drought conditions. Furthermore, we found a positive correlation between the MGIDI, ANOVA, and tolerance index results, indicating that the same desirable genotypes of G7 and G8 were identified by these procedures as being highly tolerant and stable across a range of soil moisture conditions. Based on MGIDI analysis, we can recommend that the G7 genotype exhibits higher grain yield and yield-related traits with the best drought-tolerant indices.

Cystic echinococcosis in Cyprus: historical retrospective and finding of 2 Echinococcus granulosus sensu lato species.

The island of Cyprus was a historical endemic area for cystic echinococcosis (CE) in the Mediterranean. During the last decades, Cyprus has been an open-air laboratory and a model for testing and implementing control measures aiming to eliminate CE as a public health problem. Despite control and surveillance measures implemented during last 50 years, molecular characterization of Echinococcus granulosus sensu lato specimens has been never provided. In February 2023, the carcass of a stray dog collected in the Nicosia district was examined by the Veterinary Services and found infected with Echinococcus spp. worms. The worms were sent to the European Union Reference Laboratory (EURLP) for species/genotype identification. The sequences analyses of nad2 and nad5 genes allowed us to identify the tapeworms as Echinococcus canadensis, genotype G7b. In November 2023, a parasitic liver cyst was observed during the post-mortem examination of a mouflon from the same area of the dog's finding. The cyst sample was also referred to EURLP for identification and comparison with tapeworms previously collected from the dog. The sequences analysis of cox1 gene allowed to identify the cyst as E. granulosus sensu stricto, genotype G1. The finding of 2 different species of E. granulosus s.l. in a limited area raises epidemiological questions on the origin of the samples: whether distinct transmission cycles are present or a recent introduction event have occurred. From a public health perspective, it will be essential to conduct further molecular epidemiology studies to clarify the recent transmission dynamics of Echinococcus species in Cyprus.

Assessment of agro-physiological traits for identifying drought-tolerant durum wheat (Triticum durum Desf.) genotypes under rainfed conditions

Breeders are focused on developing high-yielding genotypes that can grow in semi-arid regions under water stress. A field experiment was conducted during the 2020 to 2021 cropping season at the experimental field of ITGC, Setif. The aim of this study was to assess the performance of durum wheat genotypes for agronomic traits growing under semi-arid conditions. The 10 genotypes evaluated were grown in a randomized block with three replications. Analysis of variance showed that the genotype effect was significant for most parameters studied. The best grain yield was recorded for genotypes G3 (3.52 t ha-1) G2 (3.48 t ha-1), and G5 (2.89 t ha-1); thus, they maintained the highest water content (81.09, 84.95, and 84.34%, respectively) and lower temperatures under these conditions. Simple linear regression showed that grain yield correlated positively with the number of spikes, and the number of grains per spike. The principal component (PC) analysis classified both genotypes G2 and G3 as high grain yielding genotypes; by contrast, genotypes Jupare C 2001, Bouatleb, and G1 were low-yielding.

Multiplex PCR Technique for Simultaneous Detection and genotyping of E. granulosus, E. multilocularis, and other Taeniidae in some intermediate hosts in Erbil Province

One of the most significant helminthozoonosis in Iraq and around the world is cystic echinococcosis, which occur by the etiologic agent of Echinococcus granulosus and it’s distinguished by considerable intra-specific variability (genotypes G1–G10). DNA was extracted from 48 isolated cysts (25 sheep, 12 goats and 11 human) and used as templates to amplify using Trachsel method to differentiate Taeniide (Echinococcus spp. and/ or Taenia spp.) and mitochondrial cytochrome c oxidase subunit one (COX1) gene for genotyping. The PCR products were sequenced, and sequence analysis was used to further evaluate the data. Out of 48 separated of the host cysts, 36 isolates displayed the G1 genotype (100%), and in 12 samples, a nucleotide substitution at position 58 (T→C) results in polymorphism (99.9%). The G1 is considered that the most contagious and prevalent genotype of E. granulosus in the world. Our investigation revealed that, a single genotype that may be in charge of the disease's infectivity in sheep, goats, and human as well as its persistence in endemic areas. these epidemiological findings could be guided the successful hydatidosis control measures in Erbil Provence

Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters

Rice (Oryza sativa L.) is an important member of the family Poaceae and more than half of world population depend for their dietary nutrition on rice. Rice cultivars with higher yield, resilience to stress and wider adaptability are essential to ensure production stability and food security. The fundamental objective of this study was to identify higher-yielding rice genotypes with stable performance and wider adaptability in a rice growing areas of Pakistan. A triplicate RCBD design experiment with 20 Green Super Rice (GSR) advanced lines was conducted at 12 rice growing ecologies in four Provinces of Pakistan. Grain yield stability performance was assessed by using different univariate and multivariate statistics. Analysis of variance revealed significant differences among genotypes, locations, and G x E interaction for mean squares (p < 0.05) of major yield contributing traits. All the studied traits except for number of tillers per plant revealed higher genotypic variance than environmental variance. Broad sense heritability was estimated in the range of 44.36% to 98.60%. Based on ASV, ASI, bi, Wi2, σ2i and WAAS statistics, the genotypes G1, G4, G5, G8, G11 and G12 revealed lowest values for parametric statistics and considered more stable genotypes based on paddy yield. The additive main effects and multiplicative interaction (AMMI) model revealed significant variation (p < 0.05) for genotypes, non-signification for environment and highly significant for G × E interaction. The variation proportion of PC1 and PC2 from interaction revealed 67.2% variability for paddy yield. Based on ‘mean verses stability analysis of GGE biplot’, ‘Which-won-where’ GGE Biplot, ‘discriminativeness vs. representativeness’ pattern of stability, ‘IPCA and WAASB/GY’ ratio-based stability Heat-map, and ranking of genotypes, the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 were observed ideal genotypes with yield potential more than 8 tons ha−1. Discriminativeness vs. representativeness’ pattern of stability identifies two environments, E5 (D.I Khan, KPK) and E6 (Usta Muhammad, Baluchistan) were best suited for evaluating genotypic yield performance. Based on these findings we have concluded that the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 could be included in the commercial varietal development process and future breeding program.

Molecular phylogenetic analysis of Echinococcus granulosus sensu lato infecting sheep in Italy.

Cystic Echinococcosis (CE), caused by the larval form of Echinococcus granulosus sensu lato, is a neglected zoonosis still threatening public health worldwide. In Italy different epidemiological scenarios were reported depending on the geographical area and associated socio-economic activities. Although in northern Italy the occurrence of E. granulosus is considered sporadic, in the southern regions and, particularly in Sardinia, CE prevalence reaches high levels. We analysed CE cysts collected from infected sheep from various areas of mainland Italy and the Sardinia island, with the main objective to investigate intergenotypic and intragenotypic variations at national level. CE cysts were collected from slaughtered sheep following post mortem inspection at local abattoirs. Total genomic DNA was extracted and amplification and sequencing of the partial mitochondrial genes nad5 and cox1 were performed. A Bayesian phylogenetic tree was estimated on a nad5 dataset (n=260) composed of E. granulosus samples from this study (n=126) and all the nad5 haplotypes available in GenBank (n=134). In addition, haplotype network, diversity and neutrality analysis were performed on nad5 and cox1 sequences of Italian origin obtained in this study. E. granulosus sensu stricto (s.s.) was found to be the only Echinococcus species infecting sheep in Italy, mainly represented by G1 genotype (76%) and, to a lower extent, by G3 genotype (24%). Phylogenetic analyses revealed 40 nad5 and 33 cox 1 haplotypes, and the presence of two founder haplotypes, belonging to G1 and G3 genotype, showing 100% similarity with DNA sequences from different geographic regions. The lack of geographical segregation, high haplotype and low nucleotide diversity coupled with significant negative values of Tajima's D and Fu's Fs observed in this study indicated high genetic variation and demographic expansion of E. granulosus s.s. in Italy.

Stability analysis and nutritional quality of soybean (Glycine max (L).Merrill.) genotypes for feed in southwestern Ethiopia

Soybean is a leguminous crop known for its multiple utilizations both as food and feed for humans and livestock. The objectives of the study were to identify high dry matter yielder and stable genotypes across environments in southwestern Ethiopia. The effect of genotype environment (G x E) interaction on dry matter yield of soybean genotypes were evaluated in two cropping seasons (2019–2020) under rain fed condition. Eight pre tested soybean genotypes with two checks were used as treatment in a randomized complete block design with three replications. Collected data were recorded and analyzed using GGE biplot models using R software. The combined analysis of variance showed that dry matter yield of soybean genotypes was significantly affected by genotype, environment and genotype-environment (G x E) interaction. The genotype, environment, and genotype-environment interaction, respectively, accounted for 11.4%, 49.5%, and 38.8% of the observed variation to the dry mater yield. This indicates that dry matter yield was significantly more affected by environments and G × E interaction than genotypes. The GGE biplot analysis revealed that six environments used in the current study were grouped into four mega-environments. The mega-environments were identified for genotype evaluation. The biplot showed that the vertex genotypes were G4, G10, and G9 and considered as optimum performance in their respective mega-environments and more responsive to environmental changes. The biplot also showed that ENV5 (Kersa 2020) was an ideal and the most discriminating and representative environment. Genotype G4 (TGX1990-114FN) was the ideal genotype and overall winner in dry matter yield and stability in the findings. Therefore, genotype G4 (TGX-1990-114FN) is the better option to be used as forage soybean in Ethiopia. Further demonstration of the feeding values of high yielders and stable genotypes on animal performances should be done.

Screening Iranian endemic coriander genebank germplasm for drought tolerance using a new multivariate statistical method

Drought is one of the serious abiotic factors influencing crop production such as coriander. Development of tolerant genotypes is prevented by the lack of effective selection criterion. Objectives of this study were evaluation of coriander accessions for water deficit stress and introduce a new multivariate method to select drought tolerant genotypes. For investigation of 19 traits, 16 Iranian endemic coriander genotypes were grown in a glasshouse under control and water deficit stress conditions. Shoot dry weight (SDW), fruit weight per plant (FWPP), fruit number per plant (FNPP) and umbel number per plant (UNPP) were decreased (Susceptibility Index>38%) under water deficit stress condition compared with the control condition. While the mean values of root dry weight (RDW) and root to shoot ratio (RTSR) were increased 1.49% and 97.33% under water stress condition, respectively. Because of high inheritance, high expected genetic gain, high genotypic correlation with together, well response to drought stress and high explanation of FWPP variation in regression model, the FWPP, branch number per plant (BNPP), FNPP and SPAD chlorophyll content in grain filing stage (SCCIGFS) traits were selected to screen coriander genotypes for drought tolerance in coriander. The principal component analysis mediated method (PCAMM) indicated as comprehensive criterion to screen drought tolerant genotypes. This method was highly heritabl, able to separate the Fernandez described A, B, C and D groups, no multicollinear and using multiple drought tolerance related traits. The PCAMM results showed that G13, G16, G2 and G12 genotypes belonged to Fernandez described A, B, C and D groups, respectively.

Multi Environment Analysis of Soybean Genotypes to Delineate Stability and Adaptability for Yield and Quality Parameters

The present investigation was carried out at three locations of Gujarat under the jurisdiction of Anand Agricultural University (AAU) during kharif-2022. Three diverse environments were selected for conducting an experiment. The experimental material comprised of 40 genotypes of soybean sown in a randomized block design with three replications at all environments. Based on the AMMI analysis for seed yield per plant, E3 was considered as the most suitable environment for seed yield per plant while, E2 was considered as the poor environment. The genotypes G4, G16 and G40 were considered as the most stable genotypes and had general adaptation for seed yield per plant among all the genotypes since they were least affected by the environment. The genotypes G15, G22, G24, G25, G27, G29, G32 and G39 performed well in the poor environment (E2). Genotypes G10, G20 and G33 had specific adaptability in potential environment (E3) Based on the AMMI stability value G24, G25 and G22 were considered as stable genotypes over environment while, G33, G20 and G35 were considered as unstable genotypes. According to the AMMI 2 biplot G15, G16, G22, G24, G25, G27, G32 and G39 were considered as high yielding with general adaptability. The vertex genotypes for E3 were G10, G12, G20 and G33. G31 was for E2 while, vertex genotype for E1 was G26.

Cystic echinococcosis in cattle and sheep caused by Echinococcus granulosus sensu stricto genotypes G1 and G3 in the USA

BackgroundEndemic domestic dog-ruminant cycles and human cystic echinococcosis caused by Echinococcus granulosus have been sporadically reported in the United States. However, there is a paucity of molecular data describing the genotypes and haplotypes of this important cestode in domestic ruminant hosts.MethodsNinety-four cysts from the lungs and/or livers of slaughtered beef cattle (76 samples), dairy cows (five samples) and sheep (13 samples) were collected from abattoirs in four states of the USA. Samples were genotyped at two mitochondrial loci, cox1 and nad5. Sequences were used to determine species, genotypes and haplotypes using median joining networks and Bayesian phylogenetic analyses. Cyst fertility was assessed in hematoxylin and eosin-stained sections. Additionally, previously reported autochthonous E. granulosus infections in the USA in various hosts were mapped.ResultsBased on cox1 sequences obtained from 94 cysts, 89 (94.7%) were identified as E. granulosus G1/G3, while five (5.3%) were Taenia hydatigena. Taenia hydatigena were only isolated from sheep. Based on nad5 sequences obtained from 89 hydatid cysts, 96.6% and 3.4% belonged to E. granulosus sensu stricto genotypes G1 and G3 respectively. Two haplotypes were found among E. granulosus cox1 sequences, neither of which was geographically unique. Six haplotypes were found among nad5 sequences in genotype G1, of which five were novel, while one haplotype was found in genotype G3. In the concatenated cox1-nad5 dataset, seven haplotypes were identified, of which six were geographically unique. All cysts from cattle were non-fertile. Four cysts from sheep were fertile.ConclusionsAll genotyped samples belonged to E. granulosus s.s. This is the first study to our knowledge to confirm the presence of genotypes G1 and G3 in domestic cattle and sheep intermediate hosts in the USA and provide data for future diagnostic and epidemiological studies. Sequences have been deposited in GenBank (cox1 sequences: OR398494-OR398496, nad5 sequences: OR400695-OR400702).Graphical

Relative Discriminatory Ability of AMMI and GGE Biplot in Analysis of GxE Interaction for Yield and Seed Index in Chickpea (Cicer arietinum L.)

Background: The research focused on investigating the impact of genotype-environment interaction on the yield stability and performance of eight chickpea genotypes across three different locations (Bhatapara, Kawardha and Raipur). Method: The study employed a randomized block design with two replications in each environment in Rabi season during 2021-22. Analysis of variance (ANOVA) revealed significant variations between environments and genotype-environment interaction (G x E) based on AMMI and GGE biplot. Results: To visualize the genotype-environment relationship, a two-dimensional GGE biplot was created using the first two principal components, which accounted for 87.8% and 11.5% of the interaction’s variation. The GGE biplot indicated that genotype g4 (ICCX 161100-B-B-B-B) in environment e2 (Kawardha) and g8 (JG-24) in environment e1 (Bhatapara) exhibited high yield. Genotype g3 (ICCV 201112) in environment e3 (Raipur) also showed high yield, while genotype g5 (JG 2020-10) demonstrated stability across all three environments. Furthermore, the AMMI analysis identified genotype g2 (ICCV 201103) as a superior performer in terms of yield stability across environments. By employing the GGE biplot and AMMI analysis, the study categorized the genotypes into three groups, facilitating simplified visual evaluations. The GGE biplot highlighted that genotype g8 (JG-24) exhibited better seed index in environment e3 (Raipur), while genotype g1 (ICCV 201210) performed well in environment e1 (Bhatapara). Genotype g2 (ICCV 201103) demonstrated a good seed index in all three environments. The AMMI analysis indicated that genotype g3 (ICCV 201112) had a slightly lower seed index but maintained stability across all environments. Overall, the findings of this investigation, as represented by the GGE and AMMI biplots, visually illustrated the relationship between genotypes and environments. The identified genotypes hold potential for improving yield production and further research and breeding efforts can be based on these findings.

Recommendation of Tahiti acid lime cultivars through Bayesian probability models.

Probabilistic models enhance breeding, especially for the Tahiti acid lime, a fruit essential to fresh markets and industry. These models identify superior and persistent individuals using probability theory, providing a measure of uncertainty that can aid the recommendation. The objective of our study was to evaluate the use of a Bayesian probabilistic model for the recommendation of superior and persistent genotypes of Tahiti acid lime evaluated in 12 harvests. Leveraging the Monte Carlo Hamiltonian sampling algorithm, we calculated the probability of superior performance (superior genotypic value), and the probability of superior stability (reduced variance of the genotype-by-harvests interaction) of each genotype. The probability of superior stability was compared to a measure of persistence estimated from genotypic values predicted using a frequentist model. Our results demonstrated the applicability and advantages of the Bayesian probabilistic model, yielding similar parameters to those of the frequentist model, while providing further information about the probabilities associated with genotype performance and stability. Genotypes G15, G4, G18, and G11 emerged as the most superior in performance, whereas G24, G7, G13, and G3 were identified as the most stable. This study highlights the usefulness of Bayesian probabilistic models in the fruit trees cultivars recommendation.

Parametric and Non-Parametric Measures to Identify Stable and Adaptable Cotton (Gossypium Hirsutum L.) Genotypes

ABSTRACT The study, comprised seventeen genotypes, was conducted during 2016 to 2019 growing seasons. The design was Randomized Complete Block Design (RCBD) with three replications to identify adaptable cotton genotypes. Parametric and non-parametric measures, principal component analysis (PCA) and correlation among the ranks of the parameters computed using R software. The environment, genotype and genotype-environment interaction contributed 79.58, 3.2 and 15.46% of the variation, respectively, and were significant (p < 0.001). The highest (1510.7 kg/ha) and lowest (1080.1 kg/ha) seed cotton yield was recorded from G12 and G8 genotypes respectively. Coefficients of determination (R2) and superiority index (Pi) recognized G13, G11, G10 and G11, G12, G7 as the top three stable genotypes correspondingly. G10 was selected three times as superior by stability variance (σ2), wricke’s ecovalence (Wi) and deviation from regression (S2di). Seed cotton yield positively correlated with GAI, Kang’s rank-sum (KRS), Huhn and Nassar S(1), S(6) S(3) while negatively correlated with Thennarasu stability measures NP(2), NP(3) and NP(4 . The first, second and third clusters of the PCA biplot comprised, 4, 4 and 10 parameters respectively. G12, with highest seed cotton yield and good stability, was the best genotype and recommended for variety verification.

Deciphering Genetic Diversity in Advanced Wheat Lines (Triticum aestivum L.) for Yield and Other Yield Contributing Traits Across the Locations

Twenty advanced wheat genotypes were evaluated for yield and yield-contributing traits in six field trials over two cropping seasons (Rabi 2020-21 and 2021-22) using a completely randomized block design (RBD) at two locations: the N.E. Borlaug Crop Research Centre (NEBCRC), G.B.P.U.A&amp;T, Pantnagar, U.S. Nagar district, and the Agriculture Research Center Majhera, Nainital, Uttarakhand. The study aimed to assess genetic diversity among the genotypes via principal component analysis (PCA) and cluster analysis, offering insights into genetic variations. Three clusters were formed, with the maximum number of genotypes occurring in the second cluster. A lower p-value indicates that the clusters are statistically significant, suggesting that the observed diversity is not random. High estimates of cophenetic distance (.79) specify a high genetic distance between clusters, indicating that diverse genetic material is under study. The maximum genetic distance observed was 144.9 between genotypes G5 and G11. These findings suggest that these two genotypes are the most genetically diverse among all the studied genotypes and can be used as parents to develop high genetic variation in the studied traits. The PCA results yielded 18 principal components, with the first seven components accounting for approximately 83% of the total variance, indicating significant genetic diversity. The scree plot affirmed the robustness of the study’s results by suggesting that the first eight principal components accounted for a substantial portion of the variance.The findings of current study could be exploited in planning and execution of future breeding programme in wheat.