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Abstract Background One of the wild fruit species with a natural distribution in Türkiye, and historically used for medicinal purposes due to its rich composition, is Berberis crataegina DC. Various parts of the plant, including its roots, bark, leaves, flowers, and fruits, have been utilized in traditional medicine, while its fruits are also consumed in various forms as food. This study aimed to characterize the morphological, biochemical, and molecular traits of B. crataegina genotypes naturally growing in the Kayseri region, located in central Türkiye. Results The fruit weight of the genotypes ranged from 0.047 to 0.137 g, fruit width from 3.06 to 4.64 mm, and fruit length from 5.80 to 9.05 mm. Similarly, the leaf traits of the genotypes exhibited wide variation. The total phenolic content ranged from 190.53 to 297.55 mg GAE/100 g, total flavonoid content from 82.03 to 203.89 mg QE/100 g, total anthocyanin content from 4.54 to 11.76 mg cyn-3 gluc/100 g, and total antioxidant capacity between 57.76 and 87.93%. A principal component analysis (PCA) of 11 traits identified four principal components with eigenvalues greater than 1. The first four components accounted for 71.89% of the total variation, with PCA1 explaining 23.48%, PCA2 18.68%, PCA3 16.39%, and PCA4 13.34%. ISSR molecular analysis using nine markers revealed a band count ranging from 4 to 13, polymorphic band count between 3 and 10, and polymorphism rates from 61.54 to 100%, with band lengths ranging from 200 to 1000 base pairs. According to the UPGMA dendrogram based on molecular analyses, the genetic similarity between the genotypes ranged from 0.64 to 1.00, with B2 and B13 being the most similar genotypes. Conclusions In conclusion, the Kayseri region is rich in B. crataegina genotypes with wide genetic variation. The genotypes identified in this region may serve as valuable genetic resources for future studies.

Local populations are key genetic resources that have adapted to the region throughout time and are still used in breeding operations. In this study, important quality features of local varieties were determined which was conducted with one hundred forty two local and two registered bread wheat genotypes in the 2019-2020 and 2020-2021 growing years. The trials were set up in a 12 x 12 alpha lattice design with three replications. Significant statistical differences were detected between genotypes and years (except for starch) for all examined traits. According to the two year-average; the thousand grain weight, hectoliter weight, protein ratio, Zeleny sedimentation value, wet gluten ratio, ash ratio, fat ratio, starch ratio, acid detergent fiber and neutral detergent fiber of the genotypes were changed between 21.32 - 45.09 g, 75.12 - 81.09 kg, 11.77 - 16.07%, 24.31 - 48.50 ml, 23.96 - 33.61, 1.23 - 1.97%, 1.39 - 2.29%, 61.45 - 69.81%, 3.29 - 5.51% and 13.75-17.07%, respectively. According to the Biplot graph; positive correlations were found between hectoliter weight, thousand grain weight and starch ratio; between ash ratio and neutral detergent insoluble fiber ratio; between Zeleny sedimentation value, wet gluten ratio and protein ratio; between acid detergent fiber value and oil ratio. Furthermore, according to this graph, genotypes G99, G105, G126, and G137 had the highest protein, wet gluten, and Zeleny sedimentation values; genotypes G53, G67, and G72 had the highest starch value; and genotypes G46 and G53 had the highest thousand grain weight values. As a result, the majority of the populations in the trial outperformed the registered varieties in terms of quality parameters. [ABSTRACT FROM AUTHOR]

Introduction: Feeding local forages to ruminants is a promising strategy for enhancing metabolic processes, promoting sustainable farming, and improving product quality. However, studies comparing the effects of different forages on rumen histology and meat attributes of heifers are limited and variable. Material and methods: This study evaluated the benefits of incorporating local forages into heifer diets by comparing barley straw (BS) and oat hay (OH) on heifer attributes focusing on meat quality (MQ) and rumen status (RS). Sixteen crossbred (Charolais x Limousin) female heifers (7 months of age, 263 ± 10.50 kg) were randomly assigned to two dietary treatments (BS or OH) over 120 days. Results and discussion: Heifers fed OH showed enhanced RS (p < 0.05), characterized by improved intestinal epithelial integrity and a lower percentage of hyperpigmented cells, suggesting a potential reduction in inflammatory processes compared to BS, which may indicate a lower risk of metabolic diseases. Despite this, no significant differences (p > 0.05) were found in animal performance, chemical composition, and technological properties of the meat between the dietary groups, while lower levels (p < 0.05) of certain saturated fatty acids (C12:0, C15:0, and C22:0) were found in the meat from heifers fed OH. Principal component analysis (PCA) reduced the variables and demonstrated that all variables assessed can be condensed into four new variables explaining 75.06% of the variability. Moreover, biplot analysis reveals that the OH diet could be discriminated from BS. Our findings suggest that OH is a valuable fiber source, positively influencing certain heifer attributes, and supporting sustainable animal agriculture practices. [ABSTRACT FROM AUTHOR]

To optimize growth and management, precision agriculture relies on a deep understanding of agricultural dynamics, particularly crop water status analysis. Leveraging unmanned aerial vehicles, we can efficiently acquire high-resolution spatiotemporal samples by utilizing remote sensors. However, non-linear relationships among data features, localized within specific subgroups, frequently emerge in agricultural data. Interpreting these complex patterns requires sophisticated analysis due to the presence of noise, high variability, and non-stationarity behavior in the collected samples. Here, we introduce Local Biplot, a methodological framework tailored for discerning meaningful data patterns in non-stationary contexts for precision agriculture. Local Biplot relies on the well-known uniform manifold approximation and projection method, such as UMAP, and local affine transformations to codify non-stationary and non-linear data patterns while maintaining interpretability. This lets us find important clusters for transformation and projection within a single global axis pair. Hence, our framework encompasses variable and observational contributions within individual clusters. At the same time, we provide a relevance analysis strategy to help explain why those clusters exist, facilitating the understanding of data dynamics while favoring interpretability. We demonstrated our method's capabilities through experiments on both synthetic and real-world datasets, covering scenarios involving grass and rice crops. Moreover, we use random forest and linear regression models to predict water status variables from our Local Biplot-based feature ranking and clusters. Our findings revealed enhanced clustering and prediction capability while emphasizing the importance of input features in precision agriculture. As a result, Local Biplot is a useful tool to visualize, analyze, and compare the intricate underlying patterns and internal structures of complex agricultural datasets. [ABSTRACT FROM AUTHOR]

Yield and stability are desirable characteristics that crops need to have high agronomic value; sugarcane stands out globally due to its diverse range of products and by-products. However, genotype-environment (G × E) interactions can affect the overall performance of a crop. The objective of this study is to identify genotypes with the highest yield and stability, as well as to understand their independent and interactive effects. A collection of 10 sugarcane varieties was evaluated, including Colombian, Dominican, Ecuadorian lines, and a group of clones planted across five different locations from 2018 to 2020. A two-way ANOVA along with the GGE biplot technique were used to analyze yield and stability. The ANOVA model shows highly significant effects in all cases (p < 0.001) except for the genotype by year and sector interaction (G × Y × S); however, the decomposition by sectors reveals a significant triple interaction in sector 04 (p < 0.05). The GGE biplot model accounted for up to 74.77% of the total variance explained in its PC1 and PC2 components. It also highlighted the group of clones as having the highest yield and environmental instability, and the Ecuadorian varieties EC-07 and EC-08 as having the best yield-stability relationship. We conclude that the combined results of the ANOVA and GGE biplot models provide a more synergistic and effective evaluation of sugarcane varieties, offering theoretical and practical bases for decision-making in the selection of specific varieties. [ABSTRACT FROM AUTHOR]

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El palangre de superficie es un arte pesca dirigido a la captura de peces pelágicos, el cual puede enganchar especies vulnerables como tiburones, tortugas, aves y mamíferos marinos. El objetivo del presente trabajo fue analizar la incidencia de estos grupos en la pesca de barcos nodrizas ecuatorianos. La base de datos fue proporcionada por el Instituto Público de Investigación de Acuicultura y Pesca, correspondiendo a registros de observadores a bordo, para el período 2019-2023. La principal carnada utilizada fue Dosidicus gigas. Se encontró el uso de anzuelos tipo “C” y “J”, siendo el segundo el más utilizado. Un total de 14 especies de tiburones, una de raya (Pteroplatytrygon violacea) y una de mantarraya (Mobula birostris) incidieron en la pesca con palangre. Prionace glauca, Alopias pelagicus, Carcharhinus falciformis, A. superciliosus e Isurus oxyrinchus tuvieron la incidencia anual más alta. La incidencia de tiburones mostró una baja relación con la cantidad de lances. Las aves marinas reportadas fueron 25 especies, alimentándose o deambulando. Oceanites gracilis y Procellaria parkinsoni tuvieron la mayor incidencia. Los delfines fueron los mamíferos marinos más representativos, el Género Delphinus fue el más abundante, sin evidencia de mortalidad. Las tortugas Chelonia mydas y Lepidochelys olivacea presentaron registros recurrentes, mientras que Caretta caretta y Dermochelys coriacea fueron esporádicas. Los tiburones fueron el único grupo que presentó mortalidad, mientras que, las tortugas presentaron lesiones corporales sin mortalidad. Bajo este escenario, es necesario desarrollar y aplicar medidas de manejo que promuevan la protección de las especies vulnerables.

Rhizomania destroys sugar beet globally, but breeding disease-resistant genotypes is crucial in fighting it. In this study, 13 modern genotypes were examined based on the list provided by the Iraniai Seed Registration and Certification Institute. Genotypes grown in a randomized complete block design, with four replications in Iran's Karaj, Mashhad, Miandoab, Shiraz, and Hamedan stations. Results revealed that F-21375 and F-21092 genotypes achieved the highest white sugar yield in all five investigated stations. The results of additive mean effect multiplicative interaction (AMMI) analysis based on white sugar yield showed that the additive effects of genotype and environment and the multiplicative effect of G×E accounted for 13.11, 51.29, and 10.60% of the total data variance, respectively. The AMMI stability parameters identified the F-21376 genotype as a stable variety that produces a high white sugar yield in five locations. Also, the first two components of the interaction effect (G×E) explained 80.70% of the variance. The biplot analysis showed that F-21376 was the genotype that produced the greatest white sugar yield and stability in infected conditions. Based on the results of the multi-trait stability index (MTSI), F-21375, and F-21372 genotypes were selected as ideal genotypes. Finally, it can be concluded that two genotypes, F-21375 and F-21376, can be introduced as high-yielding and disease-resistant genotypes in the beet cultivation areas due to their white sugar yield and stability in experimental environments.

The graphical representation of the correlation matrix by means of different multivariate statistical methods is reviewed, a comparison of the different procedures is presented with the use of an example data set, and an improved representation with better fit is proposed. Principal component analysis is widely used for making pictures of correlation structure, though as shown a weighted alternating least squares approach that avoids the fitting of the diagonal of the correlation matrix outperforms both principal component analysis and principal factor analysis in approximating a correlation matrix. Weighted alternating least squares is a very strong competitor for principal component analysis, in particular if the correlation matrix is the focus of the study, because it improves the representation of the correlation matrix, often at the expense of only a minor percentage of explained variance for the original data matrix, if the latter is mapped onto the correlation biplot by regression. In this article, we propose to combine weighted alternating least squares with an additive adjustment of the correlation matrix, and this is seen to lead to further improved approximation of the correlation matrix.

The objective of this experiment was to determine drought tolerance exhibited by lentil lines developed by the International Center for Agricultural Research in the Dry Areas (ICARDA) in an artificial environment, and to investigate the relationships between traits with various methods. This experiment examined 15 traits of 21 lentil (Lens culinaris Medik.) accessions grown under artificial drought stress created with polyethylene glycol (PEG)-6000 (0%, 10%, 15% and 20%) concentrations during germination and early seedling stages. Germination characteristics, seedling developmental properties and root system architecture traits were investigated to observed the impacts of drought stress. The originality lies in enabling the identification of drought-tolerant and sensitive genotypes through a brief and practical research method, while shedding light on the key traits by principal component analysis. The first two PCs explained 22.9% and 31.7% (total 54.6%) under optimal conditions while they described 14% and 58.3% (total 72.3%) under PEG-induced drought conditions, respectively. Variation in PC1 was mostly contributed by positive coefficients of germination index, uniformity of germination and germination energy, and negative coefficients of mean germination time. Variation in PC2 was mostly contributed by positive coefficients of seedling vigor index, root fresh weight and root dry weight. 'Tigris', G3664 and G3840 exhibited higher performance in terms of germination characteristics, while G3710, G3829 and G3840 produced higher DM accumulation, total biomass and lateral roots. Overall, PC-biplot denoted that selection based on germination index and seedling vigor index at germination and seedling stages would improve drought tolerance. In conclusion, genotypes G3840 and G3664 were identified as droughttolerant, whereas genotypes G35, G3659, G3759, G3837, and G3844 were classified as drought-sensitive. In addition, G3664, G3840 and G3710 exhibited the highest stress tolerance index (STI) under artificial drought conditions. [ABSTRACT FROM AUTHOR]

The 2014 shutdown localization of prostitution in Surabaya City, East Java Province, Indonesia, has given rise to an illegal prostitution industry, resulting in the spread of uncontrolled sexually transmitted infections (STIs). Mapping needs to be done to track the spread of the disease. This study used secondary data on STIs in 2020 from the Surabaya City Health Office. By using biplot analysis, this study sought to offer a detailed understanding of the distribution and dynamics of STI cases in different parts of Surabaya. The early-stage syphilis was found in Tegalsari and Krembangan Subdistricts; then, gonorrheal urethritis was found in Tandes, Karang Pilang, and Pabean Cantian Subdistricts. Meanwhile, gonorrhea was typically found in Tandes, Gunung Anyar, Sawahan, and Karang Pilang Subdistricts. On the other hand, Tegalsari, Krembangan, and Pabean Cantian Subdistricts also had cases of advanced syphilis. This study enables relevant parties, specifically the Surabaya City Health Office, to monitor the method's rapid spread and respond to each case according to the predominant type of STI. [ABSTRACT FROM AUTHOR]

Introduction and Objective: Yield under stress conditions has never been an accurate criterion for selecting drought-tolerant genotypes, and the goal of preparing drought-tolerant cultivars has always been to create cultivars that relatively tolerate stress better compared to other genotypes and in the same agricultural conditions, they show less yield loss. In most studies, only the seed yield is considered for the field selection of crops, while some researchers believe that in order to be more efficient in breeding compatible and superior cultivars in arid and semi-arid regions, the indicators that are effective in identifying the stability of cultivars under drought stress conditions should be identified and used them as selection index in addition to seed yield, therefore, the relative uield status of genotypes in drought stress conditions and water conditions is a starting point for identifying and selecting genotypes for improvement in dry environments. In semi-arid regions where the distribution of rainfall is not proportional, the yield potential in stress conditions is not considered the best criterion for drought tolerance, but in addition to yield stability, the comparison of yield in stress and optimal conditions is a more suitable criterion for the reaction of genotypes to moisture stress. Due to the fact that most of the studies related to indicators in crop species and especially wheat are done only in one place and one year and finally in a specific environment and the results are generalized to all environments and the variable effects of year and place are not taken into account in the calculation of indicators. In this regard, this research was carried out to evaluate the genotypes of autumn wheat in terms of drought tolerance, to select the best drought tolerance indices and to identify drought stress tolerant cultivars in different regions of the country's cold climate. Material and Methods: In this research project, 20 genotypes under normal irrigation and water deficit conditions in the form of randomized complete block design (RCBD) with three replications in the research stations of Karaj, Mashhad, Miandoab and Arak, in the crop years of 2017-2018 and 2018-2019 were investigated. In order to investigate the drought tolerance of the genotypes, different tolerance and stress sensitivity indices were determined for the genotypes under investigation and the genotypes were grouped based on the sensitivity and tolerance to drought by each of these indices. Principal component analyzing was also used in order to summarize the data and draw a diagram based on the first two components and identify the desired indicators. Finally, biplot analysis was used to group genotypes and indices based on drought tolerance criteria. Results: Stress decreased the Yield of genotypes, but the amount of reduction was different in different genotypes. The average grain yield for all genotypes under normal irrigation conditions and drought stress at the end of the season was 7.002 and 5.215 tons per hectare, respectively, which showed that the stress conditions caused a decrease of about 25% in grain yield compared to normal irrigation conditions. The environmental and agricultural conditions of different regions and the studied years caused differences in the estimated indices so that the ranking of genotypes changed based on different indices in different years and regions therefore, it is better to carry out studies on stress tolerance indices in several places and several years so that the process of functional changes of different cultivars and genotypes is correctly determined and as a result, there is more confidence in the calculated tolerance and sensitivity indices. Genotypes G4, G2, G16 and G5 showed higher yield in both conditions. STI, MP, GMP, MSTI1, MSTI2, YI, HM, and RR had a positive and significant correlation with grain yield under normal and stress conditions, and therefore, they can be used for more favorable selection of drought tolerant genotypes. Principal component analysis showed that indicators can be grouped using the first two components. The first principal component explained 53.16% of the changes in the total data and had a positive and significant correlation with yield in normal and stress conditions as well as MP, STI, GMP, YI, MSTI1, MSTI2, HM and RDY indicators. Due to the high correlation of this component with yield under normal and stress conditions, this component was named as the yield potential component under normal and stress conditions. The second estimated component justified 42.33% of the total data changes and showed a positive and significant correlation with yield in normal conditions and SSI, TOL, ATI, SSPI and RR indices. It seems that this component is able to identify genotypes that have high yield under stress conditions. Biplot analysis showed that HM, MP, STI, MSTI1, MSTI2, GMP, RDY, YI, and SNPI indices had a positive and high correlation with performance under stress and normal conditions. So that the sharp angles between these indices showed their positive and very high correlation with each other. RDI and YSI indices had a negative correlation with performance in normal conditions and RR, SSI, TOL and SSPI indices had a negative correlation with performance in stressful conditions. Conclusion: In order to achieve varieties resistant to drought stress by using indices, in order to prevent the mutual effects of the environment in the genotype, the experiments should be carried out in many years and places so that the effects of the environment in the calculated indices can be reduced and more reasonable results can be obtained. Finally, G4, G2, G16, G5 and G17 genotypes can be selected as genotypes with high performance under normal and stress conditions. [ABSTRACT FROM AUTHOR]

In behavioral research, it is very common to have manage multiple datasets containing information about the same set of individuals, in such a way that one dataset attempts to explain the others. To address this need, in this paper the Tucker3-PCovR model is proposed. This model is a particular case of PCovR models which focuses on the analysis of a three-way data array and a two-way data matrix where the latter plays the explanatory role. The Tucker3-PCovR model reduces the predictors to a few components and predicts the criterion by using these components and, at the same time, the three-way data is fitted by the Tucker3 model. Both the reduction of the predictors and the prediction of the criterion are done simultaneously. An alternating least squares algorithm is proposed to estimate the Tucker3-PCovR model. A biplot representation is presented to facilitate the interpretation of the results. Some applications are made to empirical datasets from the field of psychology. [ABSTRACT FROM AUTHOR]

Rhizomania destroys sugar beet globally, but breeding disease-resistant genotypes is crucial in fighting it. In this study, 13 modern genotypes were examined based on the list provided by the Iraniai Seed Registration and Certification Institute. Genotypes grown in a randomized complete block design, with four replications in Iran's Karaj, Mashhad, Miandoab, Shiraz, and Hamedan stations. Results revealed that F-21375 and F-21092 genotypes achieved the highest white sugar yield in all five investigated stations. The results of additive mean effect multiplicative interaction (AMMI) analysis based on white sugar yield showed that the additive effects of genotype and environment and the multiplicative effect of G×E accounted for 13.11, 51.29, and 10.60% of the total data variance, respectively. The AMMI stability parameters identified the F-21376 genotype as a stable variety that produces a high white sugar yield in five locations. Also, the first two components of the interaction effect (G×E) explained 80.70% of the variance. The biplot analysis showed that F-21376 was the genotype that produced the greatest white sugar yield and stability in infected conditions. Based on the results of the multi-trait stability index (MTSI), F-21375, and F-21372 genotypes were selected as ideal genotypes. Finally, it can be concluded that two genotypes, F-21375 and F-21376, can be introduced as high-yielding and disease-resistant genotypes in the beet cultivation areas due to their white sugar yield and stability in experimental environments. [ABSTRACT FROM AUTHOR]

Banana (Musa species) is the fourth most important export crop worldwide after cereals, oil crops and sugar. In spite of this socio-economic significance, the crop suffers massive postharvest losses caused by mechanical fruit damage, limited infrastructure for fruit ripening, postharvest diseases and physiological disorders. Although use of optimum postharvest environments such as packaging and storage temperatures can reduce fruit loss and improve ripening quality; information regarding the interaction between varieties and postharvest environments and stability of fruit ripening traits across postharvest environments is limited. The objectives of this study were to determine the magnitude of interaction of varieties with postharvest environments on fruit ripening traits and to identify stable banana variety for ripening across postharvest environments. Seven commonly grown banana varieties (Dwarf Cavendish, William I, Grand Naine, Poyu, Giant Cavendish, Butazu and Local variety) were laid out in a completely randomized design with five replications in ten varied postharvest environments. The result indicated that pulp and peel ratio had negative high principal component one (PCA1) score whereas the PCA1 score for postharvest period, peel weight and fruit weight were positive and high. Cluster analysis grouped Dwarf Cavendish and Grand Naine; Poyu and Butazu varieties together for postharvest traits whereas the local variety was clustered separately. This study has demonstrated that hybridization of local with the introduced varieties can be done to improve postharvest traits. AMMI depicted significant variation for genotype, postharvest environments and their interactions for all traits. The magnitude of environmental effect was higher than the genotype and interaction effects. AMMI and GGE biplot analyses identified Gran Naine, Poyu and William I as consistent for ripening traits across postharvest environments.

El trigo es el cereal más cultivado dentro del sistema agrícola con una producción estimada en 2022 de 794 millones de toneladas y en nuestro país se constituye la principal fuente de alimento con un rendimiento que oscila en 1.1 t ha-1 en los últimos diez años (2013-2022). El presente estudio tiene como objetivo identificar líneas élites con características agronómicas sobresalientes para el componente de rendimiento bajo condiciones agro meteorológicas del Altiplano Central de Bolivia, identificar correlaciones entre variables agronómicas, fenológicas, fisiológicas de rendimiento y calidad en las trece líneas élites de trigo harinero. Para el presente trabajo se evaluaron trece líneas élites y dos testigos (Tepoca-T89 y INIAF-Totora-2014) donde se instaló bajo el diseño de bloques completamente al azar. Los genotipos fueron sembradas con una densidad de siembra de 120 kg ha-1, con una fertilización de 87.452 kg ha-1 de 46-00-00 y 45.999 kg ha-1 de 18-46-00, para el control de malezas de hoja ancha se aplicó herbicida metsulfuron-metil en tres dosis de 8-9-10 g ha-1 y riegos de acuerdo a la necesidad del cultivo. Las evaluaciones de las variables registradas fueron: fenológicas, agronómicas, fisiológicas, rendimiento y calidad acorde a las fases fenológicas del cultivo. Para analizar e interpretar los datos se realizó análisis estadístico descriptivo, varianzas, prueba de medias, multivariado, componentes principales, ranking de rendimiento. En conclusión, para estas características destacan los genotipos L-13, Tepoca-T89, INIAF-Totora-2014 con rendimientos de: 2 374, 2 066, 1 969 kg ha-1 como los más promisorios. Por lo tanto, es posible cultivar el trigo tomando medidas de prevención y adaptación para garantizar la viabilidad de producción en esta región del Altiplano Central de Bolivia.

IntroductionFeeding local forages to ruminants is a promising strategy for enhancing metabolic processes, promoting sustainable farming, and improving product quality. However, studies comparing the effects of different forages on rumen histology and meat attributes of heifers are limited and variable.Material and methodsThis study evaluated the benefits of incorporating local forages into heifer diets by comparing barley straw (BS) and oat hay (OH) on heifer attributes focusing on meat quality (MQ) and rumen status (RS). Sixteen crossbred (Charolais x Limousin) female heifers (7 months of age, 263 ± 10.50 kg) were randomly assigned to two dietary treatments (BS or OH) over 120 days.Results and discussionHeifers fed OH showed enhanced RS (p 0.05) were found in animal performance, chemical composition, and technological properties of the meat between the dietary groups, while lower levels (p

Little millet is an important small millet grown mostly in India. The availability of genetic variability is a critical requirement for crop improvement. Principal Component Analysis (PCA) and correlation study was undertaken in a set of 28 little millet genotypes to estimate genetic diversity, association pattern among seven quantitative traits and to select suitable genotypes for crop improvement. In cluster analysis, the genotypes were classified into three distinct clusters, each with one or two subgroups. Cluster I had the major genotypes with comparable ancestry, followed by Cluster II. The total variance was split into seven major principal components, with the top two PCs with eigenvalues greater than one accounting for 82.57% of the overall variation. PC1, which explained a larger part of the variance (58.05%), was strongly influenced by days to 50% flowering, days to maturity, number of productive tillers per plant, 1000-grain weight, and grain yield. PC2 was primarily influenced by plant height and fodder yield. PCA and association analysis revealed a significant positive association between grain yield and the number of productive tillers per plant, 1000-grain weight, plant height. These traits would be useful for direct selection for little millet crop improvement. In both cluster analysis and PCA, the genotypes DHLM 14-5, IIMR LM-8004, NDL LM1, TNPSu 242, VS 33, WV 168, DPLN 1 and VS 38 displayed diversity, implying that these lines may be used in crossing programme to generate further genetic variability to select suitable transgressive segregants.

The aim of this study was to explore the characteristics essential for a maintainer line to effectively complement the A lines in hybrid rice production. The experiment was conducted at the Regional Agricultural Research Station, Jagtial and Telangana, India during kharif, 2016 (June-October). A total of 40 genotypes were raised in Randomized Block Design (RBD) with two replications. PCA identified five principal components (PCs) with Eigen values over 1, collectively accounting for approximately 75.50% of the total variance. PC1 predominantly representing yield and related features (number of tillers per plant, panicle length, length-to-breadth ratio, grain yield per plant), while the other PCs corresponded to unique aspects like grain numbers, morphological and quantitative traits. The study also utilized biplot analysis to elucidate the relationships among these traits, revealing significant correlations and interactions crucial for rice breeding. It indicated a negative correlation between 1000 grain weight, kernel breadth, and the number of grains per panicle, while showing positive correlations among traits influencing grain yield. This method also proved assistance in identifying superior genotypes for specific traits, as exemplified by genotypes JMS18B and JMS20B excelling in grain numbers per panicle and genotype B18 standing out in grain yield and other yield-related traits.

Introduction The water deficit is one of the most important problems in rice cultivation, particularly when the decrease in rainfall and dry season affects its vegetative growth and grain yield. Drought stress is known as one of the most effective factors of yield reduction in crops. Identifying and introducing tolerant genotypes is a good way to cope incompatible environmental conditions. For easier evaluation of genotypes under drought conditions and identification of drought tolerant genotypes, various indices have been suggested as criteria for selection of genotypes based on their yield under stress and non-stress conditions. The present study was conducted to evaluate some rice genotypes under drought stress conditions as well as to introduce drought tolerant genotypes using important tolerance and sensitivity stress indices. Materials and methods This experiment was conducted in split plots based on randomized complete block design with three replications in Azadshahr, Golestan province, Iran. The main factor included two irrigation levels (drought stress and flooding as control) and the sub-factor included eight rice varieties. The experimental plots were three m2 with a distance of one m from each other. After randomly assigning the treatments to the experimental units, transplanting was done as four plants per pile. Each genotype was cultivated in six two-meter rows with a distance of 25 × 25 cm. Irrigation of the experimental field under both stress and non-stress conditions until the tillering stage of the genotypes was conducted as flooding. Then, under stressful conditions, irrigation was carried out from 40 days after transplanting (maximum tillering stage) until the end of the cropping season at an interval of 25 days, which according to the climatic conditions of the studied region, irrigation was done only once in stressful conditions. From the six rows planted in each plot, one row from around each plot was removed as border and the second to fourth rows were selected for sampling. After measuring traits and calculating different indices, the data were analyzed by SAS software. Two-dimensional biplot diagram was also drawn by STATGRAPHIC software. Research findings The results of analysis of variance showed a significant difference between the genotypes for all studied traits under both drought stress and flooded (control) conditions. Comparison of means showed that the highest average grain yield under both control and stress conditions belonged to Fajr, IRAT216, Sang-Jo, and Sang-Tarom Gerdeh genotypes, and the lowest grain yield belonged to the Sepidrood variety. The results of the correlation coefficients showed that grain yield in control conditions had a positive and significant correlation with mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HARM), and drought tolerance (TOL) indices, respectively, and the highest correlation was observed between grain yield and MP index (r = 0.918). Also, under drought stress conditions, grain yield showed a high correlation with the harmonic mean (HARM), geometric mean productivity (GMP) and mean productivity (MP) indices, the highest of which was related to harmonic mean index (r = 0.933). The results of principal component analysis showed that 94.31% of the total variation between data was justified by the first and second principal components. Cluster analysis based on drought stress indices separated rice genotypes into three groups, and the genotypes in the first cluster had the highest drought tolerance. Conclusion The results of biplot analysis and correlation between stress indices indicated that GMP, MP, and HM indices were the best indices for selecting high-yielding genotypes under both stress and nonstress conditions in this experiment. Based on these indices and biplot diagram, Fajr, Sang-Tarom Gerdeh, Sang-Jo, and IRAT216 genotypes were identified as high-yielding and drought-tolerant genotypes, and Sepidrood and Gharib Siah Reyhani varieties as low yielding and drought sensitive genotypes. [ABSTRACT FROM AUTHOR]

The role of genetic variation is utmost importance in the selection of a desirable genotype for breeding programs. In the northern region of Bangladesh, the performance of five short duration boro rice varieties (BRRI dhan28, BRRI dhan74, BRRI dhan81, BRRI dhan88, and Bangabandhu dhan100) on yield and yield-contributing traits were evaluated in four locations. Yield attributes tiller hill-1 (TN), panicle hill-1 (PN), filled grain panicle-1 (FG), panicle length (PL), 1000-grain weight (TGW), and harvest index (HI), showed a positive correlation with grain yield (GY). Conversely, spikelet sterility (SSP) and unfilled grains panicle-1 (UFG) showed negative associations with grain yield. Principal component analysis (PCA) revealed that the first three components accounted for 89.60% of variability. The highest positive eigenvalue was observed in DF, DM, BY, HI, PN, SY, TN, PL and GY in PC1, indicating their significant influence on the overall genotype variations. PC2 was primarily driven by plant height (PH) and FG, while PC3 driven by TGW and UFG. The results suggest that grain yield is highly influenced by FG, PH, DM, DF, PN, TN, PL, TGW, SY, BY, and HI. These components highlighted the importance in distinguishing rice genotypes with higher grain yield potential. By considering these traits, BRRI dhan74 have outperformed other varieties, followed by BRRI dhan88 and Bangabandhu dhan100. BRRI dhan74 is most suitable for all four location followed by BRRI dhan88. The traits such as PN, PL, FG, TGW, PH, & HI significantly influence rice yield and should be prioritized in breeding programs aimed at developing high-yielding rice varieties.

IntroductionSalinity stress is one of the main abiotic stress factors and environmental problems affecting crop yields worldwide, especially in arid and semi-arid regions. Land salinization is increasing, with 10 million ha of agricultural land destroyed annually. An increase in the concentration of salts in soil solution or irrigation water adversely affects plant growth and productivity, which can substantially reduce yield production. Maize (Zea mays L.) is the third most important cereal grain after rice and wheat, due to its high yield and nutritive value and also known as the queen of cereal crops and is moderately sensitive to salinity stress. Accurate screening of maize tolerant genotypes using selection indices for salinity stress tolerance is an efficient approach to improve salinity tolerant crop plant genotypes, as well as reduce the effect of salinity on this crop.Materials and methodsThis study was conducted at the Urmia University Research Farm in 2017 to evaluate the influence of salinity stress (8 dSm-1) on the grain yield of 86 maize lines, as well as identify salt-tolerant maize lines based on selection indices for salinity stress tolerance. The pot experiments in normal and salinity stress conditions were set up in a randomized complete block design (RCBD) with three replicates. Ten selection indices for salinity stress tolerance including Stress Susceptibility Index (SSI), Tolerance Index (TOL), Stress Tolerance Index (STI), Mean Productivity (MP), Geometric Mean Productivity (GMP), Harmonic Mean (HM), Abiotic Tolerance Index (ATI), Drought resistance Index (DI), Modified Stress Tolerance Index in normal condition (MpSTI), and Modified Stress Tolerance Index in stress condition (MsSTI) were calculated based on grain yield of lines under normal and salinity stress conditions.Results and discussionA wide range of genetic variability was obtained among the studied maize lines in terms of grain yield under normal and salinity stress conditions as well as in terms of selection indices for salinity stress tolerance, which provided suitable conditions for evaluating tolerance indices and selection of tolerant lines. STI, MP, GMP, and HM had the highest correlation with grain yield in both normal and salinity stress conditions and were suitable to screen salt-tolerant and high-yielding maize lines. The three-dimensional (3D) plot obtained from these indices showed that the lines Ma025, Ma010, Ma026, Ma011, Ma009 Ma015, Ma116, Ma012, Ma028, and Ma062, which were in group A, had high yields in both normal and stress conditions. The results obtained from the use of principal component analysis showed that the first two principal components account for 93% of the total variance. The first component, called yield potential, had a very significant correlation with STI, MP, GMP, HM, DI, MpSTI, and MsSTI and was able to separate high-yielding maize lines in both normal and stress conditions. The second component, called sensitive or tolerant to salinity stress, had a very high correlation with SSI, TOL, and ATI and was able to distinguish stable maize lines. According to the hierarchical cluster analysis, a total of 86 maize lines were grouped in three tolerant, semi-tolerant, and sensitive clusters somehow this clustering was completely consistent with the separation of maize lines by the first principal component. In addition, each of these clusters had two subclusters that were separated according to the second principal component, so that in each cluster, the lines that had high yield stability were placed in the first subcluster, and the lines that had lower yield stability were placed in the second subcluster. Thus, Ma010, Ma026, Ma009, Ma027, Ma023, Ma007, and Ma005 were introduced as salt-tolerant maize lines with stable yields to use in breeding programs.ConclusionBased on the available findings, the present study, as the first study on a large number of maize lines (86 lines) in the country, evaluated salinity stress tolerance using selection indices. The results of this study revealed the importance of using selection indices for stress tolerance as a reliable and useful tool to improve salinity stress tolerance in maize lines. Accordingly, STI, MP, GMP, and HM were identified as the most appropriate indices for the selection of tolerant and stable maize lines using multivariate statistical methods. It is recommended that the selected maize lines be considered as parent lines in future breeding programs in order to improve salinity stress tolerance and stable grain yield.

Evaluation of the education quality in Indonesia, especially in Vocational High Schools (VHS), carried out through the Presidential Instruction 2016. The implementation of these instructions is not easy because of the different characteristics of each region both geographically and socio-culturally. This study aims to analyze related to the mapping of the characteristics of the quality of vocational education from 34 provinces in Indonesia. The methods used are correspondence analysis, biplot analysis, and cluster analysis which are multivariate statistical analysis methods. The correspondence analysis results show that there are differences in the characteristics of the quality of vocational education from each province based on school accreditation. The biplot analysis show that Teacher Quality is greatest diversity variable compared to other variables. In addition, the provinces of Aceh, East Nusa Tenggara, West Sulawesi and Central Kalimantan have a quality score below the average and are dominated by non-accredited VHSs based on the results of the analysis. The k-means cluster analysis with 4 optimal clusters gives the result that cluster 2 is the cluster with the best quality value while cluster 4 is the cluster with the lowest quality value. Three analytical concluded that provinces with very good quality scores such as DKI Jakarta, Bali and DI Yogyakarta can be used as pilot provinces for other provinces. Meanwhile, provinces with VHS quality scores below the provincial average as a whole should receive attention in order to further improve the quality of their VHSs

Extended Abstract Introduction and Objective:The soybean genotype's stability and high performance are essential factors for long-term development and food security. That the occurrence of various stresses, including drought stress, can cause high losses in the production and supply of this product. This factor has caused the wide attention of researchers to evaluate the stable and tolerant genotypes to drought stress in different environments to introduce the best variety. Materials and Methods: This research investigated the interaction effects of G × E on yield stability in 12 soybean genotypes in four different northern Iran environments. This experiment was conducted as a randomized complete block design with three replications in each environment. During several harvests, yield component traits such as plant height, number of pods, number of seeds per pod, the weight of 1000 seeds, biological yield, harvest index, seed yield, oil percentage, oil yield, and seed protein content were evaluated in 1400 and 1401. Stability tests for multivariate stability parameters were performed based on AMMI and GGE biplot analysis. Results: Among the investigated cultivars, the Sari variety had the highest yield in all three studied regions, and the Hill variety had the lowest yield among the cultivars. The variety Sari in the two environments of Karakhil and Kapik and the varieties Tapur and SBA2 were more compatible with the Bai-Kola region than the rest of the varieties. Sari, Tapur, Caspian, and SBA3 cultivars were in this range. And Telar, Nekader, SBA2, and SBA4 cultivars are in the field of TOL and SSI indices, these cultivars were also identified as drought-sensitive cultivars. Conclusion: In addition to yield stability in the two regions, the Sari variety was tolerant to drought stress and had a higher yield than the rest of the studied varieties. This variety has drought-tolerance genes and is the best parent for transferring these genes. Based on the results of cluster analysis, Hill and SBA6 cultivars had the furthest distance from SBA2. The best parents to improve the generation are crossed to create a diverse population to produce superior cultivars or genotypes.

To optimize growth and management, precision agriculture relies on a deep understanding of agricultural dynamics, particularly crop water status analysis. Leveraging unmanned aerial vehicles, we can efficiently acquire high-resolution spatiotemporal samples by utilizing remote sensors. However, non-linear relationships among data features, localized within specific subgroups, frequently emerge in agricultural data. Interpreting these complex patterns requires sophisticated analysis due to the presence of noise, high variability, and non-stationarity behavior in the collected samples. Here, we introduce Local Biplot, a methodological framework tailored for discerning meaningful data patterns in non-stationary contexts for precision agriculture. Local Biplot relies on the well-known uniform manifold approximation and projection method, such as UMAP, and local affine transformations to codify non-stationary and non-linear data patterns while maintaining interpretability. This lets us find important clusters for transformation and projection within a single global axis pair. Hence, our framework encompasses variable and observational contributions within individual clusters. At the same time, we provide a relevance analysis strategy to help explain why those clusters exist, facilitating the understanding of data dynamics while favoring interpretability. We demonstrated our method’s capabilities through experiments on both synthetic and real-world datasets, covering scenarios involving grass and rice crops. Moreover, we use random forest and linear regression models to predict water status variables from our Local Biplot-based feature ranking and clusters. Our findings revealed enhanced clustering and prediction capability while emphasizing the importance of input features in precision agriculture. As a result, Local Biplot is a useful tool to visualize, analyze, and compare the intricate underlying patterns and internal structures of complex agricultural datasets.

Yield and stability are desirable characteristics that crops need to have high agronomic value; sugarcane stands out globally due to its diverse range of products and by-products. However, genotype-environment (G × E) interactions can affect the overall performance of a crop. The objective of this study is to identify genotypes with the highest yield and stability, as well as to understand their independent and interactive effects. A collection of 10 sugarcane varieties was evaluated, including Colombian, Dominican, Ecuadorian lines, and a group of clones planted across five different locations from 2018 to 2020. A two-way ANOVA along with the GGE biplot technique were used to analyze yield and stability. The ANOVA model shows highly significant effects in all cases (p < 0.001) except for the genotype by year and sector interaction (G × Y × S); however, the decomposition by sectors reveals a significant triple interaction in sector 04 (p < 0.05). The GGE biplot model accounted for up to 74.77% of the total variance explained in its PC1 and PC2 components. It also highlighted the group of clones as having the highest yield and environmental instability, and the Ecuadorian varieties EC-07 and EC-08 as having the best yield-stability relationship. We conclude that the combined results of the ANOVA and GGE biplot models provide a more synergistic and effective evaluation of sugarcane varieties, offering theoretical and practical bases for decision-making in the selection of specific varieties.

IntroductionSafflower is an oilseed plant tolerant to water deficit, and have an important role in oil production. Drought stress is the most important factor limiting crop yields in many parts of the world, including Iran. Nitrogen plays a key role in plant growth and this role is highly related to the amount of water and how it is distributed. Bacteria of the genus Azotobacter are one of the most important growth-promoting bacteria in plants due to their abundance and extent of spread, which is able to improve the availability of nitrogen. In areas where most rainfall occurs in winter and early spring, crops will face water constraints at the end of the growing season. In such conditions, finding cultivars and lines that have good performance in non-stress and drought stress conditions and have a suitable response to Azotobacter and nitrogen fertilizer is of special importance.The aim of this experiment was to evaluate the response of safflower genotypes to the application of Azotobacter and nitrogen fertilizer under different moisture conditions.Materials and methodsThis experiment was carried out during two growing seasons (2015/2016 and 2016/2017), in Sarableh Agricultural Research Station, Ilam Province. The factorial scheme 4 × 6 experiment was performed in both years in a randomized complete block design with three replications under terminal drought stress and non-stress conditions. The distance between these two environments was considered to be 10 meters so that the humidity of the two adjacent environments did not affect each other. Experimental factors included seed inoculation with A. chroococcum using urea chemical fertilizer at four levels [without using any N fertilizer source (control), seed inoculation with A. chroococcumalso without use N fertilizer, seed inoculation with A. chroococcum + 50% N of urea fertilizer source, and 100% N of urea fertilizer source], and six safflower genotypes (312-S6-697, PI-401478, PI-253895, PI-306974, Padideh, and Sina).After harvesting and determining grain yield in both experimental conditions, stress tolerance indices including stress sensitivity index (SSI), mean productivity (MP), tolerance (TOL), geometric mean yield (GMP), stress tolerance index (STI) and Modified stress tolerance indices (MSTI) were calculated. Statistical calculations of analysis of variance and mean comparisons were performed using SAS 9.1 software. STATGRAPH software was used to principal component analysis and drawing biplot diagrams.Results and discussionThe results showed that among the nitrogen source treatments, the highest percentage of grain yield reduction with 48% in drought stress conditions compared to non-stress conditions was related to the application of 100% nitrogen chemical fertilizer. This result shows that in drought stress conditions, the application of 100% nitrogen fertilizer due to the increase of biological substances, causes an imbalance between the roots and plant aerial parts in water absorption and water loss through transpiration by aerial organs, which in Extremely serious damage to the economic sector of the plant.Azotobacter inoculation + 50% nitrogen fertilizer application had the highest mean productivity index and the lowest stress sensitivity index among nitrogen source treatments, although it was not significantly different from other nitrogen source treatments. These results indicate that the use of Azotobacter in combination with the application of 50% nitrogen fertilizer reduces the damage caused by drought stress in safflower. Sina cultivar was the most tolerant genotype under drought stress under Azotobacter inoculation and 100% nitrogen fertilizer application. In conditions of inoculation with Azotobacter + 50% of nitrogen fertilizer application, Sina and Padideh cultivars are located in the area of high production potential and low drought sensitivity in the vicinity of vectors related to drought tolerance indicesConclusionSina cultivar in inoculation treatment with Azotobacter and consumption of 100% nitrogen fertilizer, Padideh cultivar in addition to Sina cultivar in combined application of Azotobacter + 50% nitrogen fertilizer had the highest tolerance to terminal drought stress; Therefore, in selecting drought tolerant genotypes, special attention should be paid to nitrogen source factor.

Quality protein maize (QPM) commercialization can combat the food and nutritional insecurity that is common in some developing nations of the world. Evaluation of QPM hybrids under varying rainfed environments provide valuable evidence for the selection of the most productive genotypes for the target environment. The present study was conducted at three locations to assess the agronomic performance and the grain yield stability of 11 QPM and 2 commercial hybrids (checks) over two years. There were significant (p ≥ 0.01) differences among the environments in the expression of all measured traits while genotype as well as genotype × environment interaction also differed significantly for all the traits except for husk cover and Anthesis-silking interval. The tested QPM hybrids outperformed the local and reference checks by 17.28% and 29.47% respectively. The biplot explained 85.3% of the total variation in yield, with 65.4% attributed to principal component 1 and 19.9% to principal component 2. Three vertex hybrids, EWQH-25, EWQH-21 and Local Check, were identified as the most responsive in the environments within which they fall. Hybrid EWQH-21 produced the highest yield across all environments but was unstable. Therefore, hybrids EWQH-22, EWQH-9, and EWQH-13, with similar yield values and more stable performances were recognized as ideal across environments. Lapai 2017 (E2) proves to be both representative and discriminative, making it the ideal test environment for selecting hybrids with broad adaptability. The study concludes that EWQH-9, EWQH-13, and EWQH-22 be recommended for cultivation across the environments while EWQH-21 be recommended for the specific area of adaptation.

The evaluation of the diversity in the cowpea local varieties (CLVs) allows the efficient use of genetic resources for cultivar development. This study aimed to evaluate the diversity of CLVs based on observation of morphological characteristics and to identify the relationship among morphological traits and potential varieties as donor genes to improve yield potential. The CLVs were collected from five provinces in Indonesia during 2017–2018. The evaluation of the performance of CLVs’ morphological characteristics was carried out in the Indonesian Legumes and Tuber Crops Research from March to July 2019. The observed data were 43 agronomic characters which consist of qualitative and quantitative characters. There is a high variation in stem pigmentation and seed color in 214 CLVs. There were nine qualitative characters with no variation. Most quantitative characters showed significant variation among CLVs. The clustering of 214 CLVs results in five clusters in which some CLVs maintain valuable characteristics that could be used in the breeding program. The number of pods per plant, number of racemes per plant, and 100 seed weight were useful for indirect selection in the yield improvement. Based on the genotype by trait biplot, the CLV 112, 191, and 111 could be used as donor parents for seed size improvement and the CLV 169 could be used as a donor parent for the yield potential improvement in the cowpea breeding program. Four cowpea genotypes can be recommended for commercial release or used as potential breeding material in cowpea cultivar development programs. The new findings of this study could provide a basis for the genetic improvement of cowpea.

Introduction: Today’s society is aware that healthy aging favors quality of life in the future, even more so as life expectancy increases in populations such as Europe. As in countries such as Japan, it is necessary for institutions to provide social services to support the elderly, with the aim of achieving an optimal quality of life for these people. The aim of this study is to analyze the different types of social services and activities that certain institutions provide to the elderly in order to find areas for improvement or to propose relationships between them that will benefit both users and institutions. Methods: Official data from Junta de Castilla y León (Spain) on social services for the elderly in the 9 provinces of the autonomous community of Castilla y León from 2007 to 2021 were analysed using multivariate statistical techniques. Results: Throughout the period under analysis, there is an association between the number of places in public and private non-profit residential centers for the elderly and the number of places in day-care centers or the number of students in the Inter-University Experience Programme. The variables associated with the telecare programme are related to the number of people under guardianship. On the other hand, three well-differentiated clusters of provinces of Castilla y León were observed. Discussion: Our findings have implications for the quality of life of the elderly, as the differences in social services in the areas analysed have a direct impact on the health of the elderly. [ABSTRACT FROM AUTHOR]

The success of plant breeding depends on diversity in plant genetic resources and their responses to changing environments. Accordingly, 20 strawberry genotypes with diverse genetic background were evaluated for their performance under different environments based on the estimation of their genetic variability and heritability. The results showed that environmental factors have great influences on changing the size of the measured traits. Also, a high heritability and genetic variation detected for yield and its components showed a strong potential for improvement among the strawberry genotypes and being considered as raw materials in breeding programs. Biplot and heatmap, in line with the clustering, showed to be key methods for finding the structural association among genotypes and traits. Cluster analysis showed that the genotypes originating from the same geographic area were not necessarily placed in the same clusters which could be due to the environmental variability and the different responses of the genotypes coming from altered genetic materials. The overall results regarding multivariate analyses showed that genotypes Kurdistan, Queen Elisa and No.14 could be considered as a cluster with high similarity for being crossed by other genotypes in the clusters such as groups of Pajaro and Chandler, or the group of Selva and Gaviota. [ABSTRACT FROM AUTHOR]

Objective: considering the importance of early maturityin canola, this research was carried out in order to identify important agronomic traits related to seed yield and to early with high-yielding cultivars in Brassica genus. Methods: The genetic materials examined in this research included 100 genotypes of six species of Brassica genus (B. napus, B. juncea, B. nigra, B. rapa, B. carinata and B. oleracea) were planted in two repetitions in the form of a lattice square design in the research fields of University of Agricultural Sciences and Resources Natural Sari. Results: The results of variance analysis showed that the studied genotypes have very significant differences with each other in terms of all agricultural traits. The results of mean comparison showed that genotypes from B. napus species has the highest yield and genotypes from B. rapa species has the shortest days to ripening with the lowest yield. The analysis of genetic correlations for all species revealed that yield of seed had a significant positive correlation with days to ripening, silique number per plant, thousand grian weight and grian number in silique. Results of stepwise regression analysis revealed that silique number per plant, 1000-grain weight, number of silique per plant and days to maturity had significantly effects on grain yield. The result of factor analysis showed three independent factors that explained 92% of the total variability, which were named 'productivity', 'phenology', and 'thousand grian weight', respectively. Conclusion: According to all three factors, B. napus, best species and Janetzika, Liragold, Hayola 401andHayola 308 from B. napus species, were identified as the best cultivars concerning seed yield and early maturity. [ABSTRACT FROM AUTHOR]

Highly significant variations due to treatments, locations and TxL interactions were observed for wheat yield by analysis of variance during field evaluation of nano urea formulations at number of locations in the north western plans zone of the country. First component of AMMI analysis shared of about 51.3% while second accounted for 29.9%. Significant variations due to locations, TxL interactions and treatments effects were observed for thousands grains weight. Around 82.9% of the interaction effects accounted by two significant components while total of significant components were up to 96.9%. Maximum yield was observed at Karnal followed by Hisar more over maximum yield for 56.1 was expressed by T3 treatment. ASV1 & ASV measures based on 81.3% of interaction effects selected T5, T8 and T8, T5 treatments. Average of thousands grains weight found T3, T8, T9 treatments as suitable for maximum realization and as per MASV1 and MASV settled T6, T2 treatments for thousands grains weight. Adaptability measures corresponding to BLUP estimates of yield i.e. PRVG, PRVG*Gu, HMPRVG*Gu, HMPRVG measures found T3, T4, T2 treatments for yield. Superiority index measures considering average thousands grains weight and stability in 65 and 35 ratios for weighted average settled for T3, T7, T8 treatments formulation of nano urea in the study. Biplot analysis observed Pantnagar center had expressed strong bondage with superiority index measures while considering mean, GAI and HM of treatments based on fixed and random effects of treatments. WAASB, W3, W2, W5 had maintained direct association with MASV, MASV1 on right hand side and with ASV1, W1, IPC4 on left side for yield. Treatments T13, T5 and T4 would express unstable yield as compared to T11, T6, T7 placed near to origin of biplot analysis. Thousands grains weight found that Karnal, Hisar centers with IPV2 formed the first cluster while Gurdaspur with Gwalior joined hands with superiority index measures in second cluster of biplot analysis. Next cluster was of adaptability measures PRVG, HMPRVG, PRVG*Gu, HMPRVG*Gu, mean, GAI, HM with Jammu, Delhi and Ludhiana centres. Next cluster of IPC4, IPC6 with Pantnagar observed near to large cluster of adaptability measures PRVG, HMPRVG, PRVG*Gu, HMPRVG*Gu. [ABSTRACT FROM AUTHOR]

The sustainable management of agricultural residues is a pivotal element in ensuring the sustainable development of agriculture. This is based on strategies that include the reutilization of residues as a substrate for the cultivation of economically significant mushroom species. The primary aim of this investigation is to assess the viability of utilizing two of the most prevalent agricultural residues in Ecuador as a substrate for the cultivation of hybrids within the Pleurotus genus. This assessment includes an evaluation of the nutritional and productivity parameters exhibited by the resulting mushrooms, employing multivariate statistical methodologies. The hybrid strains were developed by crossing compatible neohaplonts obtained through chemical dedikaryotization. A total of five neohaplonts of Pleurotus ostreatus as parental strain P1 and five monokaryons of Pleurotus djamor as parental strain P2 were randomly crossed in all possible combinations. Two parental hybrid strains, H1 and H2, were produced. These hybrids were cultivated using agricultural waste substrates, specifically, green banana leaves (GBL) and sugarcane bagasse (SB). Two distinct treatments or mixtures were tested: M1 (composed of 80% SB and 20% GBL) and M2 (composed of 20% SB and 80% GBL). It was found that the M1 blend promotes mushroom growth, yielding superior properties attributable to the higher proportion of nutritional content derived from sugarcane bagasse. [ABSTRACT FROM AUTHOR]

Introduction Barley (Hordeum vulgare L.) has been known as one of the most adapted cereal crops to various environmental conditions. In addition, this cereal crop ranks fourth in the world in terms of economic importance after wheat, rice, and corn. Identification of high-yielding genotypes with highly desirable growth traits is one of the most important goals in barley breeding programs. However, the present study aimed to select superior genotypes based on grain yield and some morpho-phenological traits using different selection models. Materials and Methods To identify superior genotypes of barley for cultivation in the warm and dry conditions in the southern regions in the Fars province, 21 genotypes were investigated in a randomized complete block with three replications during the 2021-2023 cropping seasons. During the plant growth and development, several morpho-phenological traits were recorded. Agronomic traits measured were days to spike emergence (DHE), days to maturity (DMA), plant height (PLH), grain filling period (GFP), grain yield (GY), 1000-kernel weight (TKW), spike length (SL), spike density (SD), awn length (AL), spike weight (SPW), number of grains per spike (NGS), row type (RT) and number of spikes per m2 (NS). After collecting experimental data, statistical analyses were computed using SAS and R softwares Results and Discussion Results of the analysis of variance (ANOVA) showed that there is a significant difference among the investigated genotypes in terms of all the measured traits (except for Awn length and spike length). Based on the multi-trait genotype-ideotype distance index (MGIDI), genotypes G1 (Oxin), G7, G3, and G14 with the lowest values were identified as superior genotypes. Moreover, the ideotype design via the best linear unbiased prediction (FAI-BLUP) model identified genotypes G20, G8, G2 (Golchin) and G1 (Oxin) as the desirable genotypes compared with other genotypes. The Venn diagram revealed that genotypes G1 and G7 were selected using both selection indices, simultaneously. The MGIDI index showed a positive and significant correlation with DHE (0.58**), while it negatively and significantly correlated with GFP (-0.51*) and GY (-0.74 **). The FAI-BLUP index showed a significant positive relationship with SL (0.50 *) and SPW (0.45*), while it negatively and significantly correlated with DHE (-0.47 *). To better evaluate and group the investigated genotypes, principal components analysis (PCA) was used. Results of the PCA showed that the first and second principal components explained 30.5 and 20.6 percent, respectively. Moreover, the results of the PCA showed that the selected genotypes based on MGIDI and FAI-BLUP indices are located in the 1st and 2nd regions of the PCA diagram. In total, the results showed that there is a relative compliance between the MGIDI and FAI-BLUP indices with PCA. Additionlly, there was a high agreement between the MGIDI indices and the first principal component, and on the other hand, the second principal component showed a high agreement with the FAI-BLUP index. Conclusion In conclusion, the genotype G7 with the highest grain performance and the relative superiority in terms of MGIDI and FAI-BLUP indices was identified as a superior genotype compared to all reference genotypes. Hence, this genotype can be recommended for further comprehensive evaluation before commercial release in the southern regions in Fars province. [ABSTRACT FROM AUTHOR]

To identify genotypes tolerant to drought stress in rice germplasm, a factorial pot experiment was carried out in the form of a completely randomized design with three replications and 70 rice genotypes originating from Central and West Asian countries in non-stress and drought-stress conditions at the Rice Research Institute of Iran, Rasht, north of Iran, in 2019. Based on the results of this year (i.e. 2019), 19 genotypes selected and cultivated in the form of randomized complete block design with three replications in two environments (normal and drought stress) in 2020. Based on tolerance and sensitivity indices and the results of cluster analysis, rice genotypes were divided into two groups, and based on the comparison of means and deviations from the total mean, genotypes of the second group (Shirodi and Neda (Iran), Sela-Zodras and Shisham-Bagh-2014 (Afghanistan) and Dijla (Iraq) recognized as stress-tolerant genotypes. Also, six genotypes (Nada and Shiroudi (Iran), D3 (Iraq), Sela-Zodras, Jalal-Abad Indica-2014, and Shisham Bagh-2014 (Afghanistan)) were identified by biplot analysis and the ranking method of seven genotypes (Shirodi, Neda and Gilaneh (Iran) Sela-Zodras, Jalal Abad Indica-2014 and Shisham Bagh-2014 (Afghanistan) and D3 (Iraq) were recognized as drought stress tolerant genotypes. Altogether, based on the methods of cluster analysis, biplot, and ranking, the genotypes of Shiroudi and Neda (Iran), Sela-Zodras, and Shisham Bagh-2014 (Afghanistan) were recognized as drought tolerant genotypes. The mentioned selected genotypes can be used in advancing breeding programs for developing new rice genotypes with higher tolerance to drought stress.

IntroductionToday’s society is aware that healthy aging favors quality of life in the future, even more so as life expectancy increases in populations such as Europe. As in countries such as Japan, it is necessary for institutions to provide social services to support the elderly, with the aim of achieving an optimal quality of life for these people. The aim of this study is to analyze the different types of social services and activities that certain institutions provide to the elderly in order to find areas for improvement or to propose relationships between them that will benefit both users and institutions.MethodsOfficial data from Junta de Castilla y León (Spain) on social services for the elderly in the 9 provinces of the autonomous community of Castilla y León from 2007 to 2021 were analysed using multivariate statistical techniques.ResultsThroughout the period under analysis, there is an association between the number of places in public and private non-profit residential centers for the elderly and the number of places in day-care centers or the number of students in the Inter-University Experience Programme. The variables associated with the telecare programme are related to the number of people under guardianship. On the other hand, three well-differentiated clusters of provinces of Castilla y León were observed.DiscussionOur findings have implications for the quality of life of the elderly, as the differences in social services in the areas analysed have a direct impact on the health of the elderly.

Psychologically-based chronic pain variables measure multiple domains of the pain experience such as anxiety, depression, catastrophizing, acceptance and stages of change. These variables measure specific areas such as emotional and cognitive states towards chronic pain and its management, acceptance towards the chronic pain condition, and an individual’s readiness to move towards self-management methods. Conceptually, these variables appear to be interrelated to each other, and also form groupings of similar underlying themes. Groupings that have been previously discussed for these variables include positive and negative affect, and improved and poor adjustment. Psychological experience of chronic pain as a whole is mostly understood through conceptually consolidating individual scores across different measures covering multiple domains. A map of these variables in relation to each other can offer an overview for further understanding and exploration. We hereby visualize highlights of relationships among 11 psychosocial chronic pain variables including measures examining physical and somatic aspects, using three-dimensional biplots. Variables roughly form two groupings, with one grouping consisting of items of negative affect, cognition, and physical state ratings, and the other grouping consisting of items of acceptance and the later three stages of change (contemplation, action, maintenance). Also, we follow up with canonical correlation as a complement to further identify key relationships between bimodal groupings. Key variables linking bimodal relationships consist of catastrophizing, depression and anxiety in one grouping and activity engagement in the other. Results are discussed in the context of existing literature.