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Background and objectives: Grass pea (Lathyrus sativus L.), an annual pulse crop belonging to the family of Fabaceae is under grown for food and feed purposes. Lathyrus genus involve in 187 species and subspecies, are cultivated for grain and forage purposes. The world demand for legume proteins is increasing for animal feeding. Grass pea would be a nice alternative for cropping systems in marginal lands and environments. This crop is relatively tolerant to several abiotic stresses; making it a reliable candidate for expansion in the semiarid areas of the world which are predicted to become more drought-prone due to climate change. Materials and methods: This research was carried out in Plant Production and Breeding Department, Faculty of Agriculture, University of Maragheh, Maragheh, East Azerbaijan Province, Iran. The twenty-five grass pea genotypes were provided by ICARDA. In order to evaluate genotypes in terms of salinity tolerance, genotypes were studied at factorial experiments in completely random design with two replications in 2017. Salinity treatments were applied at four levels (0, 40, 80 and 120 mM of NaCl). Different seedlings traits in the laboratory and agronomic trait in pots in the field of were evaluated. Results: The genotypes had significant differences in most of the studied traits. With increasing salinity levels plant height, shoot weight, number of branches, shoot dry weight, leaf width, leaf number, first branch location and seedling time, root length, length of shoots, seedling length, root dry weight and stem dry weight were decreased. The cluster analysis of high-yielding genotypes based on the standardized mean with Euclidean distance and Ward algorithm divided the studied genotypes into three clusters. The first cluster included genotypes 19 and 20. The genotypes 24, 25, 8, 16, 10, 2, and 5 were located into the second cluster, and finally, the third cluster included genotypes 3, 6, 1, 7, 23, 15, 4, 22, 18, 14, 13, 12, 11, 21, 9 and 17. Principal component analysis (PCA) reduced the traits in three main components with 70.25 % of variation, which according to the results the first component was named the grain yield component and the second component as the number of leaves. These components can be used in breeding programs for the selection of genotypes and breeding goals in resistance to salt stress. Conclusion: With increasing in salinity levels, the yield significantly decreased compared to the control. Genotypes 21 and 18 had the highest and lowest germination rates, respectively, and genotypes 8 and 15 had the highest and lowest germination percentages, respectively. In terms of the durability of genotypes to salinity, genotypes 8, 9, 10, 12, 13, 14, 23, and 24 were the best genotypes and the most sensitive genotypes to salinity with low performance were genotypes 19 and 20. Genotypes 5, 14, 10, 16, 21, 24 and 25 (control) had the highest yield. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the variability of Ethiopian black cumin genotypes by using morpho-agronomic traits. Sixty-four genotypes were tested at Debre Zeit and Kulumsa Agricultural Research center in 2021 using an 8 × 8 simple lattice design with two replications. Analysis of variance revealed significant (p ≤ 0.001 or p ≤ 0.01) differences among the genotypes for all traits studied, except the number of primary branches per plant. The effect of location was significant (p ≤ 0.001 or p ≤ 0.05) for all traits except the number of primary branches per plant. It is expected to improve all phenological traits as well as seed yield and yield-related qualitative traits by 4–41% over improved varieties by the selection of the top 5% landraces. Thus, through selection, it would also be possible to shorten the flowering and maturity periods of the genotypes. High broad sense heritability values coupled with high to moderate genetic advance as a percentage of mean values were shown by the number of capsules per plant and plant height which indicates possibilities for improvement of these traits through selection. Plant height, number of primary branches per plant, number of seeds per capsule and thousand seeds weight had a positive and significant phenotypic and genotypic association with seed yield per hectare. Plant height and seed yield per plant had a positive direct effect on seed yield per hectare phenotypically and genotypically. This would be a direct selection criterion for further improvement of the genotypes. The principal component analysis of 12 quantitative traits exhibited 81.5% of the total variance captured by the first four principal components (PCs). Days to 50% flowering, days to full blooming, days to maturity, number of seeds per plant, and seed yield per plant were the main contributor traits for the variation in the first and second PCs. The genotypes were grouped into three different clusters (C-I = 35.93%, C-II = 9.38%, and C-III = 54.69%) based on 12 quantitative traits with significant inter-cluster distances. This clearly showed that there was sufficient diversity among the genotypes which can be exploited for the future black cumin improvement program. [ABSTRACT FROM AUTHOR]

ABSTRACT: Owing to rich in vitamins, proteins, mineral elements, and active substances, the highly medicinal and economic value of mung bean seeds have been proven to be beneficial to human. In order to fully identificate and innovative utilization of excellent germplasm resources for mung bean yield and quality breeding, the genetic diversity level of eight seed phenotypic traits of 302 mung bean germplasm resources were comprehensively evaluated by diversity analysis, correlation analysis, principal component analysis (PCA), and cluster analysis. The results showed the genetic diversity of eight seed phenotypic traits of 302 mung bean germplasm resources with a Shannon diversity Index ranging from 0.25 to 2.09. For most traits, their coefficient of variation (CV) were more than 10% with the highest being seed shape (41.51%). Correlation analysis showed that the 100-seed weight had extremely positive correlations with seed size, seed length, seed width, and seed thickness. PCA of seed phenotypic traits showed that the cumulative contribution rate of the first three principal components was 78.551%. These principal components included seed width, seed coat gloss and seed color. The 302 mung bean germplasm resources were divided into eight groups by cluster analysis. A total of 140 germplasm resources with large-seed were selected from group I and group II, of which 9 germplasm resources in group II were likely to be high-yield varieties. Overall, this study not only indicated sufficient variation among the studied germplasm resources, but also provided a theoretical basis for the selection, utilization and hybrid breeding of mung bean germplasm resources.

Background and objectives: Lentil is an important source of protein, minerals and vitamins in the human diet. In addition, it is rich in minerals and carbohydrates, and its straw provides valuable fodder for animals. Lentil is cool season food legumes that are generally cultivated in semi-arid temperate regions. The introduction of grain legumes such as lentils in agricultural systems and rotation with other crops can contribute to the stability of the nitrogen cycle and increase soil fertility through the biological fixation of atmospheric nitrogen in the soil, disrupt disease cycles and generally help create a better production environment for other crops. Lentil seed yield is strongly influenced by environments and breeders often determine the stability of high yield genotypes across environments before recommending a stable cultivar for release. Identification of high- yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. The challenge of the interaction of genotype × environment is one of the main issues in plant breeding. Various statistical methods to estimate the interaction of genotype × environment and choice the stable and productive genotype(s) have been introduced. One of the applications of Non-Parametric methods is determination of genotypes rank in different environments, which is also used as a measuring stability. A stable genotype shows similar ranks across different environments and has minimum rank variance in different environments. And the genotype that has the minimum average rank in all environments is considered as a stable genotype.Non)Parametric Stability Statistics require no statistical assumptions about the distribution of the phenotypic values and are easy to use. Materials and methods: This study was conducted during two years (2019-2020 and 2020-2021) in two stations in the cold dry areas of the country (Qeydar Zanjan, Maragheh). The experiment consisted of 17 advanced lentil genotypes along with three control cultivars Kimia, Bilesvar and Senna (20 genotypes in total) which was performed in a randomized complete block design with three replications. Each experimental plot consisted of four planting rows of four meters length with a density of 200 Plants m-2, the distance between the lines was 25 cm. Combined analysis of data was done based on four environments. Comparison of means and analysis of combined variance were performed with SAS software assuming that he effect of genotype was fixed and the effect of environment was random. Different non-parametric methods for estimating the stability of genotypes include Si(1), Si(5), Si(4), Si(3), Si(2) and Si(6) non)parametric statistics. Tenarazo NPi(3), NPi(2), NPi(1) and NPi(4), average rank statistic (R), Katata stability statistics σmy,σr, Kang stability statistic (Ysi) and Fox stability statistics (TOP, MID and LOW) and genotype stability index (GSI) were used. Results: The combined analysis of variance indicated that the main effects of genotype (G), environment (E) and their interactions genotype and environmen (G×E) were highly significant (p < 0.05). The principal component analysis (PCA) based on rank correlation matrix indicated that the first two PCAs explained the variance of original variables. Based on bi-plot analysis, the stability parameters were classified into four groups. Clustering of the genotypes according to the mean yield and nonparametric stability statistics showed that there were two main clusters. Overall, according to mean rank of nonparametric stability parameters, G17, G3, G9 and G2 had the lowest variations and were recognized as the most stable genotypes. Genotypes G7, G11 and G13 had the highest values of mean rank of parameters and could be considered as most unstable. According to the present study, the stability measures Ysi, and TOP were associated with mean yield (MY) and the dynamic concept of stability. Therefore, these procedures were suitable for selecting stable and high yielding genotypes. Average seed yield had a positive and significant correlation with TOP, Ysi and SR statistics. Conclusion: Based on these parameters, genotypes G13 (340 t ha-1 ) and G11 (305 t ha-1 ) were identified as high yield stable genotypes. Therefore, these procedures were suitable for selecting stable and high yielding genotypes. [ABSTRACT FROM AUTHOR]

Butterfly pea (Clitoria ternatea L.) is a legume used as tea, forage, ornamental, salad, and medicinal plant. The flowers range from white to dark purple with little known about the variation for seed and flower color in the United States Department of Agriculture, Agricultural Research Service, Plant Genetic Resources Conservation Unit germplasm collection. Therefore, 26 butterfly pea accessions were analyzed using a principal component analysis (PCA) and average linkage cluster analysis (ALCA). These butterfly pea genotypes ranged from 56% to 99% for viabilities, 2.57 to 5.88 g for 100 seed weight, 34.07 to 226.26 g for total seed weight, and 1,326 to 3,874 for total seed numbers. PCA accounted for 40%, 57%, 70%, 79%, and 86% of the variation using principal components (PCs) 1 through 5, respectively. PC1 was most correlated with 100 and total seed weight, while PC2 correlated with blue, white, and purple flowers. PC3 correlated mostly with germination, purple flowers, and total seed weight. PCs 4 and 5 primarily correlated with blue and purple flowers, respectively. Several significant correlations were also observed. ALCA grouped the 26 butterfly pea genotypes into four distinct seed number–producing clusters. Clusters 1 to 4 represent the lowest to highest seed numbers produced by the butterfly pea genotypes. Several potential health benefits from butterfly pea flowers, leaves, seeds, and roots for human use were identified from the literature. [ABSTRACT FROM AUTHOR]

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In this study, the level of genetic variation in the phenotypic traits of 215 sugar beet germplasm resources was evaluated by correlation analysis, principal component analysis and cluster analysis. The genetic diversity of the descriptive traits showed the highest growth potential index (1.423) and the lowest graininess index (0.176). Among the quantitative traits, the coefficient of variation was the highest for α-N content (78.226%) and the lowest for seed set (17.995%). Correlation analysis showed that there were extremely negative correlations between the number of leaves and the 100-seedling weight and sugar content. In terms of belowground traits, the root yield exhibited extremely significantly positive relationship with sugar yield, potassium content and α-N content. Principal component analysis of ten quantitative traits showed that the cumulative contribution of the first four principal components was 71.325%. These principal components included sugar yield, sugar content, leaf number and ring number per vascular bundle. The 215 germplasm resources were divided into four groups by cluster analysis. Group II and Group III could be used for breeding new varieties of energy beet, fodder beet or sugar beet, and Group IV members could be used for germplasm resource development and breeding. Overall, these results provide a theoretical basis for the selection, utilization and breeding of sugar beet germplasm resources. [ABSTRACT FROM AUTHOR]

A set of 36 promising genotypes were evaluated for 33 agro-morphological traits. Sufficient genetic variability was found for almost all the characteristics of wheat. Genetic diversity among nineteen traits of wheat genotypes was estimated using Mahalanobis D2 analysis and principal component analysis (PCA). Sufficient genetic diversity was observed among the genotypes and grouped genotypes into five clusters by Tocher’s method. Cluster I contained the maximum numbers of genotypes (32) and the remaining clusters II, III, IV and V were mono-genotypic. The lowest inter cluster distance was noticed between clusters III and I (260.57) and maximum between Cluster IV and V (891.62). The larger inter-cluster distances between clusters were considered more diverged than those with small distances. The major contributing character towards genetic divergence was found to be grain yield per plant (25.24%), followed by wet gluten (21.59%), chlorophyll content (11.11%) and protein content (10.63%). Principal component (PC) analysis resulted in eight principal components (PCs) having Eigenvalue >1 which contributed 78.67 per cent of the total variability amongst the wheat genotypes assessed for various morpho-physiological traits. The traits with the highest weight in component first were the number of tillers per plant, the number of ear per plant, grain yield per plant and harvest index which explained 15.17 per cent of the total variation. Component 2 was associated with protein content and wet gluten content which account for 13.91 per cent variation. In component 3, traits with highest weight were days to heading, days to maturity, plant height, the number of spikelets per ear, ear length and relative water content which explained 13.41 per cent of the total variation. Similarly, the traits with the highest weight in component 4 were sedimentation value; biological yield per plant in component 5; ear weight and chlorophyll content in component 6; peduncle length, 1000-grain weight and canopy temperature in component 7 was the major contributing traits which account for 8.89, 7.78, 7.20 and 6.31 per cent variability, respectively for the above traits. The result of the present study could be exploited in the planning and execution of a future breeding programme in wheat.

The present investigation was undertaken to decipher multivariate diversity, variability, genetic parameters and traits association in Ashwagandha (Withania somnifera (L.) Dunal), genotypes for the yield of a dry root, total alkaloids in root and agro-morphological traits. A total of 16 genotypes were evaluated at three experimental sites in Gujarat, India. A randomized complete block design with two replications was used to conduct the trial. Pooled ANOVA results showed highly significant differences (p < 0.001) among the genotypes (G), environments (E) and G x E interactions. Higher phenotypic and genotypic coefficient of variation values were recorded for yield and agro-morphological traits indicating variation and scope of improvement through selection based on phenotypes. Higher heritability associated with greater genetic advance for the majority of traits showed a prevalence of additive gene effect and thus, phenotypic selection will be more productive. Based on the similarity of traits within and between members of clusters, genotypes were divided into five clusters. The principal component analysis (PCA) showed that most of the differences (76.90%) were explained by the first four PCA. The correlation analysis implies that improving one or more components traits could result in enhancement in root yield and total alkaloid content in ashwagandha. Genetic variability was present for the traits under study in the tested genotypes. Hybridization of genotypes from different clusters could be able to yield new genotypes combining high yield and other desirable yield-contributing traits.

For ranking and grouping of full-sibs and hybrids of sugar beet obtained from breeding programs, two separate experiments were carried out at the farm of the Agricultural and Natural Resources Research Station of Miandoab in 2017 under saline and normal conditions. For this purpose, 17 full-sibs and 28 hybrids differing in resistance and susceptibility to environmental stresses were investigated in for different traits. The ranking results in both conditions indicated that genotypes 18 and 22 in full-sibs test and, genotypes 6, 23, 25, 27 and 29 in the hybrid test were superior to all other genotypes. Cluster analysis showed that in both experiments (full-sibs and hybrids), there was a slight matching between the normal and saline environments and the environment affects the grouping of genotypes. Principle Components Analysis in the full-sibs test indicated that in both conditions, leaf area, root yield, sugar yield, root dry weight, relative water loss, sugar content, purity of syrup and extractable sugar content had the highest contribution in the first and second components. In contrast, in the hybrid test, leaf area, root yield and leaf water content had the highest role in the first and second components. Most of the traits studied in the experiments contained diversity and can be used for grouping sugar beet genotypes. Also, groupings will vary depending on environmental conditions.

An investigation was undertaken during rabi season of 2018 to evaluate fifteen okra genotypes for agro-morphological traits. Variability parameters indicated high GCV and PCV values for the number of fruits per plant, yield per plant and 100 seed weight and the narrow differences between GCV and PCV determine that traits under study had negligible environmental influence. High values of heritability coupled with high genetic advance were recorded for all the traits studied. Fruit length and the number of fruits per plant had a positive and significant correlation with yield per plant. The number of fruits per plant had the highest positive and direct effect on yield per plant. The first four principal components (PC1 to PC4) gave eigenvalues > 1 and cumulatively expressed 84.28 per cent of the total variation. Cluster analysis suggested that the hybridization of cluster I with cluster II will be favourable for developing varieties under multiple environmental conditions in India. Therefore, these quantitative traits in these clusters can be selected to enhance yield potential as they will be beneficial in developing promising varieties under diverse climatic conditions throughout India.

This study presents a spatial assessment of eight potentially toxic elements (PTE: Cd, Cr, Cu, Fe, Pb, Ni, Mn, and Zn) in white button (Agaricus bisporus J.E. Lange) mushroom samples collected from the local vegetable markets of Uttarakhand State, India. Fresh A. bisporus samples were collected from thirteen districts and fifteen sampling locations (M1-M15) and analyzed for the concentration of these PTE using atomic absorption spectroscopy (AAS). The results revealed that A. bisporus contained all eight selected PTE in all sampling locations. Based on the inverse distance weighted (IDW) interpolation, principal component (PC), and hierarchical cluster (HC) analyses, the areas with a plane geographical distribution showed the highest PTE concentrations in the A. bisporus samples as compared to those in hilly areas. Overall, the decreasing order of PTE concentration in A. bisporus was recognized as Fe > Zn > Mn > Cr > Cu > Ni > Cd > Pb. The Kruskal–Wallis ANOVA tests displayed a highly significant (p < 0.05) difference among the sampling locations. However, the concentration of PTE was below permissible limits, indicating no potential hazard in consuming the A. bisporus. Similarly, the health risk assessment studies using the target hazard quotient (THQ) also showed no significant health risk associated with the consumption of A. bisporus being sold in the local mushroom markets of Uttarakhand, India. This study is the first report on state-level monitoring of PTE in A. bisporus mushrooms, which provides crucial information regarding the monitoring and occurrence of potentially toxic metallic elements. [ABSTRACT FROM AUTHOR]

BackgroundThe external clinical manifestations (psychopathology) and internal subjective experience (phenomenology) of catatonia are of clinical importance but have received little attention. This study aimed to use a large dataset to describe the clinical signs of catatonia; to assess whether these signs are associated with underlying diagnosis and prognosis; and to describe the phenomenology of catatonia, particularly with reference to fear.MethodsA retrospective descriptive cross-sectional study was conducted using the electronic healthcare records of a large secondary mental health trust in London, United Kingdom. Patients with catatonia were identified in a previous study by screening records using natural language processing followed by manual validation. The presence of items of the Bush-Francis Catatonia Screening Instrument was coded by the investigators. The presence of psychomotor alternation was assessed by examining the frequency of stupor and excitement in the same episode. A cluster analysis and principal component analysis were conducted on catatonic signs. Principal components were tested for their associations with demographic and clinical variables. Where text was available on the phenomenology of catatonia, this was coded by two authors in an iterative process to develop a classification of the subjective experience of catatonia.ResultsSearching healthcare records provided 1,456 validated diagnoses of catatonia across a wide range of demographic groups, diagnoses and treatment settings. The median number of catatonic signs was 3 (IQR 2–5) and the most commonly reported signs were mutism, immobility/stupor and withdrawal. Stupor was present in 925 patients, of whom 105 (11.4%) also exhibited excitement. Out of 196 patients with excitement, 105 (53.6%) also had immobility/stupor. Cluster analysis produced two clusters consisting of negative and positive clinical features. From principal component analysis, three components were derived, which may be termed parakinetic, hypokinetic and withdrawal. The parakinetic component was associated with women, neurodevelopmental disorders and longer admission duration; the hypokinetic component was associated with catatonia relapse; the withdrawal component was associated with men and mood disorders. 68 patients had phenomenological data, including 49 contemporaneous and 24 retrospective accounts. 35% of these expressed fear, but a majority (72%) gave a meaningful narrative explanation for the catatonia, which consisted of hallucinations, delusions of several different types and apparently non-psychotic rationales.ConclusionThe clinical signs of catatonia can be considered as parakinetic, hypokinetic and withdrawal components. These components are associated with diagnostic and prognostic variables. Fear appears in a large minority of patients with catatonia, but narrative explanations are varied and possibly more common.

In the present study, a total of 273 bulls between 12 and 26 months of age were studied using morphometric measurements in order to establish a cattle grading system for beef cattle in Tunisia. The bulls were mainly Holstein (169), Limousin (16), Charolais (58), Salers (11), and crossbred animals (19). Measurements of the height at withers (WH) and pelvis (PH), the width (CW) and girth of the chest (CG), the width at pelvis (PW), and the depth of chest (CD), in addition to the weight and age at slaughter, were recorded. Statistical evaluations were made using of the principal component analysis (PCA) as well as a Ward's cluster analysis (WCA). High correlations were recorded between the weight, the width at pelvis (r = 0.90), the chest width (r = 0.89), and the chest perimeter (r = 0.89). Principal components analysis identified two main components that could characterize the carcasses. Ward's cluster analysis based on the two main components displayed the presence of four groups of bulls defined as following: (1) bulls with a low conformation and a small frame size, (2) bulls with a medium conformation and a large frame size, (3) bulls with fairly good conformation and a small frame size, and (4) bulls with a good conformation and a large frame size. Consequently, live weight and the height at withers can be used as the main measurements to establish a live cattle grading grid in Tunisia including a combination of live weight (light or heavy) and withers height (tall or short). [ABSTRACT FROM AUTHOR]

For ranking and grouping of full-sibs and hybrids of sugar beet obtained from breeding programs, two separate experiments were carried out at the farm of the Agricultural and Natural Resources Research Station of Miandoab in 2017 under saline and normal conditions. For this purpose, 17 full-sibs and 28 hybrids differing in resistance and susceptibility to environmental stresses were investigated in for different traits. The ranking results in both conditions indicated that genotypes 18 and 22 in full-sibs test and, genotypes 6, 23, 25, 27 and 29 in the hybrid test were superior to all other genotypes. Cluster analysis showed that in both experiments (full-sibs and hybrids), there was a slight matching between the normal and saline environments and the environment affects the grouping of genotypes. Principle Components Analysis in the full-sibs test indicated that in both conditions, leaf area, root yield, sugar yield, root dry weight, relative water loss, sugar content, purity of syrup and extractable sugar content had the highest contribution in the first and second components. In contrast, in the hybrid test, leaf area, root yield and leaf water content had the highest role in the first and second components. Most of the traits studied in the experiments contained diversity and can be used for grouping sugar beet genotypes. Also, groupings will vary depending on environmental conditions. [ABSTRACT FROM AUTHOR]

Grain legumes, including cowpea, are the cheapest sources of minerals and protein to enhance human nutrition. Cultivar development and deployment of cowpea with increased grain mineral content and protein composition rely on selection of genetically unique and complementary breeding lines. The objective of this study was to assess the grain minerals and protein composition of diverse cowpea collections of eastern, southern and western Africa to select promising parents to develop a breeding population. Twenty-two genetically diverse cowpea genotypes were field evaluated using a randomised complete block design with three replications in two locations in South Africa. The dried grain mineral contents were determined using an Atomic Absorption Spectrophotometre, while the protein content was determined by the combustion method. Analyses of variance showed significant (P

This study presents a spatial assessment of eight potentially toxic elements (PTE: Cd, Cr, Cu, Fe, Pb, Ni, Mn, and Zn) in white button (Agaricus bisporus J.E. Lange) mushroom samples collected from the local vegetable markets of Uttarakhand State, India. Fresh A. bisporus samples were collected from thirteen districts and fifteen sampling locations (M1-M15) and analyzed for the concentration of these PTE using atomic absorption spectroscopy (AAS). The results revealed that A. bisporus contained all eight selected PTE in all sampling locations. Based on the inverse distance weighted (IDW) interpolation, principal component (PC), and hierarchical cluster (HC) analyses, the areas with a plane geographical distribution showed the highest PTE concentrations in the A. bisporus samples as compared to those in hilly areas. Overall, the decreasing order of PTE concentration in A. bisporus was recognized as Fe > Zn > Mn > Cr > Cu > Ni > Cd > Pb. The Kruskal–Wallis ANOVA tests displayed a highly significant (p < 0.05) difference among the sampling locations. However, the concentration of PTE was below permissible limits, indicating no potential hazard in consuming the A. bisporus. Similarly, the health risk assessment studies using the target hazard quotient (THQ) also showed no significant health risk associated with the consumption of A. bisporus being sold in the local mushroom markets of Uttarakhand, India. This study is the first report on state-level monitoring of PTE in A. bisporus mushrooms, which provides crucial information regarding the monitoring and occurrence of potentially toxic metallic elements.

Durum wheat (2 n = 28, AABB, Triticum turgidum L. ssp. durum) is the most commonly cultivated form of allotetraploid wheat and is grown on 8% of the world’s wheat area. The trial was conducted at Dabat station of Gondar Agricultural Research Center, northern Ethiopia, with the objective of assessing the nature, extent, and patterns of genotypic and phenotypic variation in durum wheat accessions for yield, yield-related and quality traits. Sixty-four durum wheat landraces were evaluated using an 8 × 8 simple lattice design. Analysis of variance revealed the presence of highly significant (P

The article is devoted to the study of the relationship between the lengths of orthologous proteins of four organisms, one of which is taken as the basic one ( more than 1200 proteins in total). The methods of multivariate statistical analysis are used, it is applied to pairs, triples and fours (strings) composed of lengths of orthologous proteins. The number of such lines is from 200 to 400. The analysis of pair correlations, orthogonal transformation and cluster analysis allowed us to distinguish two homogeneous clusters of four-lengths. At the same time, we studied the increments of the length of the orthologous protein relative to the basic organism. We showed that the lines form a non-uniform sample, and the increments form a homogeneous sample. Then the task was to expand the clusters with rows with incomplete data. It was shown that cluster analysis is not applicable for this task, so we used discriminant analysis with a training sample — clustering with complete data. A 100 percent separation of all incomplete rows by clusters was obtained; with the following description of the length dependences of clusters on the base. The adequacy of the resulting regression equations was tested. As a result of statistical analysis, the following conclusions were made. For a set of lengths of orthologous series, a generalizing factor was obtained, let's call it the size of an orthologic object from 4 lengths of orthologous proteins. For the given task such sizes of objects were obtained, and their average group values differ, they form two separate ranges of values, one for each group of the values obtained by other methods. For series of increments of the lengths of orthologous proteins from objects of four, an analysis performed by all methods showed homogeneity of the set. It was shown that the lengths of orthologous proteins have significant autocorrelation, as is the case with rows associated with the same basic series.

Spatial variation of hydrochemical groundwater parameters indicates that the chemistry is ruled by complex process interactions (mixing of natural and anthropogenic processes). For this approach, analysis of 32 groundwater wells was conducted. Anthropogenic-influenced surface recharge and geogenic processes such as silicate weathering and redox process are identified by multivariate statistics, principal component analysis (PCA) and cluster analysis (CA). Surface water recharge tops the list of factors affecting groundwater chemistry in the Sohag area. The main recharging sources are leaching of salts of overlain soils and irrigation canals associated with anthropogenic impacts such as domestic sewage and agricultural nutrients. The excess of SO42− and HCO3− relative to Ca2+ in the semiconfined shallow aquifer at the floodplain can be attributed to the anthropogenic influence, infiltrated irrigation water and wastewater. On the other hand, in deep wells at the desert fringes, the deficiency of SO42− relative to Ca2+ concentration (however the dissolution of gypsum modeled by MINTEQ) is evidence on sulfides precipitation under reducing conditions as confirmed by the PCA analysis. Ion exchange on clay is another possible reason responsible for the deficiency of Ca2+ + Mg2+/SO42− + HCO3− relative to Na+/Cl− in semiconfined aquifer. Different water types (Na–Cl, Ca–Cl, Mg-–Cl and Na–HCO3) indicate different ion exchange processes formed due to varying contacts between freshwater and saline water. Excessive Mn/Fe ratio is attributed to fertilization and redox processes. Results enable the spatial separation of wells under semiconfined hydraulic conditions recharged by infiltrated irrigation water, from those under unconfined conditions recharged by seepage water leaching salty soils. Accordingly, different water types and values of salinity are complex and could be identified and spatially separated using AqQa and statistical analysis. [ABSTRACT FROM AUTHOR]

• The objective of this research is to examine the possibility of introducing telemedicine-based services in developing countries. • We surveyed developing countries in Asia and Africa. In Asia, the study was conducted in nine developing countries, excluding those whose data were unavailable. In Africa, 13 countries that had a per capita GDP less than USD 1,000, and where data were unavailable, were excluded. • The target countries were classified into five clusters according to economic indicator, medical environment indicator, IT spread index. • The results of this research suggest that there is a good possibility of introducing remote telemedicine services in South Africa and that the possibility for its introduction is also high in Thailand where internet spread is more advanced. In some developing countries, despite advancements in Information Technology (IT), medical resources are scarce; hence, introduction of telemedicine services can solve this problem. In this study, we examined the possibility of introducing telemedicine-based services in developing countries utilizing the available data. In Asia, the study was conducted in nine developing countries, excluding those where data were unavailable. In Africa, thirteen countries whose per capita Gross Domestic Product (GDP) was less than USD 1000, and where data were unavailable, were also excluded. We chose the number of doctors, nurses, and midwives as indicators of the healthcare environment. We used the number of internet contracts and mobile phone contracts as indicators of IT penetration, and set per capita GDP and its growth rate as economic indicators. We combined the two continents' data and performed a principal component analysis (PCA) and cluster analysis. We used cluster analysis to classify the target countries into the following five clusters: Cluster A: Algeria, Egypt, Morocco, Indonesia, Ghana, Tunisia, Madagascar, Nigeria, and Thailand; Cluster B: Bangladesh, Ethiopia, Kenya, Uganda, India, and Pakistan; Cluster C: Sudan, Malaysia, Vietnam, Tanzania, Philippines, and China; Cluster D: South Africa, and Cluster E: Japan and Singapore. As a result of conducting PCA, Cluster A emerged as the region with the highest progressiveness and development possibility. Introduction of telemedicine services has been visualized by using cluster analysis and PCA. However, it is necessary to incorporate future medical needs as indicators to make a more appropriate assessment of its potential. [ABSTRACT FROM AUTHOR]

Durum wheat (2 n = 28, AABB, Triticum turgidum L. ssp. durum) is the most commonly cultivated form of allotetraploid wheat and is grown on 8% of the world's wheat area. The trial was conducted at Dabat station of Gondar Agricultural Research Center, northern Ethiopia, with the objective of assessing the nature, extent, and patterns of genotypic and phenotypic variation in durum wheat accessions for yield, yield-related and quality traits. Sixty-four durum wheat landraces were evaluated using an 8 × 8 simple lattice design. Analysis of variance revealed the presence of highly significant (P < 0.01) variations among Accessions for all traits. The observed wide range of differences among genotypes for these main traits may be due to genetic differences of genotypes and selection can be effective for different breeding programs. High values for both heritability (85.5%) and genetic advance as percent mean (19.96) for plant height indicates better possibility and easiness for improvement of the trait through selection. Genotypic and phenotypic coefficients of variation ranged from 3.08 (days to maturity) to 12.67 (thousand seed weight) and 4.94 (days to maturity) to 18.93 (grain yield t/ha), respectively. Highly significant and positive phenotypic and genotypic correlations were observed between grain yield and biological yield (rp = 0.67, rg = 0.59), thousand seed weight (rp = 0.37, rg = 0.43) and harvest index (rp = 0.58, rg = 0.46) respectively. The highest positive and significant genotypic direct effects on grain yield were exerted by days to maturity, biological yield and harvest index, phenotypic direct effects on grain yield were via days to heading, grain-filling period, biological yield, and plant height. The highest intracluster distance was observed in cluster XI (45.27) and the lowest in cluster IV (5.66). The highest inter-cluster distance was between cluster V and VIII (996.7) followed by cluster I and XI (690.71). The first five principal components, whose eigenvalues greater than one, accounted for 81.58% of the total variation. The variability and diversity of traits, which were exhibited among the genotypes, can serve in planning selection and crossing programs for durum wheat improvement and the selection and hybridization of genotypes based on the traits with a high positive correlation coefficient and direct effects on grain yield can be recommended for further yield improvement of durum wheat. [ABSTRACT FROM AUTHOR]

Grain legumes, including cowpea, are the cheapest sources of minerals and protein to enhance human nutrition. Cultivar development and deployment of cowpea with increased grain mineral content and protein composition rely on selection of genetically unique and complementary breeding lines. The objective of this study was to assess the grain minerals and protein composition of diverse cowpea collections of eastern, southern and western Africa to select promising parents to develop a breeding population. Twenty-two genetically diverse cowpea genotypes were field evaluated using a randomised complete block design with three replications in two locations in South Africa. The dried grain mineral contents were determined using an Atomic Absorption Spectrophotometre, while the protein content was determined by the combustion method. Analyses of variance showed significant (P < 0.05) effects of genotypes, locations and their interactions. The test genotypes showed considerable variation for the following nine mineral contents: calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn), sodium (Na), phosphorus (P), and zinc (Zn) varying from 0.07 to 0.12 mg kg−1; 4.46 to 7.81 mg kg−1; 0.06 to 0.11 g; 11.82 to 14.45 g; 1.86 to 2.27 g; 9.24 to 13.30 mg kg−1; 0.26 to 0.80 g; 4.63 to 5.92 g and 0.03.00 to 0.05 g, respectively. Further, the total protein content varied from 23.16 to 28.13%. Significant correlations were detected among some mineral elements and total protein content, suggesting the possibility of simultaneous selection for these traits. The principal component analysis (PCA) identified four principal components (PCs) contributing to 70.93% of the total explained variation amongst genotypes. Overall the following genotypes with desirable grain mineral and protein attributes were selected: IT90K-59 (Ca), 98K-5301 (Ca and protein), ITOOK-1060 (Cu), ITOOK-1217 and IT845-2246 (Fe), Bensogla (K, Na, and P), TVU11424 and ITOOK-1217 (Mg), CH14 (Mn and Na), TVU12637 (Mn) and Glenda and Vuli (Zn). The selected cowpea genotypes are useful genetic resources for population and cultivar development for grain nutrients composition. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Plant Production is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The multivariate statistical approach is one of the most common techniques applied in livestock classification, where quantitative and qualitative variables are used throughout the statistical analysis to obtain farms descriptions. The aim of this study was to divide dairy farms on the bases of farm size, mechanization level, energy profile and availability of building and facilities. A population of 285 conventional dairy cow farms located in the south of Italy was involved in this project. Using the principal component analysis and the k-means cluster analysis allowed to obtain 3 different groups. Results showed a repartition where 156 farms were located in cluster 2 “semi-intensive, low structural and mechanized farms”, 110 farms in cluster 1 “semi-intensive, high structural and mechanized farms”, and 19 farms were positioned in cluster 3 characterized by “intensive, high structural and mechanized farms. Larger farms are equipped with a wide number of appliances, holding higher level of power installed, but when reported to the number of raised heads or to the cultivated land area as indices, larger farms resulted more efficient and utilized less power per unit.

A methodology for the classification of railway passenger stations was developed in this study. Four groups of factors are defined to study the characteristics of the station: potential of the town, importance of the town, infrastructural factors, and characteristics of passengers. In the research we investigated 18 factors and studied 98 passenger stations of railway network in Bulgaria. The method of principal components has been applied for grouping the factors and cluster analysis has been applied to classify the stations. The factors have been classified into 4 components by the method of principal components. The stations have been classified into 6 groups using hierarchical cluster analysis. The methods, Average linkage between group and Within-groups linkage, and distance-type measures Euclidean distance and Squared Euclidean distance were compared to verify the results of cluster analysis. The grouping of the stations has been used for the determination of the stops for categories intercity passenger trains. The main groups of stations for servicing express trains are the first, second, third, fourth and fifth groups. In the sixth group are stations for servicing fast passenger trains. The methodology can be applied to the study of all stations and stops in the rail network.

In order to investigate drought tolerance indices of 14 maize hybrids to different levels of water deficit, a split-plot experiment was conducted in complete randomized block design with four replications at the Agricultural Research Station, University of Tabriz. The main plots consisted of three levels of irrigation regimes (control, mild and severe water deficit) and sub-plots of 14 corn hybrids. Drought tolerance indices were calculated for the grain yields produced. Under mild drought condition, hybrids like SC702, SC500 and K3647×K18 were tolerant based on tolerance index (TOL) and stress susceptibility index (SSI) indices while hybrid SC 500 was the most tolerance one. Based on stress tolerance index (STI), mean productivity (MP) and geometric mean productivity (GMP) indices under both mild and severe stress conditions hybrids K166×K18, SC500، K3647×K18 and SC400 were found to be the most tolerant to water deficit than others. The STI and GMP indices that had highest positive correlation with grain yield under both of these stress conditions. Thus these two indices were determined as the best indices for selection of tolerant hybrids. Cluster analysis based on these two indices classified hybrids into two groups under mild stress and in three groups under severe stress conditions. Biplot graphs for two main components based on principle components analysis (PCM) displayed that SC500 to be a tolerant maize hybrid in both mild and severe drought stress conditions with high yield performance. Also, hybrids SC700 and SC704 were low yielders under both control and stress conditions and thus were identified to be as sensitive hybrids.

The aim of this study was to display distribution and relationships of heavy elements in the unconfined, shallow alluvial aquifers of the lower Jia Bharali catchment and adjoining areas in central part of North Brahmaputra Plain (NBP), India using hydrochemical as well as multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis. The original matrix was made up of 10 trace elements (As, Cd, Cu, Co, Cr, Fe, Mn, Pb, Ni and Zn) estimated from 50 shallow alluvial dug wells in both the wet and the dry season for a duration of 3 hydrological years (2008-2011). Except As, Cu and Zn all the other toxic metals in the shallow aquifers were found exceeding the WHO maximum permissible limits for drinking water. PCA extracted five varimax factors as geogenic, agricultural and anthropogenic explaining about 71.2% of the total variance in the wet season and 69.3% total variance in the dry season. Hierarchical cluster analysis classified the dug wells into two groups in the wet season and three groups in the dry season with respect to the heavy elements. The results emphasized the need for routine monitoring and management in order to avoid contamination of groundwater sources in the NBP with respect to the dissolved trace elements. [ABSTRACT FROM AUTHOR]

Background: The global market has an increasing demand for buffalo by-products due to their unique nutritional characteristics. Many buffalo herds lack suitable breeding control programs, hindering the implementation of selection programs. Objective: To evaluate milk production per lactation (MP), lactation length (LL), and calving interval (CI) of a herd of crossbred Murrah buffaloes to support buffalo clustering according to their potential. Methods: Data from 543 lactations between 2002 and 2014 from 105 crossbred Murrah female buffaloes were used. Data were subjected to principal component analysis (PCA) and cluster analysis. Results: The first components (PCs) were responsible for 92.32% of the total variation, of which 61.45 and 30.87% were explained by the first (PC1) and second (PC2) components, respectively. The cluster analysis allowed three female buffalo groups according to their potentials. Conclusion: Buffalo farmers can make decisions on nutritional, reproductive management and cow culling based on grouping. [ABSTRACT FROM AUTHOR]

In an attempt to protect the earth in the era of climate change, effort has been put forth to restrict carbon emission globally. Although Korea is not one of the countries being obliged to reduce carbon emission specified in Kyoto Protocol, it has voluntarily implemented the emission trading scheme. In the midst of current situation 'low carbon', 'green growth' and paradigm are receiving global attention from the recent issue of climate change. This will provide a direction on understanding the emission trading of Korea in comparison with other developed countries, while determining the future direction of Korea's emission trading. However, studies and data on domestic and international emission trading are currently lacking. Therefore for the purpose of understanding the nature of emission trading of Korea and corresponding guidelines, this paper analyzed the characteristics of domestic and international emission trading through principal component analysis and cluster analysis. The findings will be useful in identifying emission trading of other countries similar to the position of Korea. The significance of this study was to use the findings to provide reliable reference information for improving emission trading. [ABSTRACT FROM AUTHOR]

Dasypyrum is a genus with two species, an annual diploid Dasypyrum villosum and a perennial diploid or tetraploid D. breviaristatum. It is difficult to distinguish between the two, especially for a non-taxonomist. In this paper we demonstrate how to distinguish between the two species and between the two ploidy levels of D. breviaristatum. We achieve this using RAPD analysis to identify potential candidates for marker development and after carrying out principal component analyses and partitioning of genetic variance, developed SCARs and an identification key. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Kirkuk University for Administrative & Economic Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With traditional driving cycle predictive model, the state point in vehicle-acceleration projection plane couldn’t cover the real driving state completely. And date-missing caused by this lead to interruption of the prediction process. So in this paper, a real-time prediction model with variable horizon is proposed to solve the problem. Real driving data is used to reconstruct the driving cycle and the accuracy of the real time prediction model could be estimated based on historical information. By using principal component analysis and cluster analysis, an online prediction model with variable horizon based on Marco Chain is established. The correctness of this method is verified by experiment of Hardware-in-loop simulation. And the result shows that the accuracy of variable time prediction model is 8.203km/h, which has been improved by 20% comparing with fixed time prediction model. [ABSTRACT FROM AUTHOR]

The aim of this paper was the application of multivariate statistical techniques to evaluate spatial and temporal variations in the water quality of Potrero de los Funes River using physical, chemical and bacteriological parameters and select the most significant parameters of organic pollution in the river in order to implement in the future water quality monitoring. The river was monitored regularly at three sites: RP1, RP2 and RP3, over the period 2008–2009, for 16 parameters. The complex data matrix was treated with three multivariate statistical techniques: cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA). CA generated three groups of sites, cluster 1 (RP1), cluster 2 (RP2) and cluster 3 (RP3) according to relatively low, very high and moderate pollution regions, respectively. PCA identified two components, which were responsible for the data structure explaining 73% of the total variance of the data matrix. Temporal DA (Wet season and Dry season) showed that turbidity, NO3- and COD were the discriminant variables. Spatial DA shows that there were significant differences between the three categorical classes, 1 (RP1, low pollution region), 2 (RP2, strongly polluted zone) and 3 (RP3, moderate polluted site) .The discriminating functions contained only eight parameters (EC, NO3-, turbidity, DO, BOD, COD, total coliform and fecal coliform) to discriminate between sites. The application of these techniques has achieved meaningful classification of physical, chemical and bacteriological variables and of river water samples, based on seasonal and spatial criteria. This study is essential for the future design of fast and effective monitoring programs of river water quality. That would include only parameters that are indicative of organic pollution.

A methodology for the classification of railway passenger stations was developed in this study. Four groups of factors are defined to study the characteristics of the station: potential of the town, importance of the town, infrastructural factors, and characteristics of passengers. In the research we investigated 18 factors and studied 98 passenger stations of railway network in Bulgaria. The method of principal components has been applied for grouping the factors and cluster analysis has been applied to classify the stations. The factors have been classified into 4 components by the method of principal components. The stations have been classified into 6 groups using hierarchical cluster analysis. The methods, Average linkage between group and Within-groups linkage, and distance-type measures Euclidean distance and Squared Euclidean distance were compared to verify the results of cluster analysis. The grouping of the stations has been used for the determination of the stops for categories intercity passenger trains. The main groups of stations for servicing express trains are the first, second, third, fourth and fifth groups. In the sixth group are stations for servicing fast passenger trains. The methodology can be applied to the study of all stations and stops in the rail network. [ABSTRACT FROM AUTHOR]

Oleiferous Brassica species are economically important agricultural commodities. India is one of the largest rapeseed-mustard growing countries. Indian mustard (Brassica juncea) is predominantly grown oilseed crop of India, where it is widely cultivated under diverse agro-climatic situations. As a consequence of breeding research over a century in this crop, many varieties have been bred, however little information is available about extent of variability and diversity among these varieties. Variability for 18 agro-morphological traits and for 6 computed variables was estimated in 62 extant varieties. Multivariate analyses based upon principal components and hierarchical cluster revealed 4 distinct groups of varieties based upon geographical region of their originating centers. Much of the variability could be accounted for leaf and stem characteristics and phenological stages. Closely resembling as well as distinct varieties were identified. Varieties from different clusters based upon genetic distance were suggested for utilization in hybridization program. [ABSTRACT FROM AUTHOR]

There are many genotypes and varieties in the citrus family. Currently, citrus classification systems have significant divergences in varieties of species, and subgenus classification as well. In this study, near-infrared spectroscopy technique was used to acquire spectral information on the surface of citrus fruits. Cluster analysis was consequently conducted to identify citrus genotypes. Results indicated that the combination of 9-point moving average smoothing and multiplicative scattering correction was optimal for preprocessing spectral data. In the spectral range of 1,180-1,220 nm, the cumulative reliability of the first two principal components were greater than 99.4%, and sweet oranges were clustered into an independent class. In 1,280-1,320 nm, systematic clustering performed better than principal component clustering, and all other sour oranges, except Goutoucheng, were clustered into a single clade. With dimensions reduction, the cumulative reliability of first five principle components in full band of 1,000-2,350nm reached up to 99.1%. Using principal component cluster analysis, pomelo and loose-skin mandarin were clustered together; sweet and sour oranges were clearly separated. Pomelo being clustered with loose-skin mandarin, implies that they may have a hybrid origin; Jiaogan Mandarin, Daoxian yeju Mandarin, Goutoucheng sour oranges, and Zhuhongju sour tangerine were clustered with sweet orange, which implies old varieties may contain similar characteristic matters as sweet orange; Given that Jinlong lemon and Ranpour lime were clustered with sour orange, they were proved to originated from sour orange. The study indicates the great potential of spectral analysis for citrus genotype identification and classification. [ABSTRACT FROM AUTHOR]