Stepwise Discriminant Function Analysis Research Articles

Utility of the metatarsal diaphyseal nutrient foramen in estimating sex in the South African Africans population

IntroductionSex estimation is challenging in cases where dismembered or non-intact skeletal remains are recovered. Therefore, the development of sex estimation standards using various bones that present with high recovery rates during forensic investigations, like the metatarsal bones, is needed. The usefulness of the dimensions around the metatarsal diaphyseal nutrient foramen in sex estimation has not been assessed in South African Africans (SAA), constituting the majority of the country's population. Materials and methodsFive measurements around the nutrient foramen were taken from 995 metatarsal bones (first to fifth) from 200 individual skeletons (100 males, 100 females). Measurements subjected to direct and stepwise discriminant function (DFA) and logistic regression (LRA) analyses included the total length, distance from proximal end to nutrient foramen, circumference, and mediolateral and dorsoplantar diameters at the level of the nutrient foramen. ResultsThe original classification accuracies for multivariable functions of the stepwise and direct DFA ranged from 75.1 to 80 % and 76–79.5 % respectively. The original classification accuracies for multivariable functions of the stepwise and direct LRA ranged from 76.3% to 79.5 % and 75%–80.5 % respectively. The cross-validation classifications showed a drop of 0–2% for DFA and 0.2–1.9 % for LRA. Overall breadth measurements showed better classification accuracies than length measurements and females were classified with higher accuracy rates than males. ConclusionThe dimensions around the nutrient foramen of the metatarsal bones show sexual dimorphism in the SAA. The generated DFA and LRA functions produced high average classification accuracies which can be appropriate for use in sex estimation in forensic settings, especially when an isolated foot is recovered.

Assessing the reliability and accuracy of sex estimation models utilizing sternal morphometry derived from computed tomography in the Ghanaian population

Sex estimation models are specific to populations and cannot be generalized due to genetic and environmental variabilities. This retrospective cross-sectional study, conducted between January and September 2023 at the Tamale Teaching Hospital, included 119 (50.9 %) females and 115 (49.1 %) males aged 23–82 years. Measurements, including manubrium length (M), manubrium width (MW), sternal body length (B), combined manubrium and sternal body lengths (CL), corpus sterni width at first sternebrae (CSWS1), and corpus sterni width at third sternebrae (CSWS3), were obtained from Computerized Tomographic (CT) images of the sternum using DICOM Viewer, accurate to 0.1 cm. Subsequently, sternal area (SA) and sternal index (SI) were calculated. Univariable and stepwise multivariable discriminant function analysis (DFA) and logistic regression (LR) models were developed using a training sample (70 %), and cross-validation was performed on a holdout sample (30 %). Results showed that the linear measurements, excluding M, and sternal area were higher in males than females (P<0.001), while the sternal index was <50 % in males but >50 % in females (P<0.001). Univariable sex estimation accuracies, in cross-validation, ranged from 43.7 % to 92.9 % in DFA and 50.0–92.9 % in LR. For multivariable models, the accuracy ranges were 92.9–94.3 % in DFA and 91.6–93.0 % in LR. The sternal body length was the most accurate at 90.1 % in DFA and 90.2 % in LR, with lower sex bias (male-female) in LR than in DFA (-0.1 vs. 8.7). The sternum proves valuable for sex estimation, with sternal body length as the most accurate linear measurement. However, multivariable models, particularly LR, demonstrate higher accuracy compared to DFA.

“Back to Braak”: Role of Nucleus Reuniens and Subcortical Pathways in Alzheimer’s Disease Progression

BackgroundPatients with Alzheimer’s Disease (AD) exhibit structural alterations of the thalamus that correlate with clinical symptoms. However, given the anatomical complexity of this brain structure, it is still unclear whether atrophy affects specific thalamic nuclei and modulates the clinical progression from a prodromal stage, known as Mild Cognitive Impairment (MCI), to full-fledged AD.ObjectivesTo characterize the structural integrity of distinct thalamic nuclei across the AD spectrum, testing whether MCI patients who convert to AD (c-MCI) show a distinctive pattern of thalamic structural alterations compared to patients who remain stable (s-MCI).DesignInvestigating between-group differences in the volumetric features of distinct thalamic nuclei across the AD spectrum.SettingProdromal and clinical stages of AD.ParticipantsWe analyzed data from 84 healthy control subjects (HC), 58 individuals with MCI, and 102 AD patients. The dataset was obtained from the AD Neuroimaging Initiative (ADNI-3) database. The MCI group was further divided into two subgroups depending on whether patients remained stable (s-MCI, n=22) or progressed to AD (s-MCI, n=36) in the 48 months following the diagnosis.MeasurementsA multivariate analysis of variance (MANOVA) assessed group differences in the volumetric features of distinct thalamic nuclei obtained from magnetic resonance (MR) images. A stepwise discriminant function analysis identified which feature most effectively predicted the conversion to AD. The corresponding predictive performance was evaluated through a Receiver Operating Characteristic approach.ResultsAD and c-MCI patients showed generalized atrophy of thalamic nuclei compared to HC. In contrast, no significant structural differences were observed between s-MCI and HC subjects. Compared to s-MCI, c-MCI individuals displayed significant atrophy of the nucleus reuniens and a trend toward significant atrophy in the anteroventral and laterodorsal nuclei. The discriminant function analysis confirmed the nucleus reuniens as a significant predictor of AD conversion, with a sensitivity of 0.73 and a specificity of 0.69.ConclusionsIn line with the pathophysiological relevance of the nucleus reuniens proposed by seminal post-mortem studies on patients with AD, we confirm the pivotal role of this nucleus as a critical hub in the clinical progression to AD. We also propose a theoretical model to explain the evolving dysfunction of subcortical brain networks in the disease process.

Evaluation of Foramen Magnum for Sex Determination among the Population of Dakshina Kannada District: A Retrospective CBCT Study.

This study aims to evaluate the accuracy rate of foramen magnum dimensions in determining sex among the South Indian population using discriminant functional analysis. An observational study in which CBCT images from 200 full field of view (FOV) scans were analysed. The dimensions of the foramen magnum were measured. Intra- and interobserver reliability were calculated. Independent t-tests were used to compare the various parameters between sexes. Stepwise discriminant function analysis was used to determine sex. A total of 200 CBCT scans were included in the study. The mean age (±SD) was 25.66 (±7.11) years among males and 24.64 (±5.12) years among females. The measurements and the circumference of the foramen magnum were significantly (p < 0.001) greater in males than in females. The univariate analysis of foramen magnum measurements reached an accuracy rate of 73.5% in sex determination. The discriminant function analysis combining the foramen magnum measurements and circumference yielded an overall predictability rate of 66.5% for determining sex. Taking into account the predictability rate of sex based on foramen measurement in the present population, it can be concluded that its applicability should be limited to cases associated with fragmentary skull bases.

Attitudes of Latino Students Toward High School Physical Education

ABSTRACT The attitudes physical education students have about the subject influences their level of engagement in and out of class as well as their overall physical activity, which impacts their health and well-being. This study examined the attitudes of Latino high school students toward physical education, specifically to understand how their attitudes were associated with their English comprehension, gender, age, ethnic heritage, and place of birth. The Student Attitude toward Physical Education instrument was administered to participants to measure their attitudes. Data were analyzed using multivariate analysis of variance (MANOVA), stepwise discriminant function analysis (DFA), and analysis of variance (ANOVA). Latino high school students (n = 1003) from public schools in a large city participated. Enjoyment curriculum and total enjoyment were the main predictors of attitude, and they varied significantly by ESL class enrollment, place of birth, and primary home language. The results indicate that these variables may interact with attitude.

Evaluating the patella bone for sex estimation in Northwest Indian subjects: A radiological study

ObjectivesIn forensic identification, pelvis, post cranial bones especially long bones and skull are considered best for sex estimation. But there are circumstances where these bones cannot be recovered for establishing the correct biological profile of unknown human skeletal remains. In those cases, other skeletal bones should be investigated for sex estimation. The goal of the present study was to validate whether the patellar bone measurements through CT scan can be used for the sex estimation in Northwest Indian subjects. Materials and methodsThis study comprises of 344 subjects (179 males and 165 females) between the age group of 18- 80 years. Eight variables of patella were selected in the study for sex estimation using CT scan images of patella. ResultsAll the variables were statistically significant with p-value< 0.05 for indicating the sex. Univariate and multivariate discriminant function analysis (direct and stepwise method) were applied for sex estimation. The overall accuracy rate of classifying sex was 88.4% for multivariate stepwise discriminant function analysis and 87.8% for multivariate direct discriminant function analysis. Total perimeter of patella (TPP) was found to be the best variable for sex estimation with overall accuracy rate of 84.9%. ConclusionThe present study emphasized on the most dimorphic variables of patella in Northwest Indian subjects. New variables of patella namely Patellar Femoral Distance (PFD), Patellar Apex Angle (PAA), Frontal Surface Area of patella (FSA) and Total Perimeter of Patella (TPP) were added in the study of Indian subjects. This brought an overall accuracy rate of classification above 85%. The study confirmed that patellar bone's linear and angular measurements can be used for forensic identification casework.

Sex Estimation From Measurements of the Mastoid Triangle and Volume of the Mastoid Air Cell System Using Classical and Machine Learning Methods: A Comparative Analysis.

Previous studies on the sexual dimorphism of the mastoid triangle have typically focused on linear and area measurements. No studies in the literature have used mastoid air cell system volume measurements for direct anthropological or forensic sex determination. The aims of this study were to investigate the applicability of mastoid air cell system volume measurements and mastoid triangle measurements separately and combined for sex estimation, and to determine the accuracy of sex estimation rates using machine learning algorithms and discriminant function analysis of these data. On 200 computed tomography images, the distances constituting the edges of the mastoid triangle were measured, and the area was calculated using these measurements. A region-growing algorithm was used to determine the volume of the mastoid air cell system. The univariate sex determination accuracy was calculated for all parameters. Stepwise discriminant function analysis was performed for sex estimation. Multiple machine learning methods have also been used. All measurements of the mastoid triangle and volumes of the mastoid air cell system were higher in males than in females. The accurate sex estimation rate was determined to be 79.5% using stepwise discriminant function analysis and 88.5% using machine learning methods.

Canine Crown Sexual Dimorphism in a Sample of the Modern Croatian Population.

Sex assessment is a key part of forensic analysis to establish the identity of unknown deceased individuals. Previous studies have shown that canines are the most dimorphic teeth, but population-specific data are necessary for forensic methods. This study explores sex dimorphism in canine crown dimensions and morphology in a contemporary Croatian population. The material consisted of 302 dental casts (147 females, 155 males) of orthodontic patients and dental students (11-25 years). The distal accessory ridge (DAR) of the upper and lower canines was evaluated using the Arizona State University Dental Anthropology System. Mesiodistal (MD) and buccolingual (BL) crown dimensions were measured on 120 casts. Sex differences in MD and BL dimensions were significant (p < 0.05) for all the canines (upper and lower, left and right), while in DAR only for lower canines (p < 0.000001). When all variables were put into the model, backward stepwise discriminant function analysis isolated lower canine DAR and lower left canine MD as the two independent variables differentiating sex. Using these two variables, a discriminant function formula allowed for sex determination with an accuracy of 73.5%. This study shows that both canine crown morphology and dimensions are useful for sex determination, especially for lower canines. These methods can be applied to children, as lower canines erupt at about 9 years of age.

Otolith shape and elemental signatures provide insights into the connectivity of euryhaline Chelon labrosus inhabiting two close estuaries with different burdens of xenoestrogens in the Southern Bay of Biscay

Intersex gonads have been observed in thicklip grey mullet Chelon labrosus, inhabiting estuaries with high burdens of xenoestrogens in the Southeast Bay of Biscay, but knowledge of population connectivity among estuaries is lacking for this euryhaline fish species. This study investigates the population structure of C. labrosus using otolith shape and elemental signatures of 60 adults (overall length ∼ 38 cm) from two estuaries 21 nautic miles apart, one with a high incidence of intersex condition (Gernika), and the other one pristine (Plentzia). Otolith shape analyses were performed using elliptical Fourier descriptors, while elemental signatures of whole sagittae were obtained by inductively coupled plasma mass spectrophotometry. Univariate and multivariate statistics were applied to determine if otolith signatures show patterns of homogeneity between estuaries. The data indicated significant differences in the otolith shape and elemental composition between mullets of Gernika and Plentzia. Elemental differences were mainly driven by Sr, Li (both higher in Plentzia) and Ba (higher in Gernika). The 98% re-classification success rate obtained from stepwise linear discriminant function analysis suggests that Gernika and Plentzia individuals form separated population units. The limited connectivity between these two close estuaries would indicate a different life history of exposure to chemicals, which might explain the high prevalence of intersex condition in Gernika and its absence in Plenztia.

Cranio-facial bones evaluation based on clinical CT data for sex determination in Northwest Indian population

The skull and pelvis have been the first choice of bones for determination of unknown human remains. The goal of the present study was to derive discriminant function equations by using clinical CT scan data of cranio-facial bones for sex determination in Northwest Indian population. This study was conducted at Department of Radiology, by collecting the retrospective data of CT scan of 217 samples. In the data, 106 were males and 111 were females in the age group between 20 and 80 years. The total number of parameters under investigation were 10. All the selected variables were sexually dimorphic and showed significant values. 91.7% of original grouped cases were correctly classified to their sex category. The TEM, rTEM and R were under the acceptable limits. The univariate, multivariate and stepwise discriminant function analysis recorded an accuracy of 88.9%, 91.7% and 93.6% respectively. Multivariate direct discriminant function analysis stepwise method yielded the highest level of accuracy in differentiating males and females. All the variables reflected statistically significant difference between males and females (p less than 0.001). The best single parameter with highest level of sexual dimorphic trait was length of cranial base. This study aims to provide sex assessment using clinical data of CT scan in Northwest Indian population by incorporating the BIOFB cranio-facial parameter. The morphometric measurements taken on CT scan images can be utilized by forensic experts in identification process.

Gender Determination in Pakhtun Pakistani Population Using Dental Arch Dimensions: A Digital Model Study

Introduction: In circumstances where the ante mortem list is unknown, gender determination would exclude one-half of the population, aid in a more precise search of the ante mortem records. This study aims to formulate gender prediction models in the Pakhtun Pakistani population using digital dental arch dimensions. Methods: Data collection and analysis of the dental casts were conducted on 128 subjects, 64 males and 64 females from the Pakistani population. The mean age of the subjects was 19.2 years old. Several linear dental arch dimensions were measured and recorded for both upper and lower arches. Results: It was found that gender differences in linear arch dimensions were statistically significant for both males and females (p&lt;0.05); in which the arch dimensions for the males were larger than the arch dimensions for the females. Stepwise discriminant function analysis found that the highest discriminant power of the variables was present within the inter-second premolar width for the upper arch and inter-molar width for the lower arch. These variables significantly contributed to gender variance. Moreover, the prediction of 67.2% of original grouped cases for the upper arch and 66.4% of cross-validated group cases was correct. Similarly, the correct prediction was made on 64.8% of original grouped cases for the lower arch and 64.1% of cross-validated group cases. Conclusion: The dental arch dimensions were larger among the males compared to the females. Prediction models obtained in this study were moderately strong predictors which may be used as an adjunct to predict gender.

TAASSC 프로그램을 활용하여 원어민과 한국인 대학생이 작성한 에세이에 나타난 명사구 복잡성의 특징 비교

This study investigates how syntactic features can be used to distinguish essays written by Korean college students from NS college students. Essays from the ICNALE(International Corpus Network of Asian Learners of English) corpus were analyzed using TAASSC(the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity) program. Two statistical analyses were performed. First, a multivariate analysis of variance(MANOVA) was employed to examine whether there are statistically significant differences in noun phrase complexity features between NS and Korean students. Second, a stepwise discriminant function analysis was performed to classify into two groups(i.e., NS and Korean students) in terms of noun phrase complexity features. Results showed that Korean and NS students significantly differed in terms of various noun phrase complexity indices. The best four predictors for distinguishing Korean students’ essays from NS students’ essays were dependents per object of the preposition, relative clause modifier per nominal, prepositions per object of the preposition, and dependents per nominal. It was shown that NS students produced more syntactically complex essays than Korean students by employing phrasal embedding. Implications of this study for English writing instruction are discussed.

The soundscape of swarming: Proof of concept for a noninvasive acoustic species identification of swarming Myotis bats.

Bats emit echolocation calls to orientate in their predominantly dark environment. Recording of species-specific calls can facilitate species identification, especially when mist netting is not feasible. However, some taxa, such as Myotis bats can be hard to distinguish acoustically. In crowded situations where calls of many individuals overlap, the subtle differences between species are additionally attenuated. Here, we sought to noninvasively study the phenology of Myotis bats during autumn swarming at a prominent hibernaculum. To do so, we recorded sequences of overlapping echolocation calls (N= 564) during nights of high swarming activity and extracted spectral parameters (peak frequency, start frequency, spectral centroid) and linear frequency cepstral coefficients (LFCCs), which additionally encompass the timbre (vocal "color") of calls. We used this parameter combination in a stepwise discriminant function analysis (DFA) to classify the call sequences to species level. A set of previously identified call sequences of single flying Myotis daubentonii and Myotis nattereri, the most common species at our study site, functioned as a training set for the DFA. 90.2% of the call sequences could be assigned to either M. daubentonii or M. nattereri, indicating the predominantly swarming species at the time of recording. We verified our results by correctly classifying the second set of previously identified call sequences with an accuracy of 100%. In addition, our acoustic species classification corresponds well to the existing knowledge on swarming phenology at the hibernaculum. Moreover, we successfully classified call sequences from a different hibernaculum to species level and verified our classification results by capturing swarming bats while we recorded them. Our findings provide a proof of concept for a new noninvasive acoustic monitoring technique that analyses "swarming soundscapes" by combining classical acoustic parameters and LFCCs, instead of analyzing single calls. Our approach for species identification is especially beneficial in situations with multiple calling individuals, such as autumn swarming.

Machine learning and discriminant function analysis in the formulation of generic models for sex prediction using patella measurements

Sex prediction from bone measurements that display sexual dimorphism is one of the most important aspects of forensic anthropology. Some bones like the skull and pelvis display distinct morphological traits that are based on shape. These morphological traits which are sexually dimorphic across different population groups have been shown to provide an acceptably high degree of accuracy in the prediction of sex. A sample of 100 patella of Mixed Ancestry South Africans (MASA) was collected from the Dart collection. Six parameters: maximum height (maxh), maximum breadth (maxw), maximum thickness (maxt), the height of articular facet (haf), lateral articular facet breadth (lafb), and medial articular facet breath (mafb) were used in this study. Stepwise and direct discriminant function analyses were performed for measurements that exhibited significant differences between male and female mean measurements, and the “leave-one-out” approach was used for validation. Moreover, we have used eight classical machine learning techniques along with feature ranking techniques to identify the best feature combinations for sex prediction. A stacking machine learning technique was trained and validated to classify the sex of the subject. Here, we have used the top performing three ML classifiers as base learners and the predictions of these models were used as inputs to different machine learning classifiers as meta learners to make the final decision. The measurements of the patella of South Africans are sexually dimorphic and this observation is consistent with previous studies on the patella of different countries. The range of average accuracies obtained for pooled multivariate discriminant function equations is 81.9–84.2%, while the stacking ML technique provides 90.8% accuracy which compares well with those presented for previous studies in other parts of the world. In conclusion, the models proposed in this study from measurements of the patella of different population groups in South Africa are useful resent with reasonably high average accuracies.

Decoupling between circulation pattern and dust path since the last glacial in the Songnen Plain, NE China: Insights from quantitative provenance reconstruction of the Harbin dust sediments

• Potential sources of the Harbin loess during the last glacial and modern dust were quantitatively tracked. • The sandy lands of NE China figure importantly in acting as a dust transfer station. • Decoupling between circulation patterns and dust export since the last glacial in the Songnen Plain were revealed. • The SW-direction sandy land of the Songnen Plain should be treated as a priority for environmental management. Knowledge of the provenance of dust deposits in the easternmost margin of the Eurasian loess belt is essential for understanding the connection between circulation patterns and dust source-to-sink route in the Songnen Plain, NE China. Here, a total of 131 samples, from the loess-paleosol sequence since the last glacial (20) and the modern dust-storm sediments (7) in Harbin area together with potential dust source areas (104), were collected for elemental geochemical analysis to quantify the source apportionment and compare the performance of the Frequentist and Bayesian models. Fourteen geochemical properties (V, Zn, Ga, Sr, Mo, Ba, Pb, Y/Ta, MREE N /MREE N *, Th/Sc, Th/U, La/Sc, Zr/Hf and Co/Th) were selected as the optimum composite fingerprint after a range test, non-parametric Kruskal-Wallis H-test and stepwise discriminant function analysis. Based on both the models, the source contributions to the loess sequence and dust-storm deposits were in the following order: southwestern Songnen Sandy Land (57–95%, 49–97%), Horqin Sandy Land and Onqin Daga Sandy Land (2–43%, 0–31%), northwestern Songnen Sandy Land (0–21%, 0–20%) and Hulun Buir Sandy Land (0%, 0–8%). Following the goodness-of-fit and virtual mixtures, combined with root mean square error and mean absolute error, we argue that the Frequentist model is slightly more accurate than the Bayesian model in quantifying dust sources. The sandy lands figure importantly in acting as a dust transfer station. The comparison between the loess sequence and modern dust-storm source reconstructions reveals a decoupling between circulation pattern (northwesterly wind domination in the glacial) and dust path (dominantly southwestern direction), and small areas, high vegetation coverage and topographical barrier are considered to be the main reasons for the significantly limited dust emission in the NW-direction source area. Finally, the study highlights that improving land management practices in the SW-direction but not NW-direction sandy land may help ameliorate the effects of the Harbin dust pollution.

Sex Estimation From Histomorphometric Analysis of Cortical Bone: A Hospital-based Study

Estimation of the sex of unknown skeletal remains is a daunting challenge, when only fragmented bones are available. For this reason, there is a need to study population specific histomorphometric features of bones to provide useful data for the process of identification. The purpose of this study was to estimate sex from six histomorphometric parameters of cortical bones in a cohort of Nigerian patients. The samples comprised non-pathologic bones collected from 29 patients (12 females and 17 males) between the ages of 35 to 85 years during orthopaedic procedures. The modified Frost’s manual method was used to prepare the histological sections of the cortical bones. The parameters evaluated were number of primary osteons (Os-p), number of secondary osteons (Os-s), osteon fragments (Os-f), non-Haversian canal (N-Hc), area of Haversian canal (Area Hc), and Haversian canal diameter (HCD). The data obtained were analyzed using SPSS version 23.0. Tests for sex differences were done using student t-test and stepwise discriminant function was used to formulate a predictive model for sex estimation. The mean Os-p, Os-s, Os-f, N-hc, Area HC, and HCD were 2.85 ± 0.86,3.92 ± 1.26,6.08 ± 1.37, 2.23 ± 0.66, 53.43 ± 5.55, and 7.85 ± 0.41 for males and 1.11 ± 0.56, 0.33 ± 0.17, 2.44 ± 0.67, 54.37 ± 6.04 and 7.426 ± 0.35 for females, respectively. The mean value of Os-s was significantly different in males and females (p=0.04). Stepwise discriminant function analysis showed Os-s could be used to estimate sex. 71.4% of our samples were correctly predicted based on sex. Discriminant function values of 0.418 and -0.626 were predictive values for males and females, respectively, using the DFA predictive model. Our study shows that the number of secondary osteons (Os-s) could be used to estimate sex in Nigerian patients.

Evaluation of Aus rice genotypes grown under rainfed and irrigated conditions

Bangladesh must keep increasing the production of rice (Oryza sativa L.), which is consumed by more than half of the world's population in order to ensure a steady supply of food for everyone. A field experiment was conducted to select short durated with high yield potential Aus rice genotypes under rainfed condition in a split plot design with three replications. Two water regimes (irrigated and rainfed) were imposed into main plot and 39 Aus rice genotypes were assigned into sub plots. In order to categorize the genotypes into various groups, multivariate studies including cluster analysis, principal component analysis (PCA), and discriminantfunction analysis (DFA) were carried out using fifteen quantitative plant traits. Results based on agronomic traits, the genotypes were grouped into six clusters. Early maturing genotypes are represented in cluster II, and genotypes with outstanding yield performance under irrigation are grouped in cluster III. Additionally, clusters III and IV indicate genotypes that mature quickly and a high yield potentiality under rainfed conditions, respectively. Biological yield played a very vital role under both irrigated and rainfed conditions. PCA revealed that PC 1, 2, 3, 4, and 5 described 84.90% variation under irrigated and 84.83% variation in rainfed condition, altogether. Stepwise DFA showed function 1 and 2 accounted for a cumulative of 95.40% of total variance in irrigated and of 92.3% variance in rainfed condition. BR24, Rupsail, Kachilon, Kachiloon2, Darial, Katak-Tara2, BRRI dhan43, Bowalia, BRRI dhan55 and BR14 showed the best performance under rainfed condition. The genotypes like Laksmilota, Loroi, Dhala Saita-3 and Kala manik can be used for further study as early maturing genotypes. Ann. Bangladesh Agric. (2022) 26 (1) : 91-111

Phenotypic characterization of Gesha horses in southwestern Ethiopia

Fifteen qualitative and 21 morphometric variables on a total of 394 adult horses (282 stallions and 112 mares) from three selected districts were recorded to characterize the horse populations in southwestern Ethiopia. General linear model, frequency, and multivariate analysis procedures of Statistical Analysis Software (SAS 9.0) were used to analyze the data. Sex and location significantly affected the studied traits. Stallions were larger than mares, and the Gesha horse population was the tallest, longest, and largest among the studied populations. The majority of the studied horses possess plain body colour patterns with red-coloured medium hair size. A higher frequency of white-coloured horses was observed with increasing age. Stepwise discriminant function analysis revealed that pelvic width, cannon bone length, and height at croup were the top three morphometric variables to discriminate the populations while head length, head neck circumference, chest width, cannon bone circumference, and croup length had the lowest discriminatory power. The results of discriminant function analysis showed advanced classification (76.7%) of the studied horses into their respective populations/locations. Finally, canonical discriminant function analysis categorized the horse populations into three distinct categories. The Gesha horse population was different from Masha and Telo horse populations while having a relatively higher relationship with the Masha horse population. However, the distances calculated in this study show only the relative size differences between each population. Such differences might not necessarily be due to breed (genetic) differences. Therefore, diversity studies through further genetic characterization are recommended to design conservation and breeding programmes.

Sex and Stature Estimation from Odontometric Parameters of Kalabari Ethnic Group in Rivers State, Nigeria

The resistance of the teeth to human and taphonomic factors has made it a choice for the identification of persons. The aim of this study is to estimate sex and stature from odontometric parameters of Kalabari ethnic group of Rivers State in Nigeria. The cross-sectional descriptive study involved 100 volunteers between the ages of 15 to 30 years (50 males and 50 females) whose parents and four grandparents were from Kalabri ethnic group. The parameters measured were the crown height (CH), maximum mesiodistal width (MD), buccolingual dimension (BL) of the right maxillary and mandibular incisors, canines, and premolars. The heights (HT) of the volunteers were also measured. Discriminant function analysis was used to design a predictive model for sex and Multivariate Regression Analysis was used to design a predictive model for stature. The results showed that the mean values of all teeth variables were larger in males than in females except buccolingual dimensions of second maxillary incisor (BL2) and crown height of first maxillary premolar (CH4). Discriminant Function Analysis of all measured parameters showed the score that predicts male is 1.067 while -1.067 for female. Stepwise Discriminant Function Analysis showed maxillary canine to be the best predictor of sex followed by mandibular incisor. Predictive model for sex identification was derived. Multivariate regression analysis was used to derive equation for stature estimation. This study showed that the combination of the teeth could be used for sex and stature estimation.

Fingerprinting the spatial sources of fine-grained sediment deposited in the bed of the Mehran River, southern Iran

Accurate information on the sources of suspended sediment in riverine systems is essential to target mitigation. Accordingly, we applied a generalized likelihood uncertainty estimation (GLUE) framework for quantifying contributions from three sub-basin spatial sediment sources in the Mehran River catchment draining into the Persian Gulf, Hormozgan province, southern Iran. A total of 28 sediment samples were collected from the three sub-basin sources and six from the overall outlet. 43 geochemical elements (e.g., major, trace and rare earth elements) were measured in the samples. Four different combinations of statistical tests comprising: (1) traditional range test (TRT), Kruskal–Wallis (KW) H-test and stepwise discriminant function analysis (DFA) (TRT + KW + DFA); (2) traditional range test using mean values (RTM) and two additional tests (RTM + KW + DFA); (3) TRT + KW + PCA (principle component analysis), and; 4) RTM + KW + PCA, were used to the spatial sediment source discrimination. Tracer bi-plots were used as an additional step to assess the tracers selected in the different final composite signatures for source discrimination. The predictions of spatial source contributions generated by GLUE were assessed using statistical tests and virtual sample mixtures. On this basis, TRT + KW + DFA and RTM + KW + DFA yielded the best source discrimination and the tracers in these composite signatures were shown by the biplots to be broadly conservative during transportation from source to sink. Using these final two composite signatures, the estimated mean contributions for the western, central and eastern sub-basins, respectively, ranged between 10–60% (overall mean contribution 36%), 0.3–16% (overall mean contribution 6%) and 38–77% (overall mean contribution 58%). In comparison, the final tracers selected using TRT + KW + PCA generated respective corresponding contributions of 1–42% (overall mean 20%), 0.5–30% (overall mean 12%) and 55–84% (overall mean 68%) compared with 17–69% (overall mean 41%), 0.2–12% (overall mean 5%) and 29–76% (overall mean 54%) using the final tracers selected by RTM + KW + PCA. Based on the mean absolute fit (MAF; ≥ 95% for all target sediment samples) and goodness-of-fit (GOF; ≥ 99% for all samples), GLUE with the final tracers selected using TRT + KW + PCA performed slightly better than GLUE with the final signatures selected by the three other combinations of statistical tests. Based on the virtual mixture tests, however, predictions provided by GLUE with the final tracers selected using TRT + KW + DFA and RTM + KW + DFA (mean MAE = 11% and mean RMSE = 13%) performed marginally better than GLUE with RTM + KW + PCA (mean MAE = 14% and mean RMSE = 16%) and GLUE with TRT + KW + PCA (mean MAE = 17% and mean RMSE = 19%). The estimated source proportions can help watershed engineers plan the targeting of conservation programmes for soil and water resources.