Comparison of abnormalities in the sequence of growth stages in the skeletal maturity index vs cervical vertebral maturation: A retrospective study

ABSTRACT Objectives To evaluate the frequency of abnormal progression that could ultimately affect the reliability of the skeletal maturity index (SMI) and the cervical vertebral maturation (CVM) method that are most commonly used analyses for skeletal age assessment. Materials and Methods A retrospective design was used to compare 299 hand-wrist radiographs with 299 lateral skull radiographs regarding the number of abnormalities in the proposed sequence of maturation in the SMI and CVM methods. Results A significantly greater number of abnormalities occurred in the sequence of CVM progression compared with SMI (P < .001). Sex and age did not have an effect. Conclusions Skeletal age assessment based on SMI is more accurate than CVM regarding the progressive sequence of stages.

Evaluation of Neoproterozoic Source Rock Potential in SE Pakistan and Adjacent Bikaner- Nagaur Basin India Based on Integrated Geochemical, Geological, and Geophysical Data

Discoveries of heavy crude oil in the Neoproterozoic rocks (Infracambrian rock sequence) from the Bikaner-Nagaur Basin of India emphasizes the significance to study and explore the Neoproterozoic source rocks potential in the southeastern part of Pakistan. This study evaluates the potential of the source rock in the Infracambrian rock sequence (Salt Range Formation) based on surface geochemical surveys, Rock-Eval pyrolysis, source biomarkers, geophysical characterization, and seismic inversion using machine learning for maturity index estimation. Core samples of Infracambrian rock were extracted for Rock-Eval pyrolysis and biomarker characterization. Also, 81 geo-microbial soil and gas samples were collected from the surface to explore the petroleum system and potential source rocks in the subsurface. We followed the standard laboratory procedures to investigate the origin and concentration of hydrocarbons gases at the surface, thermal maturity, the source facies, and the environment of deposition of organic matter. The results show that the investigated samples are characterized by restricted marine clay devoid of carbonate source facies with thermal maturity in the early-stage of the oil generation window. Surface geochemical samples also confirm higher concentrations of thermogenic C2-C4 hydrocarbons over the vicinity of anticlinal structures proving the existence of an effective migration path along deep-seated faults to the surface. The inverted maturity index profile demonstrates a reasonable correlation of thermal maturity with the surface geochemical survey, source biomarkers, and Rock-Eval pyrolysis. It validates the reliability of multilayer linear calculator and particle swarm optimization algorithms for inverting seismic reflection data into a maturity index profile. The obtained results indicate a higher probability of heavy and light oil along the eastern flank of Pakistan, where Infracambrian rocks are thicker and more thermally mature, and deep-seated pledged structural closures occur, in comparison to the Bikaner-Nagaur Basin, India.

Classification of large green chilli maturity using deep learning

Chili (Capsicum annuum L.) is the source of various nutraceutical small molecules, such as ascorbic acid (vitamin C), carotenoids, tocopherols, flavonoids, and capsinoids. The purpose of this study was to classify the maturity stage of large green chili into three maturity levels, i.e. maturity 1 (maturity index 1 / 34 days after anthesis (DAA)), maturity 2 (maturity index 3 / 47 DAA), and maturity 3 (maturity index 5 / 60 DAA) by using convolutional neural networks (CNN) based deep learning and computer vision. Four types of pre-trained networks CNN were used in this study i.e. SqueezeNet, GoogLeNet, ResNet50, and AlexNet. From the overall sensitivity analysis results, the highest maturity classification accuracy of large green chili was 93.89% which can be achieved when using GoogLeNet with SGDmoptimizer and learning rate of 0.00005. However, in further testing using testing-set data, the highest classification accuracy based on confusion matrix was reaching 91.27% when using the CNN SqueezeNet model with RMSProp optimizer and a learning rate of 0.0001. The combination of the CNN model and the low-cost digital commercial camera can later be used to detect the maturity of large green chili with the advantages of being non-destructive, rapid, accurate, low-cost, and real-time.

COMPARATIVE EVALUATION OF DIVERSITY AND HOMOGENEITY OF WEED COMMUNITIES OF WHEAT CROP IN TEHSIL RAZAR DISTRICT SWABI, PAKISTAN

The present study explains comparative evaluation of diversity and degree of homogeneity of weed communities of wheat crop using different indices. This study was conducted in tehsil Razar District Swabi Khyber Pakhtunkhwa, Pakistan during February-April 2016. A total of 200 quadrats having size (1x1 m2) were placed in 20 randomly selected wheat fields in the study area. Analytical quantitative characters like density, frequency and cover were calculated for each weed species. Twenty weed communities were established in 20 selected sites. Comparative evaluation of diversity revealed that Menhinick index ranged from 0.61 to 1.72, Margalef richness ranged from 2.82 to 6.3, Simpson diversity index ranged from 0.78 to 0.94, Shannon-Wiener diversity index varied from 2.13 to 3.24, Pielou evenness index varied from 0.67 to 0.97 while Pichi-Sermolli maturity index ranged from 39.6 to 67.7. Based on Raunkiaer’s law of frequency, out of 20 weed communities, 13 communities were found heterogeneous while 7 were homogeneous. Maximum number of weed species were distributed in frequency class A, B and E.

Effects of maturity indices and modified atmosphere packaging (MAP) on shelf life and post-harvest quality of cherry tomato

The present experiment was carried out at the Laboratories of the Department of Horticulture and Biochemistry and Molecular Biology, Bangladesh Agricultural University, Mymensingh during the period from February to April 2019 to study the effect of maturity indices and modified atmosphere packaging (MAP) on the extension of shelf life and quality retention of cherry tomato. The two-factor experiment consisted of three maturity indices viz. (i) Maturity index 1 (M1: Mature green color), (ii) Maturity index 2 (M2: Yellow color), and (iii) Maturity index 3 (M3: Red color) and five postharvest treatments viz. (i) Control (T0), (ii) Low density perforated poly ethylene, LDPPE (T1), (iii) Low density poly ethylene, LDPE (T2), (iv) Low density perforated plastic box, LDPPB (T3), and (v) Low density plastic box, LDPB (T4). The experiment was conducted in completely randomized design with 3 replications. The maximum weight loss (7.77%) was recorded in mature green color fruits (M2) treated with control (T0), while the minimum (3.22) was found in yellow color fruits (M2) treated with LDPPB (T3). The maximum color change was observed from yellow color fruits (M2) with LDPPB (T3) and the minimum was observed from mature green color fruits (M1) treated with control (T0). The maximum TSS content (7.20%) was recorded from yellow color fruits (M2) treated with LDPB (T4), while the minimum (5.67%) was found in mature green color fruits (M1) treated with LDPPB (T3). The highest disease incidence and severity (16.67% and 21.67%, respectively) were recorded in red color fruits (M3) treated with control whereas the lowest disease incidence (1.67%) and severity (2.33%) were found in yellow color fruits (M2) treated with LDPPB. The longest shelf life (25.00 days) was obtained in yellow color fruits (M2) treated with LDPPB (T3) and the shortest shelf life (7.00 days) was observed in red color fruits (M3) treated with control (T0). Thus, yellow color fruits (M2) treated with LDPPB (T3) could be used for the extension of shelf life and quality retention of cherry tomato. Progressive Agriculture 32 (1): 43-59, 2021