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Salinity stress is one of the primary threats to agricultural crops resulting in impaired crop growth and development. Although cotton is considered as reasonably salt tolerant, it is sensitive to salt stress at some critical stages like germination, flowering, boll formation, resulting in reduced biomass and fiber production. The mechanism of partial ion exclusion (exclusion of Na + and/or Cl – ) in cotton appears to be responsible for the pattern of uptake and accumulation of harmful ions (Na + and Cl) in tissues of plants exposed to saline conditions. Maintaining high tissue K + /Na + and Ca 2+ /Na + ratios has been proposed as a key selection factor for salt tolerance in cotton. The key adaptation mechanism in cotton under salt stress is excessive sodium exclusion or compartmentation. Among the cultivated species of cotton, Egyptian cotton ( Gossypium barbadense L.) exhibit better salt tolerance with good fiber quality traits as compared to most cultivated cotton and it can be used to improve five quality traits and transfer salt tolerance into Upland or American cotton ( Gossypium hirsutum L.) by interspecific introgression. Cotton genetic studies on salt tolerance revealed that the majority of growth, yield, and fiber traits are genetically determined, and controlled by quantitative trait loci (QTLs). Molecular markers linked to genes or QTLs affecting key traits have been identified, and they could be utilized as an indirect selection criterion to enhance breeding efficiency through marker-assisted selection (MAS). Transfer of genes for compatible solute, which are an important aspect of ion compartmentation, into salt-sensitive species is, theoretically, a simple strategy to improve tolerance. The expression of particular stress-related genes is involved in plant adaptation to environmental stressors. As a result, enhancing tolerance to salt stress can be achieved by marker assisted selection added with modern gene editing tools can boost the breeding strategies that defend and uphold the structure and function of cellular components. The intent of this review was to recapitulate the advancements in salt screening methods, tolerant germplasm sources and their inheritance, biochemical, morpho-physiological, and molecular characteristics, transgenic approaches, and QTLs for salt tolerance in cotton.

Cotton is an important agro-industrial crop across the globe. Improving the fiber quality and yield potential of cotton are major commercial targets for cotton breeders. The cotton lint yield is computed by multiplying three fundamental yield constituents: average boll weight, boll number per unit ground area, and lint percentage. The cotton species Gossypium arboreum exhibits a wide range of desirable traits, which are absent in the congener Gossypium hirsutum. Four parental lines of G. hirsutum and G. arboreum, with significant differences in boll-related traits, were used to develop the following four F2 populations: Mei Zhongmian × Chimu Heizi (MC), Mei Zhongmian × L-02292-3 (ML), Dixie king × Suyuan 04-44 (DS), and Dixie king × Pamuk (DP), in order to study complex traits, such as boll weight (BW) (g), lint percentage (LP) (%), boll upper width (BUW), boll medium width (BMW), boll lower width (BLU), and boll length (BL) (mm). In segregation populations, extensive phenotypic differences and transgressive segregation were observed. The results show that most of the correlation clusters were negatively associated with boll weight and lint percentage. The positive correlation clusters were observed among boll upper width (BUW), boll medium width (BMW), boll lower width (BLW), and boll length (BL). Seven of the twenty-four extracted principal components had eigenvalues > 1. This accounted for 62.2% of the difference between the four F2 populations. Principal component 1 accounted for 15.1% of the overall variability. The variation in principal component 1 was mainly attributed to boll lower width (BLW), boll medium width (BMW), boll upper width (BUW), boll length (BL), and boll weight (BW) of the ML population. The heritability estimates varied between high, medium, and low for various traits among the studied F2 populations. Interestingly, all traits demonstrated low genetic advance, which indicates that non-additive genes controlled these characters and that direct selection for these traits is not beneficial. The outcome of the present investigation will help to develop cotton cultivars with improved boll weight and lint percentage.

Knowledge of genetic diversity is necessary for designing future breeding programs and deriving desired genotypes. The current study was designed to explore the genetic diversity between 37 coarse and basmati rice genotypes by using 15 agro-morphological traits and 35 SSR markers. Mahalanobis’ generalized distance (D 2 ) and principal component analysis (PCA) were used to evaluate the data for agronomical traits. Of the information in the raw data for the yield-related traits, 67.28% was represented by two principal components. Five different clusters were revealed by cluster analysis (D 2 ): Cluster I had up to 6 genotypes, followed by 17, 5, 8, and 1 genotypes in clusters II, III, IV, and V, respectively. Greater genetic diversity among the genotypes was signified by a greater inter-cluster than intra-cluster distance. The maximum inter-cluster distance was observed between clusters II and V (80.88). The highest (33.080) and lowest (12.745) intra-cluster distances were observed for Cluster IV and Cluster II, respectively. Tall-growing and long grain basmati genotypes were grouped into Cluster II, while Cluster IV contained all the coarse rice genotypes. The minimum intra-cluster distance (12.745) of Cluster II indicated a narrow genetic base for the basmati rice. Molecular-based exploration of genetic diversity produced genetic similarity coefficients and clustered the genotypes into two major clusters. The total number of polymorphic alleles was 69, with an average of 1.97 alleles per SSR locus. In this study, a maximum of 5 alleles were revealed by marker RM16. The highest and lowest polymorphic information content (PIC) values were observed for markers RM6 (0.92) and RM10 (0.36), respectively. The coefficient of genetic similarity ranged between 0.45 and 1 for all basmati and coarse rice genotypes. Two pairs of coarse rice genotypes, Nagina/RD25 and Nagina/SUB-1, showed maximum divergence (0.42), with a similarity index of 0.58 for both pairs. In contrast, the maximum divergence (0.18) between three pairs of basmati rice genotypes—EF52/sup-23 and Super basmati, Sup/1138-2 and Lpa-56-3, and Sup/1138-2 and Basmati515—had a similarity index of 0.82. The similarity coefficient ranges showed a narrower genetic base for basmati rice genotypes as compared to coarse rice genotypes. Clustering based on agronomic and molecular analysis showed the clear differentiation of coarse and basmati rice into different groups, except in a few lines—Lpa-66-3-1, KSK-133, Nagina, SUB-4, and Sup1138/2—which showed some deviation from the trend. The study of genetic differences concluded that the genotypes of Cluster II and Cluster V are complementary for maximum desirable traits and could be selected for use in hybridization programs to develop promising F 1 hybrids or transgressive segregants in subsequent generations.

Cotton is an important agro-industrial crop across the globe. Improving the fiber quality and yield potential of cotton are major commercial targets for cotton breeders. The cotton lint yield is computed by multiplying three fundamental yield constituents: average boll weight, boll number per unit ground area, and lint percentage. The cotton species Gossypium arboreum exhibits a wide range of desirable traits, which are absent in the congener Gossypium hirsutum. Four parental lines of G. hirsutum and G. arboreum, with significant differences in boll-related traits, were used to develop the following four F2 populations: Mei Zhongmian × Chimu Heizi (MC), Mei Zhongmian × L-02292-3 (ML), Dixie king × Suyuan 04-44 (DS), and Dixie king × Pamuk (DP), in order to study complex traits, such as boll weight (BW) (g), lint percentage (LP) (%), boll upper width (BUW), boll medium width (BMW), boll lower width (BLU), and boll length (BL) (mm). In segregation populations, extensive phenotypic differences and transgressive segregation were observed. The results show that most of the correlation clusters were negatively associated with boll weight and lint percentage. The positive correlation clusters were observed among boll upper width (BUW), boll medium width (BMW), boll lower width (BLW), and boll length (BL). Seven of the twenty-four extracted principal components had eigenvalues > 1. This accounted for 62.2% of the difference between the four F2 populations. Principal component 1 accounted for 15.1% of the overall variability. The variation in principal component 1 was mainly attributed to boll lower width (BLW), boll medium width (BMW), boll upper width (BUW), boll length (BL), and boll weight (BW) of the ML population. The heritability estimates varied between high, medium, and low for various traits among the studied F2 populations. Interestingly, all traits demonstrated low genetic advance, which indicates that non-additive genes controlled these characters and that direct selection for these traits is not beneficial. The outcome of the present investigation will help to develop cotton cultivars with improved boll weight and lint percentage.

The world's population has been increasing continuously, and this requires prompt action to ensure food security. One of the top five cereals produced worldwide, sorghum, is a staple of the diets of many developing nations. For this reason,getting accurate information is crucial to raising cereal productivity. The quantity of crop heads arranged in various branching configurations can be used as an indicator to estimate the yields of sorghum. For various crops, computerized methods have been demonstrated to be beneficial in automatically collecting this information. However, the application of sorghum crops faces challenges due to variations in the color and shape of sorghum. Therefore,a method is proposed based on the three models for the classification, localization, and segmentation of sorghum. The shifted window transformer (SWT)network is proposed to have seven layers of path embedding, two Swin Transformers, global average pooling, patch merging, and dense connections. The proposed SWT is trained on the following selected hyperparameters: patch size(2,2), two window size,1e-3 learning rate,128 batch size,40 epochs, 0.0001 weight decay, 0.03dropout, eight heads, 64 embedding dimension, and 256 MLP. To localize the sorghum region, the YOLOv9-c model is trained from scratch on the selected hyperparameters for 100 epochs. Due to light, illumination, and noise, the sorghum images are more complex. A transformer-based SegNetmodel is designed, in which features are extracted using a pre-trained SegFormer-B0 model fine-tuned for ADE-512-512. The proposed model is trained from scratch for 10 epochs using the Adam optimizer with a learning rate of 5e-5 and CrossEntropyLoss hyperparameters, which are finalized after extensive experimentation to achieve more accurate segmentation of the sorghum; this is a significant contribution of this work. The achieved outcomes are superior to those in other published works.

Objective: To determine the frequency, cause and type of dental injury in patients reporting to Armed Forces Institute of Dentistry. Study design: Cross-Sectional Survey. Place and Duration of Study: Department of Operative Dentistry Armed Forces Institute of Dentistry, Rawalpindi, Pakistan, from Sep 2021 to Sep 2022. Methodology: A questionnaire was filled out for 357 patients reporting dental injury, including the extent of hard and soft tissue injuries. The cause and place of injury occurred; investigations, the treatment provided by the treating dentists ranging from restoration to root canal, type and duration of splint were also recorded. Results: In the current study, 189(52.9%) out of 357 children got injury due to falls to the playground and other places. Maxillary incisors were mostly affected, and 163(45.7%) children had complicated crown fractures. Rigid splinting was done in 39(70.9%) of root fracture cases, while flexible splinting was done in 162(53.6%) patients with complicated crown fracture cases and 81(26.8%) complicated crown fracture cases. In 72(88.8%) cases of uncomplicated crown fracture, indirect pulp capping was done, and in 67(41.1%) cases of complicated crown fracture, root canal treatment were done. Apexification was done in 28(68.3%) of avulsion cases. Conclusion: Our survey showed that most injuries occurred at school and the roadside. Maxillary incisors are primarily involved with complicated crown fractures, which are effectively managed.Keywords: Avulsion, Complicated crown fracture, Dental injury, Splinting.