Screening of barley genotypes for drought tolerance based on culm reserves contribution to grain yield

Grain filling determines the grain weight, a major component of grain yield in cereals. Grain filling in barley depends on current assimilation and culm reserves. A pot experiment was conducted at the Grilled House, Department of Crop Botany, Bangladesh Agricultural University, Mymensingh during October 2015–May 2016 to study the grain filling patterns and the contributions of culm reserves to grain yield under drought stress. The experiment consisted of two factors—barley cultivars (six cultivars) and drought stress treatments (control and drought stress). Drought stress was imposed by limiting the irrigation during grain filling period. The tillers were sampled at anthesis, milk-ripe and maturity to determine the changes in dry weights of different parts, viz., leaf lamina, culm with sheath, spikes, and grains; and to examine the contribution of culm reserves to grain yield. The result in this experiment revealed that the grain yield was reduced by 5–25% due to drought stress. The reduction in grain yield was attributable to reduce number of grains per spike and lighter grain weight due to the stress. Drought stress drastically reduced the grain filling duration by about 30% and the stress induced early leaf senescence. Photosynthesis rate and leaf greenness were also reduced in stress. The stress altered the contribution of culm reserves, water soluble carbohydrates (WSCs) in culms to grains. At milk ripe stage, accumulation reached its peak. It accumulated 29.0 to 70.0 mg and from 15.8 to 40.6 mg culm−1 in control and stressed plants, respectively. The residual culm WSCs ranged from 3.5 to 11.2 mg and 1.0 to 3.5 mg culm−1 under control and stress conditions, respectively. The highest contribution of culm WSCs to grain yield was observed in BARI barley2 and the lowest was in BARI barley5 both in control and stress condition. Among the cultivars studied, BARI barley2 produced higher yield with the higher contribution of culm reserves to grain yield under the drought stress

Citric Acid-Mediated Abiotic Stress Tolerance in Plants

Several recent studies have shown that citric acid/citrate (CA) can confer abiotic stress tolerance to plants. Exogenous CA application leads to improved growth and yield in crop plants under various abiotic stress conditions. Improved physiological outcomes are associated with higher photosynthetic rates, reduced reactive oxygen species, and better osmoregulation. Application of CA also induces antioxidant defense systems, promotes increased chlorophyll content, and affects secondary metabolism to limit plant growth restrictions under stress. In particular, CA has a major impact on relieving heavy metal stress by promoting precipitation, chelation, and sequestration of metal ions. This review summarizes the mechanisms that mediate CA-regulated changes in plants, primarily CA's involvement in the control of physiological and molecular processes in plants under abiotic stress conditions. We also review genetic engineering strategies for CA-mediated abiotic stress tolerance. Finally, we propose a model to explain how CA's position in complex metabolic networks involving the biosynthesis of phytohormones, amino acids, signaling molecules, and other secondary metabolites could explain some of its abiotic stress-ameliorating properties. This review summarizes our current understanding of CA-mediated abiotic stress tolerance and highlights areas where additional research is needed

SEED PRIMING AND EXOGENOUS APPLICATION OF SALICYLIC ACID ENHANCE GROWTH AND PRODUCTIVITY OF OKRA (Abelmoschus esculentus L.) BY REGULATING PHOTOSYNTHETIC ATTRIBUTES

Low and uneven germination is a serious problem for the successful production of okra seedlings. Priming of seeds as well as supplementation of different plant growth regulators exhibited better response in successful seedling production which eventually results in higher yield. Therefore, the present study was conducted to evaluate the effects of seed priming and exogenous application of salicylic acid (SA) on okra seed germination and plant development. The okra seeds were primed by 1 mM and 2 mM of SA for 60 minutes whereas the seeds were washed several times with distilled water for the control treatment. Similar doses of SA have been exogenously sprayed to the 12 days okra seedlings for 4 days. The results of the study revealed that seed priming with SA enhanced germination percentage (GP), increased coleoptile length and weight, shoot and root length, and seed vigor index (SVI). Similarly, exogenous application of 1 mM SA increased relative water content (RWC), contents of chlorophyll a, chlorophyll b, total chlorophyll while a higher dose of SA (2 mM) degraded the leaf pigments. Supplementation of SA altered photosynthetic attributes, net photosynthetic (Pn) and transpiration rate (Tr), stomatal conductance (Gs), and water use efficiency (WUE). Moreover, SA treatment reduced the time duration of flower bud initiation and days to first flowering and enhanced the yield per plant. The results of this study indicated that seed priming and exogenous application of SA enhanced germination and okra productivity by regulating RWC and photosynthetic attributes where 1 mM SA is more effective compared to 2 mM SA

Phytofabricated Silver Nanoparticles (AgNPs) Applied in Vase Solution as a Novel Anti-Microbial Agent for Enhancing the Vase-life of Cut-Rose Flower

Plant extract has been exploited for biogenic synthesis of metallic nanoparticles. This is considered as the promising alternative routes of chemical and physical synthesis methods owing to their abundancy in nature and ecofriendly friendly synthesis protocol. Rose is the top-ranked and universally favorite cut flower. Poor post-harvest management deteriorates the quality and reduces the vase life. Microbial proliferation of the stem base in the vase solution is a concern for these cut flowers that shortens their vase-life. To overcome this problem, a smart solution i.e. phytofabricated silver nanoparticles have been shown to act as anti-microbial agent. In this study, leaf extracts of Camellia sinensis were exploited to fabricate biogenic silver nanoparticles which showing UV-peak absorption ranging from 412-500 nm. This biogenic silver nanoparticles were applied @ 0.01, 0.05 and 0.1mM and compared with a control (without AgNPs) and silver nitrate (AgNO3). Interestingly, AgNPs showed a strong antimicrobial activity in vase solution and cut roses extended their vase life up to 13 days compared to 8 days in control and 9 days in AgNO3. Statistical differences in flower opening, bacterial growth (CFUmL−1) in vase solutions, water uptake, relative fresh weight and vase life of cut roses were found among treatments. In vitro microbial analysis and microscopic investigation of vessels showed that the development of microorganisms was reduced by a high concentration of AgNPs (0.1mM) at the cut end of flower and improving water uptake that followed by extended flowers vase life. The unique phytofabricated AgNPs technology can serve as a promising preservative to increase the ornamental value of cut rose flowers. Taken all together, applied phytofabricated AgNPs in vase solution significantly enhance vase life of cut rose flowers over control. [J Bangladesh Agril Univ 2022; 20(2.000): 133-140

Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System

Skin cancer is a significant health concern worldwide, and early and accurate diagnosis plays a crucial role in improving patient outcomes. In recent years, deep learning models have shown remarkable success in various computer vision tasks, including image classification. In this research study, we introduce an approach for skin cancer classification using vision transformer, a state-of-the-art deep learning architecture that has demonstrated exceptional performance in diverse image analysis tasks. The study utilizes the HAM10000 dataset; a publicly available dataset comprising 10,015 skin lesion images classified into two categories: benign (6705 images) and malignant (3310 images). This dataset consists of high-resolution images captured using dermatoscopes and carefully annotated by expert dermatologists. Preprocessing techniques, such as normalization and augmentation, are applied to enhance the robustness and generalization of the model. The vision transformer architecture is adapted to the skin cancer classification task. The model leverages the self-attention mechanism to capture intricate spatial dependencies and long-range dependencies within the images, enabling it to effectively learn relevant features for accurate classification. Segment Anything Model (SAM) is employed to segment the cancerous areas from the images; achieving an IOU of 96.01% and Dice coefficient of 98.14% and then various pretrained models are used for classification using vision transformer architecture. Extensive experiments and evaluations are conducted to assess the performance of our approach. The results demonstrate the superiority of the vision transformer model over traditional deep learning architectures in skin cancer classification in general with some exceptions. Upon experimenting on six different models, ViT-Google, ViT-MAE, ViT-ResNet50, ViT-VAN, ViT-BEiT, and ViT-DiT, we found out that the ML approach achieves 96.15% accuracy using Google’s ViT patch-32 model with a low false negative ratio on the test dataset, showcasing its potential as an effective tool for aiding dermatologists in the diagnosis of skin cancer