Ministry of Science and Technology

Sesame (Sesamum indicum L.), an important oilseed crop, requires genetic improvement to ensure food security. Exploitation of a small fraction of genetic diversity is a major limiting factor for this crop. ICAR-NBPGR holds a large sesame base collection (6,000 unique accessions), originating from India and other countries. The study aims at the characterization of a sesame germplasm collection and development of working core set representing the variability of entire germplasm collection in the National Genebank. Characterization was carried out in an Augmented Block Design (ABD) under multi-environmental conditions (six locations representing five agro-ecological zones of India) for two consecutive years based on 33 agro-morphological traits, different levels of biotic stress (phyllody, dry root rot), abiotic stress (water logging, drought), and seed quality parameters (oil, protein, lignan, fatty acids). For core set preparation, the coincidence rate (CR%) for range and the variable rate (VR%) for coefficient of variation were maximum. Levene’s test and Newman-Keuls tests were performed to compare the entire and core collection. Diversity between the two (entire and core collection) was compared using Shannon–Weaver diversity index. We developed a sesame core set of 773 accessions, which consists of 12.88% of the entire collection. Developed core set exhibited a Coincidence rate (CR)% of 99.8% and a variable rate (VR%) of CV 103.59%. A multipurpose core set of sesame germplasm was assembled to benefit the plant breeding community (for trait introgression), farmers, and researchers to develop climate-resilient sesame cultivars.

This study aimed to conduct a hydrological analysis and assess the potential for rainwater harvesting using GIS-AL technologies for the Al-Rafee’ watershed, located in the eastern part of Iraq within the governorates of Salah Al-Din and Diyala Provinces. The total area of the basin is 212.19 km², lying between latitudes (34°33’18"–34°33,49"N) and longitudes (44°35’22"–44°46’17"E). The study relied on the SCS-CV model to estimate surface water runoff volume. The findings indicated the presence of three hydrological soil groups: B, C, and D. The land cover was found to be diverse, with agricultural lands occupying the largest area (91.12 km²), while barren lands had the smallest coverage (0.22 km²). The study also showed high Curve Number (CN) values and low retention (S) values. Furthermore, it concluded that it is possible to establish reservoirs to collect rainwater at the identified locations, with the aim of developing the studied region for future investment opportunities.

Sweet potato [Ipomoea batatas (L.) Lam.] is considered a multipurpose plant with numerous applications and health benefits due to its high nutritional antioxidant, rich in fiber, and vitamins A and C. This study was conducted to determine the optimal harvesting time for sweet potato (Jewel Yams variety) cultivated for the first time in the Kurdistan Region of Iraq (KRI). The study was conducted in a RCBD (randomized block design), with five treatments which were harvested in different interval times (70, 90, 110, 130, and 150 days), 7 plants per plot, and 3 replications. After each interval of harvesting, the total yield, individual weight, size, and number of sweet potatoes per plot, as well as sweet potato quality attributes such as sugar content, were assessed using a digital refractometer (ATAGO 3810 PAL-1). The results showed that harvesting time significantly (P ≤ 0.05) affected the yield performance of the sweet potatoes. The highest values of tuber weight (265.81 g/plant), average length (36.55 cm), width (36.35 mm), sugar content (6.34%), and total weight per plot (2.79 kg) were recorded in plots harvested 150 days (150 HD). While number of fruits per plant reached a maximum (4.86) in samples harvested after 130 days. In addition, the trends of increasing the total yield per plot compared to the earliest harvest (70 days) are as follows: 349%, 843%, 871%, and 2495% for 90, 110, 130, and 150 days, respectively. It can be concluded that harvesting times have considerable potential for enhancing sweet potato traits in terms of yield and quality. Consequently, this study suggest that farmers may base decisions upon the ultimate tuber size, degree of sweetness, and overall yield per unit area, harvesting at 130–150 days after planting, depending on the tuber maximum or quantity of interest. It is, therefore, concluded that the practice of sweet potato harvest for marketing purposes must be prolonged to 150 days for the KRI to achieve high market quality and profitability.

Tuberculosis, especially drug-resistant tuberculosis remains a global threat, and new drugs are desperately needed to combat the spread of multidrug-resistant Mycobacterium tuberculosis. Here we describe a natural macrotetrolide dinactin with anti-tuberculosis activity against susceptive and non-replicating Mycobacterium tuberculosis. Dinactin can also synergistically enhance the anti-tuberculosis effect of rifampicin and isoniazid against drug-resistant strains.Furthermore, dinactin exhibited excellently antituberculosis effect in macrophage and Galleria mellonella models. Since the ionophore properties of dinactin, it not only enhanced cations transport and altered membrane permeability but also caused the dissipation of proton motive force and metabolic perturbations. Finally, through the selection of spontaneous resistant mutants and whole genome sequencing, non-synonymous single nucleotide polymorphisms were successfully identified in the cpsA gene of the LytR-Cps2A-Psr family. The dinactin-resistant mutants exhibited decreased in vitro drug sensitivity to dinactin without cross-resistance to first-line antituberculosis drugs. Genetic studies and molecular biology assays have subsequently confirmed cpsA as one of the potential targets for dinactin’s anti-tuberculosis activity. Collectively, these data indicate that dinactin could be a promising candidate for treating tuberculosis.

The mechanisms governing pH regulation in membrane-less organelles (MLOs) are essentially different from those relying on membrane proteins, yet it remains poorly understood due to the difficulty in directly controlling the conditions across the MLOs interface. Here, we develop a coacervate-based, in vitro model to investigate how liquid-liquid phase separation (LLPS) could contribute to pH regulation in MLOs. We construct peptide-based coacervate droplets using microfluidics and find that charged polymers within the coacervates help create uneven H+/OH- distributions, resulting in pH-regionalized microenvironments similar to the nucleolus. More interestingly, such a pH difference weakens or even disappears following the destruction of LLPS, a phenomenon observed in both nucleolus and coacervate droplets. Based on these findings, we demonstrate the ability to finely tune the local pH of the coacervate droplets over a wide range by incorporating enzymes, which can drive and control cascade reactions, and perform basic molecular biology operations such as polymerase chain reaction (PCR) and in vitro transcription and translation reaction (IVTT). This study highlights the role of LLPS in pH modulation within MLOs and provides insights into the potential of coacervates as protocells for broader applications.

Soluble sugars are the key photo-assimilates in higher plants, playing critical roles in growth, development, and stress regulation. The transport of sugars in plants involves the coordinated action between several sugar transporter families, including the SUT, STP, pGlcT, VGT, TMT, INT, PLT, SFP, and SWEET families. Over recent decades, numerous studies have elucidated the molecular functions of major sugar transporters. Phylogenetic and evolutionary analyses support the conservation of substrate specificity and transport direction, at least to some extent. Structural analyses have provided key insights into the structural-function relationships of important transporters (e.g., OsSWEET2b and AtSTP10), which can be effectively leveraged for artificial intelligence (AI)-enabled protein structure prediction and rational design. Advances in omics technologies now enable low-cost, routine transcriptome profiling and cutting-edge techniques (e.g., single-cell multi-omics and spatiotemporal RNA-seq), providing unprecedented ways to understand how sugar transporters function coordinately at multiple levels. Here, we describe the classification of major sugar transporters in plants and summarize established functional knowledge. We emphasize that recent groundbreaking advances in AI-enabled protein analyses and multi-omics will revolutionize molecular physiology in crops. Specifically, the integration of functional knowledge, AI-based protein analyses, and multi-omics will help unravel the orchestration of different sugar transporters, thereby enhancing our understanding of how sugar transportation and source-sink interactions contribute to crop development, yield formation, and beyond, ultimately boosting carbohydrate transport- related crop improvement.

Improper management of residues from rice cultivation and livestock farming can exert severe pressure on the environment. Anaerobically digesting these residues for biogas production is a plausible solution to mitigate their environmental impact. However, due to the low degradability of rice straw, pretreatment is imperative to enhance its methane production. Therefore, this study investigated the effects of eight thermal and four thermochemical pretreatment methods on the biodegradability of rice straw. Results indicated that the thermochemical pretreatment, with NaOH, increased methane production by 13%–15%, while thermal pretreatment increased it by 2%–5%, compared to untreated rice straw. Subsequently, the most effective pretreatment was used in co-digestion batch experiments with cattle and swine slurries separately to determine the optimal ratio of pretreated rice straw (p-RS) with each slurry. Co-digestion of p-RS with swine slurry increased methane production up to 59%, while co-digestion with cattle slurry increased it by 14%, compared to the mono-digestion of each slurry. Moreover, a techno-economic analysis was employed to assess the feasibility of establishing a biogas power plant treating the optimum co-digestion mixture. Based on our assessment, the plant can generate an annual revenue and net profit of approximately €2,418,000 and €1,510,000, respectively. The payback period was estimated at 2.98 years, while the return on investment and profit margin were 33.5% and 62.4% per year, respectively.

Unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) with a blockchain consensus algorithm is a promising solution for addressing mobile offloading of computation-intensive or latency-sensitive tasks with extensive service range, while ensuring the authenticity of the offloading. Existing UAV-aided MEC studies focus on task offloading or trajectory planning of single-antenna UAVs, missing multiple-input multiple-output (MIMO) UAV systems. In addition, most blockchain-based UAV-aided edge computing studies adopt energy-consuming proof-of-work-based consensus mechanisms, which are unsuitable for energy-limited UAV scenarios. To address the above issues, in this paper, we develop a joint deadline-aware task offloading and UAV trajectory planning scheme, utilizing the effects simulated through an energy-efficient consensus protocol. In order to prevent the exhaustion of UAVs' energy and ensure the authenticity of decision-making, we propose an energy-based Raft (E-Raft) consensus algorithm, enabling dynamic leader selection through a series of decreasing energy thresholds. Subsequently, we present a computational profit maximization problem to jointly optimize deadline-aware task offloading and the UAV swarm's trajectory planning. To address this NP-hard problem, we develop an online priority-based task offloading and trajectory selection algorithm, which is performed by the selected leader of the E-Raft consensus in each round. Simulation results demonstrate that our proposed scheme achieves up to 40% performance improvement over other approaches.