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Abstract Micronutrient application has a crucial role in mitigating salinity stress in crop plants. This study was carried out to investigate the effect of zinc (Zn) and boron (B) as foliar applications on fenugreek growth and physiology under salt stress (0 and 120 mM). After 35 days of salt treatments, three levels of zinc (0, 50, and 100 ppm) and two levels of boron (0 and 2 ppm) were applied as a foliar application. Salinity significantly reduced root length (72.7%) and shoot length (33.9%), plant height (36%), leaf area (37%), root fresh weight (48%) and shoot fresh weight (75%), root dry weight (80%) and shoot dry weight (67%), photosynthetic pigments (78%), number of branches (50%), and seeds per pod (56%). Fenugreek’s growth and physiology were improved by foliar spray of zinc and boron, which increased the length of the shoot (6%) and root length (2%), fresh root weight (18%), and dry root weight (8%), and chlorophyll a (1%), chlorophyll b (25%), total soluble protein content (3%), shoot calcium (9%) and potassium (5%) contents by significantly decreasing sodium ion (11%) content. Moreover, 100 ppm of Zn and 2 ppm of B enhanced the growth and physiology of fenugreek by reducing the effect of salt stress. Overall, boron and zinc foliar spray is suggested for improvement in fenugreek growth under salinity stress.

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Maize (Zea mays L.) is a salt-sensitive plant that experiences stunted growth and development during early seedling stages under salt stress. Salicylic acid (SA) is a major growth hormone that has been observed to induce resistance in plants against different abiotic stresses. Furthermore, plant growth-promoting rhizobacteria (PGPR) have shown considerable potential in conferring salinity tolerance to crops via facilitating growth promotion, yield improvement, and regulation of various physiological processes. In this regard, combined application of PGPR and SA can have wide applicability in supporting plant growth under salt stress. We investigated the impact of salinity on the growth and yield attributes of maize and explored the combined role of PGPR and SA in mitigating the effect of salt stress. Three different levels of salinity were developed (original, 4 and 8 dS m−1) in pots using NaCl. Maize seeds were inoculated with salt-tolerant Pseudomonas aeruginosa strain, whereas foliar application of SA was given at the three-leaf stage. We observed that salinity stress adversely affected maize growth, yield, and physiological attributes compared to the control. However, both individual and combined applications of PGPR and SA alleviated the negative effects of salinity and improved all the measured plant attributes. The response of PGPR + SA was significant in enhancing the shoot and root dry weights (41 and 56%), relative water contents (32%), chlorophyll a and b contents (25 and 27%), and grain yield (41%) of maize under higher salinity level (i.e., 8 dS m−1) as compared to untreated unstressed control. Moreover, significant alterations in ascorbate peroxidase (53%), catalase (47%), superoxide dismutase (21%), MDA contents (40%), Na+ (25%), and K+ (30%) concentration of leaves were pragmatic under combined application of PGPR and SA. We concluded that integration of PGPR and SA can efficiently induce salinity tolerance and improve plant growth under stressed conditions.

Large-scale indoor 3D reconstruction with multiple robots faces challenges in core enabling technologies. This work contributes to a framework addressing localization, coordination, and vision processing for multi-agent reconstruction. A system architecture fusing visible light positioning, multi-agent path finding via reinforcement learning, and 360° camera techniques for 3D reconstruction is proposed. Our visible light positioning algorithm leverages existing lighting for centimeter-level localization without additional infrastructure. Meanwhile, a decentralized reinforcement learning approach is developed to solve the multi-agent path finding problem, with communications among agents optimized. Our 3D reconstruction pipeline utilizes equirectangular projection from 360° cameras to facilitate depth-independent reconstruction from posed monocular images using neural networks. Experimental validation demonstrates centimeter-level indoor navigation and 3D scene reconstruction capabilities of our framework. The challenges and limitations stemming from the above enabling technologies are discussed at the end of each corresponding section. In summary, this research advances fundamental techniques for multi-robot indoor 3D modeling, contributing to automated, data-driven applications through coordinated robot navigation, perception, and modeling. [ABSTRACT FROM AUTHOR]

The labor force, physical capital, and energy sources are key economic drivers that enhance the output levels of developing economies. Despite their significance, the impact of these factors on agricultural and industrial output in Pakistan remains underexplored. This study aims to address this gap by examining the effects of the labor force, physical capital, and energy consumption—including electricity, oil, and gas—on agricultural and industrial output. Additionally, we explore the combined effects of electricity and oil consumption on these sectors. Based on unit root test results, which indicate that the variables as either I(0) or I(1), the Autoregressive Distributed Lag (ARDL) technique is selected. This method is particularly effective for handling mixed integration orders and provides robust estimates in small sample sizes, allowing for a thorough examination of both short- and long-run dynamics. Using annual time-series data from Pakistan for the period 1990–2022, the empirical results reveal that higher levels of the labor force, physical capital, electricity consumption, oil consumption, and gas consumption significantly increase agricultural and industrial output in both the short and long run. Furthermore, the findings reveal that the combined effect of electricity and oil consumption has a stronger impact on agricultural and industrial output compared to their individual effects. These results are further validated using alternative econometric techniques such as DOLS and FMOLS. To enhance Pakistan's agricultural and industrial performance, policies should prioritize investment in human capital and physical capital development, ensure reliable and efficient energy supplies, and promote integrated energy management strategies. These steps are crucial for fostering sustainable economic growth and productivity in both sectors. [ABSTRACT FROM AUTHOR]

Soil salinization limit crop yield and deteriorate product quality in arid and semi-arid agroecological regions. Under such conditions regulation of mineral nutrients may help to sustain crop productivity. Therefore, a pot experiment was carried out to identify optimal sulfur level and source for enhancing salt adaptability of sunflower (Helianthus annuus L.). A uniform salinity level of 100 mM NaCl was developed in each pot and then six S treatments viz. S0, control; S1, 20 mg sulfur kg-1 soil; S2, 40 mg sulfur kg-1 soil; S3, 60 mg sulfur kg-1 soil; S4, 80 mg sulfur kg-1 soil and S5, 100 mg sulfur kg-1 soil were applied by using elemental S and K2SO4 as sulfur source. Supplementation of sulfur caused reduction in tissue Na+ accumulation and electrolyte leakage while increase in tissue K+ and Ca2+ with a subsequent increase in relative water content and photosynthetic rate of sunflower. Increasing sulfur levels in the form of K2SO4 depicted linear increase in plant growth and yield attributes up to 80 mg sulfur kg-1 soil beyond which there was decline in these growth characteristics suggesting that sulfur as K2SO4 at 80 mg sulfur kg-1 soil might be optimum in mitigating NaCl toxicity in sunflower.