Aleksandra Sergeevna Utkina

This review synthesizes recent regional applications of satellite, unmanned aerial vehicle (UAV), and hyperspectral/spectroradiometric remote sensing for vegetation cover discrimination, including crop and natural vegetation discrimination, plant disease and pest detection, and yield assessment. The reviewed evidence demonstrates complementary rather than universally superior capabilities among sensing platforms. Satellite observations provide repeated large-area monitoring but remain constrained by spatial resolution, cloud interference, and spectral mixing, whereas UAVs offer very-high-resolution and flexible field-scale observations at the expense of spatial coverage and greater acquisition and processing requirements. Hyperspectral and spectroradiometric approaches provide detailed spectral information for distinguishing subtle vegetation differences, but are limited by data complexity and operational scalability. The quantitative results reported in the reviewed studies illustrate this variability: satellite-based crop discrimination achieved approximately 90% overall accuracy with QuickBird and 81% overall accuracy (κ = 0.74) with Sentinel-2 at a 10 m resolution, while a UAV hyperspectral vegetation classification study achieved 94.5% accuracy. However, these values are not directly comparable because the vegetation targets, sensors, acquisition conditions, and analytical methods differed among studies. Recent evidence also indicates that the phenological timing, spectral band selection, spatial resolution, and representative training data strongly influence the discrimination performance, while the transfer of disease detection models from controlled experiments to operational field conditions remains a major challenge. By integrating evidence from satellite, UAV, and ground-based spectroradiometric approaches, this review provides a comprehensive framework for understanding the complementary capabilities of these technologies for vegetation cover discrimination and highlights their importance for improving vegetation monitoring, precision agriculture, and sustainable ecosystem management.

This review aims to elucidate the genetic and epigenetic mechanisms underlying mitochondrial dysfunction in Parkinson’s disease (PD) and to explore how these insights inform emerging therapeutic strategies. A comprehensive analysis of current literature was conducted to integrate evidence on mitochondrial homeostasis, mitophagy regulation, and genome stability, with a focus on mutations in SNCA, LRRK2, VPS35, PINK1, PARK2, DJ-1, and POLG, as well as epigenetic alterations affecting mitochondrial DNA. Genetic mutations disrupt mitochondrial dynamics, impair autophagy, and cause oxidative stress, leading to dopaminergic neuron degeneration. Epigenetic modifications—such as altered DNA methylation, histone acetylation, and non-coding RNA regulation—further exacerbate mitochondrial instability and neuronal apoptosis. Mitochondrial impairment represents a common denominator linking hereditary and sporadic forms of PD, providing a unifying model of disease pathogenesis. Advances in understanding mitochondrial biology have enabled the development of novel therapeutic approaches, including activators of the PINK1/Parkin pathway, inhibitors of LRRK2 and α-synuclein aggregation, and strategies promoting mitochondrial biogenesis and intercellular transfer, offering potential for disease modification.

Non-coding RNAs (ncRNAs) have emerged as central regulators of how plants perceive, integrate, and respond to environmental and biological challenges. Once regarded as transcriptional noise, diverse ncRNA classes, including microRNAs (miRNAs), small interfering RNAs (siRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), enhancer RNAs (eRNAs), and piwi-interacting RNA (piRNAs), are now recognized as powerful modulators of gene regulatory networks that shape stress signalling, developmental plasticity, and immune competence. Acting across epigenetic, transcriptional, and post-transcriptional levels, ncRNAs orchestrate chromatin remodelling, RNA stability, redox homeostasis, and hormone signalling to balance growth and defense. This review synthesizes evidence that ncRNA-mediated regulation is highly convergent: identical ncRNA modules are repeatedly recruited across abiotic and biotic stresses and funnel diverse signals through shared regulatory nodes involving hormone networks, reactive oxygen species, and master transcriptional hubs. We highlighted how redox-ncRNA feedback loops, chromatin-embedded ncRNA activity, and cross-layer interactions among miRNAs, siRNAs, lncRNAs, and circRNAs generate synergistic control over stress responses. This review further discusses how ncRNAs encode stress memory and priming, enabling plants to respond more efficiently to recurrent challenges, while also imposing regulatory trade-offs that constrain growth, development, and yield. Despite rapid discovery, ncRNA research remains limited by incomplete mechanistic validation, uncertain epigenetic stability, weak integration with systems biology, and unresolved biosafety and regulatory issues. Addressing these barriers will be essential for translating ncRNA biology into predictive and deployable strategies. By leveraging their capacity to unify signalling and adaptive regulation, ncRNAs represent promising molecular entry points for developing resilient, climate-ready crops.

Peanut (Arachis hypogaea L.) is a globally important oilseed and food legume, yet its productivity is persistently constrained by devastating diseases and insect pests that thrive under changing climates. This review aims to provide a comprehensive synthesis of advances in precision breeding and molecular approaches for enhancing disease and pest resistance in peanut. Traditional control measures ranging from crop rotation and cultural practices to chemical protection have delivered only partial and often unsustainable relief. The narrow genetic base of cultivated peanut and its complex allotetraploid genome further hinder the introgression of durable resistance. Recent advances in precision breeding are redefining the possibilities for resilient peanut improvement. Multi-omics platforms genomics, transcriptomics, proteomics, and metabolomics have accelerated the identification of resistance loci, effector-triggered immune components, and molecular cross-talk between pathogen, pest, and host responses. Genome editing tools such as CRISPR-Cas systems now enable the precise modification of susceptibility genes and defense regulators, overcoming barriers of conventional breeding. Integration of these molecular innovations with phenomics, machine learning, and remote sensing has transformed resistance screening from manual assessment to real-time, data-driven prediction. Such AI-assisted breeding pipelines promise enhanced selection accuracy and faster deployment of multi-stress-tolerant cultivars. This review outlines current progress, technological frontiers, and persisting gaps in leveraging precision breeding for disease and pest resistance in peanut, outlining a roadmap toward climate-resilient, sustainable production systems.

Elevated cobalt (Co) levels induce cellular toxicity and reduce overall plant growth and development. Ascorbic acid is known to enhance heavy metal toleran

The worldwide rise in soil salinization is among the most critical consequences of climate change, posing a significant threat to food security. Wheat (Triticum aestivum L.), a staple crop of paramount importance worldwide, encounters significant production limitations due to abiotic stressors, particularly salinity. Consequently, the development and cultivation of salt-tolerant wheat genotypes have emerged as an essential strategy to sustain agricultural productivity and safeguard global food security. The aim of the present study was to investigate the effect of salinity (150 mM) on the performance and combining ability of 10 hybrid combinations (F2) and their parents that were obtained through a line × tester mating design at the seedling stage. Morphological, physiological, and biochemical traits were assessed under both control and salt-stress conditions. Among the assessed traits, SFW emerged as the strongest predictor of salt tolerance, demonstrating the highest correlation with MFVS and the greatest contribution in the regression model. The results highlighted distinct responses among the studied genotypes. Hybrid H5 demonstrated particular promise, surpassing the performance of the superior parent for Na⁺, K⁺, K⁺/Na⁺ and proline (Pro). Furthermore, tester T1 emerged as a good combiner for proline (Pro), total soluble sugars content (Sug), chlorophyll content (Chl) and root length (RL) under saline conditions. In contrast, under control conditions, line L1 and testers T2, T3, and T5 exhibited superior performance, demonstrating significant general combining ability (GCA) effects for four traits simultaneously. Hybrid H4 emerged as outstanding under salt stress, exhibiting favorable specific combining ability (SCA) effects for Na⁺, K⁺/Na⁺ ratio, root length (RL), relative water content (RWC), and total soluble sugars content (Sug). Under normal conditions, hybrids H7 and H10 exhibited significantly superior performance across three traits simultaneously. Non-additive genetic effects predominantly influenced the studied traits under both conditions. The parental and hybrid combinations show promise for incorporation into breeding programs designed to improve salt tolerance under the specific conditions studied.

Wheat is a vital crop globally, essential for agriculture, economics, and food security. However, in arid and semi-arid conditions, wheat production faces significant challenges due to low water availability, uneven rainfall distribution, and high soil salinity. The germination and early seedling stages are particularly vulnerable to these stresses. Therefore, this study assessed 15 wheat genotypes for their tolerance to salinity stress during early growth stages, using a hydroponic system with four salt stress levels (0, 50, 100, and 150 mM NaCl). Significant differences were observed for genotype and salinity main effects and their interaction on all investigated traits, indicating considerable variability in the response to salt stress among the investigated wheat cultivars. High NaCl concentrations led to substantial reductions in measured parameters across genotypes, with some showing resilience while others exhibited heightened sensitivity. Stress tolerance indices, such as mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), stress tolerance index (STI) and yield index (YI), were identified as reliable indicators for selecting salt-tolerant wheat cultivars. Consequently, Sidi Okba (G11), Ziad (G12), Tamezghida (G13) and Zidane (G14) emerged as the most promising, displaying acceptable performance under both non-stress and salt-stress conditions. These genotypes could serve as valuable genetic resources for breeding programs aimed at enhancing wheat’s salinity tolerance, particularly in arid and semi-arid regions.

Abiotic stresses pose significant challenges to wheat farming, yet exploiting the genetic variability within germplasm collections offers an opportunity to effectively address these challenges. In this study, we investigated the genetic diversity of key agronomic traits among twenty durum wheat cultivars, with the intention to pinpoint those better suited to semi-arid conditions. Field trials were conducted at the ITGC-FDPS Institute, Setif, Algeria, during the winter season of 2021/22. A completely randomized design was used with three replicates. Statistical analyses revealed significant variation among the genotypes for most of the studied traits, with some cultivars exhibiting a superior performance in a stressful environment. Notably, traits like the number of grains per spike (NGS) and the grain yield (GY) displayed high genotypic coefficients of variation (CVg). Except for membrane thermostability (MT) and biological yield (BY), the majority of the assessed traits exhibited moderate-to-high heritability estimates. Genotypic and phenotypic correlation studies have confirmed the importance of many yield-related traits in the expression of GY. The harvest index (HI) underscored the highest genotypic direct effect on GY, followed closely by spike number (SN), serving as consistent pathways through which most of the measured traits indirectly influenced GY. The cluster analysis categorized the durum wheat cultivars into seven distinct clusters. The largest inter-cluster distance was observed between clusters G3 and G4 (D² = 6145.86), reflecting maximum dissimilarity between the individuals of these clusters. Hybridizing divergent clusters may benefit future breeding programs aiming to develop potential durum wheat varieties through cross combinations. This study’s findings contribute to sustainable agriculture efforts by facilitating the selection of genotypes with enhanced resilience and productivity, particularly for cultivation in challenging semi-arid regions.

Wheat is considered to be a strategic crop for achieving food security. Wherefore, one of the current objectives of today’s agriculture is to ensure a consistent and sustainable yield of this particular crop while mitigating its environmental footprint. However, along with the genetic potential of varieties, agricultural practices play a key role in ensuring a high and stable yield of wheat. Under changing climatic conditions, new eco-friendly practices were adopted in the wheat farming system in recent decades. In this review, a large number of peer-reviewed articles have been screened during the last 15 years to evaluate the potential of some environmentally friendly agricultural practices such as tillage system, biological crop protection, crop rotation, intercropping systems, and the integration of resistant varieties in achieving a high and stable wheat yield. The present investigation unveiled that embracing eco-friendly agricultural methods in the wheat farming system holds the potential to engender high and sustainable wheat yields, contingent upon a normative strategy that comprehensively addresses multiple factors. These include the intrinsic attributes of the grown wheat cultivars, plant nutritional parameters, soil agrochemical characteristics, and specific climatic conditions. Further in-depth investigations under field conditions are necessary to help in the discernment of appropriate environmentally agricultural techniques that can efficaciously optimize the yield potential of the different cultivated varieties.