Essential Crop Research Articles

In vitro propagation and shootlets assessment for drought and salinity tolerance of traditional accessions of potato

Abiotic stresses, including heat, drought, and salinity, pose severe threats to agricultural yields, globally affecting essential crops like potatoes. The aim of this study is to establish an in vitro culture system for three potato accessions: Tal Amara 1 (TA1), Tal Amara 2 (TA2), and Tal Amara 3 (TA3) and to quantify their tolerance to temperature, drought, salinity, and combined stresses. The results demonstrated that MS0 (devoid of growth regulators) medium was the best for culture initiation, with a percentage of reactive meristems of 82.22%, whereas MS1 (0.35 mg L-1 Kin + 0.2 mg L-1 IAA + 0.1 mg L-1 GA3) medium resulted in the highest multiplication rate of 5.5. The most heat tolerant accession was TA1, with shootlets lengths ranging from 2 cm to 4.4 cm at temperatures of 4°C and 38°C respectively. Concerning the effect of combined drought and temperature stresses, TA1 and TA3 showed tolerance to the different mannitol concentrations. Likewise, the most prominent accession in terms of combined salinity and temperature tolerance was TA2, with shootlets lengths of 3.2 cm (60 Mm NaCl, 22°C), 2.03 cm (60 Mm NaCl, 4°C) and 1.6 cm (60 Mm NaCl, 38°C).

Dynamic molecular regulation of salt stress responses in maize (Zea mays L.) seedlings.

Maize ranks among the most essential crops globally, yet its growth and yield are significantly hindered by salt stress, posing challenges to agricultural productivity. To utilize saline-alkali soils more effectively and enrich maize germplasm resources, identifying salt-tolerant genes in maize is essential. In this study, we used a salt-tolerant maize inbred line, SPL02, and a salt-sensitive maize inbred line, Mo17. We treated both lines with 180 mmol/L sodium chloride (NaCl) for 0 days, 3 days, 6 days, and 9 days at the three-leaf growth stage (V3). Through comprehensive morphological, physiological, and transcriptomic analyses, we assessed salt stress effects and identified hub genes and pathways associated with salt tolerance. Our analysis identified 25,383 expressed genes, with substantial differences in gene expression patterns across the salt treatment stages. We found 8,971 differentially expressed genes (DEGs)-7,111 unique to SPL02 and 4,791 unique to Mo17-indicating dynamic gene expression changes under salt stress. In SPL02, the DEGs are primarily associated with the MAPK signaling pathway, phenylpropanoid biosynthesis, and hormone signaling under salt treatment conditions. In Mo17, salt stress responses are primarily mediated through the abscisic acid-activated signaling pathway and hormone response. Additionally, our weighted gene co-expression network analysis (WGCNA) pinpointed five hub genes that likely play central roles in mediating salt tolerance. These genes are associated with functions including phosphate import ATP-binding protein, glycosyltransferase, and WRKY transcription factors. This study offers valuable insights into the complex regulatory networks governing the maize response to salt stress and identifies five hub genes and pathways for further investigation. These findings contribute valuable knowledge for enhancing agricultural resilience and sustainability in saline-affected environments.

Computational Identification and Characterization of Glycosyltransferase 47 (GT47) Gene Family in Sorghum bicolor and Their Expression Profile in Internode Tissues Based on RNA-Seq Data

Sorghum is an essential crop for biofuel. Many glycosyltransferase (GT) families, including GT47, are involved in the production of both types of polysaccharides. However, a comprehensive study related to the GT47 gene family is needed. The glycosyltransferase (GT) 47 family helps in the synthesis of xylose, pectin, and xyloglucan and plays an essential role in the formation of the proper shape of the plant cell wall. In this study, we performed identification, phylogenetic tree, physiochemical properties, subcellular localization, protein–protein interaction network, detection of motif analysis, gene structure, secondary structure, functional domain, gene duplication, Cis-acting elements, sequence logos, and gene expression profiles based on RNA-sequence analyses in the GT47 gene family. As a result, we identified thirty-one members of the GT47 gene family. The phylogenetic analysis grouped them into three distinct clusters. According to their physiochemical properties, all GT47 proteins were hydrophilic, and their molecular weights ranged from 22.7 to 88.6 kDa. Three essential motifs were identified via motif and conserved domain analysis, emphasizing structural conservation. Subcellular localization was proposed for the various functional roles across cellular compartments. While gene structure analysis showed significant variation in introns–exons, promoter study verified susceptibility to phytohormones like ABA. RNA sequencing revealed that several GT47 genes were highly expressed in internodes, and this was linked to biomass accumulation, cell wall manufacturing, and stem elongation. Analysis of networks of protein–protein interactions and Cis-elements confirmed involvement in stress adaptation and growth regulation. These results contribute to a better understanding of the functional and evolutionary significance of the GT47 gene family in sorghum.

Morphological and Physiological Responses of Sorghum to Drought: Implications for Development of Climate-resilient Cultivars

Drought is a significant environmental stress affecting crop productivity, particularly, in semi-arid regions where sorghum [Sorghum bicolor (L.) Moench] serves as an essential crop for food and fodder. Therefore, it is paramount to evaluate such crop varieties with potential for use in the development of climate-resilient ones through breeding and selection. A greenhouse pot experiment was carried out at Teaching and Research Farm of the School of Agriculture (A. G. Carlson Technology area), University of Cape Coast (UCC), to determine the morpho-physiological responses of seven sorghum varieties, focusing on the stay-green trait under drought-stressed (DS) and well-watered (WW) conditions. Parameters measured included green leaf area (GLA), relative water content (RWC), chlorophyll content, and grain yield. The results showed that the Dorado and Kapaala varieties exhibited greater drought resilience, maintaining higher GLA, RWC, chlorophyll levels and grain yield under drought stress conditions. Strong positive correlations between RWC, GLA, chlorophyll level, and grain yield parameters under DS highlighted these metrics as potential indicators for selecting drought-tolerant sorghum varieties. Thus, sorghum varieties such as Dorado and Kapaala could be employed in breeding programs for the development of climate-resilient varieties. The strong positive correlations between some morphological and physiological characters could be used to indirectly select for improved grain yields. This study underscores the importance of genetic diversity in crop resilience and provides valuable insights for breeding programs aimed at enhancing drought tolerance in sorghum.

Is integrated multi-trophic aquaculture-rice co-culture an unrealistic or feasible approach to providing essential crops, optimizing feed conversion ratio, nitrogen and phosphorus use efficiency?

Is integrated multi-trophic aquaculture-rice co-culture an unrealistic or feasible approach to providing essential crops, optimizing feed conversion ratio, nitrogen and phosphorus use efficiency?

Unlocking Nature's Shield: The Promising Potential of CRISPRa in Amplifying Antimicrobial Peptide Expression in Common Bean (Phaseolus vulgaris L.).

This study proposes using the CRISPR transcriptional activation strategy to modulate the expression of genes encoding defense proteins and antimicrobial peptides (AMPs) in Phaseolus vulgaris. Three genes (PvD1, Pv-thionin, and Pv-lectin) were selected and targeted by the CRISPR-dCas9-TV-mediated transcriptional activation complex in the P. vulgaris L. hairy root. RT-qPCR investigated their activation efficiency. The eGFP-positive transgenic hairy roots exhibit enhanced expression of targeted genes compared to that of control roots. A moderate increase of 1.37-fold in PvD1 gene expression was observed in transgenic hairy roots, while 6.97-fold (Pv-lectin) and 5.70-fold (Pv-thionin) increases were observed. Importantly, no off-target effects of sgRNAs were detected, ensuring the precision and safety of the CRISPR-dCas9-TV strategy. The present article is a proof-of-concept study, and it has succeeded in demonstrating the efficiency of the CRISPR-dCas9-TV strategy in modulating the expression of target genes in P. vulgaris, paving the way for an alternative approach to protecting such essential crop plants.

Rice with a healthier glycaemic profile: Unveiling the molecular mechanisms and breeding strategies for the future.

Rice with a healthier glycaemic profile: Unveiling the molecular mechanisms and breeding strategies for the future.

A Model for Detecting Xanthomonas campestris Using Machine Learning Techniques Enhanced by Optimization Algorithms

The bacterium Xanthomonas campestris poses a significant threat to global agriculture due to its ability to infect leaves, fruits, and stems under various climatic conditions. Its rapid spread across large crop areas results in economic losses, compromises agricultural productivity, increases management costs, and threatens food security, especially in small-scale agricultural systems. To address this issue, this study developed a model that combines fuzzy logic and neural networks, optimized with intelligent algorithms, to detect symptoms of this foliar disease in 15 essential crop species under different environmental conditions using images. For this purpose, Sugeno-type fuzzy inference systems and adaptive neuro-fuzzy inference systems (ANFIS) were employed, configured with rules and clustering methods designed to address cases where diagnostic uncertainty arises due to the imprecision of different agricultural scenarios. The model achieved an accuracy of 93.81%, demonstrating robustness against variations in lighting, shadows, and capture angles, and proving effective in identifying patterns associated with the disease at early stages, enabling rapid and reliable diagnoses. This advancement represents a significant contribution to the automated detection of plant diseases, providing an accessible tool that enhances agricultural productivity and promotes sustainable practices in crop care.

Triple Threat: How Global Fungal Rice and Wheat Pathogens Utilize Comparable Pathogenicity Mechanisms to Drive Host Colonization.

Plant pathogens pose significant threats to global cereal crop production, particularly for essential crops like rice and wheat, which are fundamental to global food security and provide nearly 40% of the global caloric intake. As the global population continues to rise, increasing agricultural production to meet food demands becomes even more critical. However, the production of these vital crops is constantly threatened by phytopathological diseases, especially those caused by fungal pathogens such as Magnaporthe oryzae, the causative agent of rice blast disease, Fusarium graminearum, responsible for Fusarium head blight (FHB) in wheat, and Zymoseptoria tritici, the source of Septoria tritici blotch (STB). All three pathogens are hemibiotrophic, initially colonizing the host through a biotrophic, symptomless lifestyle, followed by causing cell death through the necrotrophic phase. Additionally, they deploy a diverse range of effectors, including proteinaceous and non-proteinaceous molecules, to manipulate fundamental host cellular processes, evade immune responses, and promote disease progression. This review discusses recent advances in understanding the effector biology of these three pathogens, highlighting both the shared functionalities and unique molecular mechanisms they employ to regulate conserved elements of host pathways, such as directly manipulating gene transcription in host nuclei, disrupting reactive oxygen species (ROS) signaling, interfering with protein stability, and undermining host structural integrity. By detailing these complex interactions, the review explores potential targets for innovative control measures and emphasizes the need for further research to develop effective strategies against these destructive pathogens in the face of evolving environmental and agricultural challenges.

Global insights, local applications: irrigation technologies and agricultural drought mitigation in the canadian prairies

The Canadian Prairies face significant water scarcity challenges despite the country's abundant freshwater resources. This scarcity, driven by limited water availability and increasing agricultural demands, makes the region vulnerable to drought. As a major agricultural hub, droughts have led to economic losses and reduced crop productivity. This scoping review examines global drought response measures, focusing on irrigation technologies adaptable for Western Canada. Case studies from Australia, China, and the United States highlight advances in water use efficiency and irrigation technologies, including drip and subsurface drip irrigation (SDI), center-pivot irrigation (CPI), and drought-resistant crop varieties. Examples include Australia's prioritization of essential crops and improved irrigation infrastructure, China's adoption of water-saving rice varieties, and California's use of SDI for water conservation. Adopting these established irrigation techniques could enhance water use efficiency, support food security, and contribute to sustainable water management in the Canadian Prairies. This review underscores the value of integrating global practices to strengthen agricultural resilience in the region.

Hormonal regulation and physiological adjustments of wheat and pea plants under simulated lunar soil conditions.

This study investigates the physiological and morphological responses of wheat (Triticum aestivum) and pea (Pisum sativum) grown in a mixture of lunar soil (LS) simulant and organic soil (OS). The experiment compared the growth of both pea and wheat in 100% organic soil (OS) and a 3:2 mixture of OS and LS (OS: LS). Wheat exhibited increased branching and root growth in OS: LS, while pea plants showed enhanced aerial elongation and altered branch morphology. Photochemical efficiency (Fv/Fm) and pigment concentrations were significantly affected, with both pea and wheat showing reduced chlorophyll content in OS: LS. Oxidative stress indicators, such as lipid peroxidation, exhibited higher levels in pea plants than wheat plants, particularly in the OS: LS mixture. Hormonal analysis performed by LC-MS/MS indicated significant increases in abscisic acid (ABA) and its catabolites in both pea and wheat in OS: LS, suggesting an adaptive response to suboptimal conditions. The results highlight species-specific growth strategies, with wheat investing more in root development and pea plants promoting aerial growth. These findings provide important insights into how essential crops could adapt to extraterrestrial soils, contributing to the development of sustainable agricultural practices for space exploration. Future research should focus on optimising crop performance based on species-specific adaptative responses in mixed-soil environments.

Effect of High-pressure Soaking on the Physicochemical, Nutritional, and Techno-functional Properties of Pearl Millets

Pearl millet is among the few essential crops that have significant nutritional value. Processed pearl millet can add value to various products and improve food and nutritional security. In this...

Sorghum Production in Ethiopia: An Overview of Advances, Successes, and Challenges

Sorghum is an essential crop, particularly significant in semiarid areas with minimal precipitation. It is the fifth most important grain crop globally and originated in Ethiopia, where it underwent diversification. In Ethiopia, sorghum serves multiple purposes, including as a food staple in forms such as popped grain, beer, malted beverages, cooked gruel or porridge, chips, and enjera. It also provides fuel, making it a vital resource for local communities. Sorghum is a critical crop for Ethiopia, contributing significantly to food security, agricultural livelihoods, and the economy. Advances in agronomic practices, breeding programs, and technology adoption have led to improved yields, disease resistance, and drought tolerance, enhancing the crop's resilience in the face of climate variability. Successes in government initiatives, research collaborations, and farmer engagement have facilitated increased sorghum production and diversification of its uses. However, sorghum production faces challenges, including biotic, socioeconomic, and abiotic factors such as diseases, pest insects, drought, and the parasitic weed striga. Soil degradation, limited access to improved seed varieties, inadequate infrastructure, and the ongoing impacts of climate change further hinder productivity. Coordination in Ethiopia is managed by the Melkassa Agricultural Research Center of the Ethiopian Agricultural Research Institute, which oversees the national sorghum breeding program. Through regional and national sorghum improvement initiatives, Ethiopia now has access to a wide variety of open-pollinated and hybrid sorghum varieties suited to diverse agro-ecological settings. This paper discusses these advancements, successes, and challenges in-depth, emphasizing the need for sustained investment in research, policy support, and capacity building to overcome barriers and ensure the long-term sustainability of sorghum production in Ethiopia.

Optimization of High-Density Planting Configurations for Poovan Banana (Musa spp.) in Coconut-Based Agroforestry Systems of the Cauvery Delta Zone

Bananas (Musa spp.) are a vital global agricultural commodity and an essential crop in tropical agricultural systems. The Poovan cultivar, known for its high productivity and adaptability, is particularly effective in intercropping within coconut-based agroforestry systems. This study investigates the impact of planting geometries on crop performance in the Cauvery Delta Zone by evaluating five spatial configurations, ranging from 2.1×2.1m to 0.9×0.9m, with a focus on morphological, physiological, and economic parameters. The results indicate that wider spacing configurations, especially 2.1×2.1m, significantly improve leaf morphological traits, including maximum leaf length (148.17 cm), breadth (77.75 cm), and leaf area index (2.61m²/plant). Additionally, these configurations enhance key fruit quality characteristics, such as increased bunch weight (16kg), improved fruit dimensions (20cm length), higher sugar content (22°Brix), and greater fruit firmness (4.5kg/cm²). The economic analysis suggests that a 1.5×1.5m spacing provides the most favorable cost-benefit ratio (1.14). This study offers valuable insights into the complex relationships between planting density, resource allocation, and productivity in tropical farming systems, providing evidence-based recommendations for optimizing both agricultural performance and economic viability in integrated farming systems.

Leveraging Edge Computing and Deep Learning for the Real-Time Identification of Bean Plant Pathologies

Leveraging Edge Computing and Deep Learning for the Real-Time Identification of Bean Plant Pathologies

Engineering cold resilience: implementing gene editing tools for plant cold stress tolerance.

This paper highlights the need for innovative approaches to enhance cold tolerance. It underscores how genome-editing tools can deepen our understanding of genes involved in cold stress. Cold stress is a significant abiotic factor in high-altitude regions, adversely affecting plant growth and limiting crop productivity. Plants have evolved various mechanisms in response to low temperatures that enable resistance at both physiological and molecular levels during chilling and freezing stress. Several cold-inducible genes have been isolated and characterized, with most playing key roles in providing tolerance against low-temperature stress. However, many plants fail to survive at low temperatures due to the absence of cold acclimatization mechanisms. Conventional breeding techniques, such as inter-specific or inter-genic hybridization, have had limited effectiveness in enhancing the cold resistance of essential crops. Thus, it is crucial to develop crops with improved adaptability, high yields and resistance to cold stress using advanced genomic approaches. The current availability of gene editing tools offers the opportunity to introduce targeted modifications in plant genomes efficiently, thereby developing cold-tolerant varieties. This review discusses advancements in gene editing tools, including zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)/Cas12a(Cpf1), prime editing (PE) and retron library recombineering (RLR). We focus specifically on the CRISPR/Cas system, which has garnered significant attention in recent years as a groundbreaking tool for genome editing across various species. These techniques will enhance our understanding of molecular interactions under low-temperature stress response and highlight the progress of genome editing in designing future climate-resilient crops.

Mapping Crop Types for Beekeepers Using Sentinel-2 Satellite Image Time Series: Five Essential Crops in the Pollination Services

Driven by the widespread adoption of deep learning (DL) in crop mapping with satellite image time series (SITS), this study was motivated by the recent success of temporal attention-based approaches in crop mapping. To meet the needs of beekeepers, this study aimed to develop DL-based classification models for mapping five essential crops in pollination services in Quebec province, Canada, by using Sentinel-2 SITS. Due to the challenging task of crop mapping using SITS, this study employed three DL-based models, namely one-dimensional temporal convolutional neural networks (CNNs) (1DTempCNNs), one-dimensional spectral CNNs (1DSpecCNNs), and long short-term memory (LSTM). Accordingly, this study aimed to capture expert-free temporal and spectral features, specifically targeting temporal features using 1DTempCNN and LSTM models, and spectral features using the 1DSpecCNN model. Our findings indicated that the LSTM model (macro-averaged recall of 0.80, precision of 0.80, F1-score of 0.80, and ROC of 0.89) outperformed both 1DTempCNNs (macro-averaged recall of 0.73, precision of 0.74, F1-score of 0.73, and ROC of 0.85) and 1DSpecCNNs (macro-averaged recall of 0.78, precision of 0.77, F1-score of 0.77, and ROC of 0.88) models, underscoring its effectiveness in capturing temporal features and highlighting its suitability for crop mapping using Sentinel-2 SITS. Furthermore, applying one-dimensional convolution (Conv1D) across the spectral domain demonstrated greater potential in distinguishing land covers and crop types than applying it across the temporal domain. This study contributes to providing insights into the capabilities and limitations of various DL-based classification models for crop mapping using Sentinel-2 SITS.

Unravelling genetic variability for yield and contributing characteristics in green gram [vigna radiata (L.) wilczek] germplasm

Mungbean [Vigna radiata (L.) Wilczek] is an essential crop for food, feed, and income generation in rice-based farming systems across Southeast Asia and other regions. Its popularity stems from its good taste, high nutritional value, and ease of digestion, making it a promising crop for enhancing livelihoods. However, despite its significance, mungbean productivity remains low, primarily due to environmental stresses and a lack of sufficient genetic variability. This study examines the variability, heritability, phenotypic and genotypic coefficient of variation, and genetic advance among yield-contributing traits in green gram germplasm. A total of 450 germplasm lines were evaluated alongside check varieties, revealing significant variation, with the analysis of variance showing notable differences across nearly all traits. The mean sum of squares for the germplasm was highly significant for all phenotypic traits. Several traits exhibited high estimates of heritability and genetic advance, viz., the number of branches/ plants, number of clusters/ plants, number of pods/ clusters, pod length, test weight, and seed yield/plant, indicating their potential for direct selection in breeding programs. These findings suggest that additive gene effects play a dominant role in controlling these traits, with minimal environmental influence, making simple phenotypic selection an effective approach. The results provide valuable insights for advancing green gram breeding programs focused on improving yield and quality through targeted hybridization and trait selection.

Weed community differences in row crops with varying input levels in Ghana

Abstract Peanut (Arachis hypogaea L.) and maize (Zea mays L.) are essential crops for Ghana’s economy and food security, but weed infestation poses a significant threat to their cultivation. Crop rotations influence weed communities, but little is known about these processes in peanut-cropping systems in West Africa. This study investigated the impact of different crop rotations and input levels on weed communities in Ghana over 3 yr. Results showed that low inputs (absence of herbicide and fertilization) favored species richness, while higher input levels (weed control with herbicides and fertilizer use) reduced it. Diversity and evenness were also affected by inputs, with varying patterns across locations and seasons. Weed population growth rates (λ) varied significantly by location and treatment; all management programs resulted in increasing weed populations. Principal component analysis revealed distinct associations between weed species and crop management. The majority of weed species exhibited a generalist behavior and did not associate with a particular management. However, billygoat weed (Ageratum conyzoides L.) and Benghal dayflower (Commelina benghalensis L.) were positively associated with high-input systems, while purple nutsedge (Cyperus rotundus L.) exhibited strong associations with low and medium inputs. The weed–crop rotation dynamics described here demonstrate how management drives the selection of weed species that are more pervasive and interfere with important food crops in Ghanaian agriculture.

Genomic selection for agronomical phenotypes using genome-wide SNPs and SVs in pearl millet.

Pearl millet is an essential crop worldwide, with noteworthy resilience to abiotic stress, yet the advancement of its breeding remains constrained by the underutilization of molecular-assisted breeding techniques. In this study, we collected 1,455,924 single nucleotide polymorphism (SNP) and 124,532 structural variant (SV) markers primarily from a pearl millet inbred germplasm association panel consisting of 242 accessions including 120 observed phenotypes, mostly related to the yield. Our findings revealed that the SV markers had the capacity to capture genetic diversity not discerned by SNP markers. Furthermore, no correlation in heritability was observed between SNP and SV markers associated with the same phenotype. The assessment of the nine genomic prediction models revealed that SV markers performed better than SNP markers. When using the SV markers as the predictor variable, the genomic BLUP model achieved the best performance, while using the SNP markers, Bayesian methods outperformed the others. The integration of these models enabled the identification of eight candidate accessions with high genomic estimated breeding values (GEBV) across nine phenotypes using SNP markers. Four candidate accessions were identified with high GEBV across 22 phenotypes using SV markers. Notably, accession 'P23' emerged as a consistent candidate predicted based on both SNP and SV markers specifically for panicle number. These findings contribute valuable insights into the potential of utilizing both SNP and SV markers for genomic prediction in pearl millet breeding. Moreover, the identification of promising candidate accessions, such as 'P23', underscores the accelerated prospects of molecular breeding initiatives for enhancing pearl millet varieties.