Nanomaterials. Effective tools for field and horticultural crops to cope with drought stress: A review

Drought is the most serious environmental challenge that limits plant growth and causes more severe yield losses than other abiotic stress factors resulting in a serious food shortage. Nanomaterials (NMs) are considered as vital tools to overcome contemporary and future challenges in agricultural production. Recently, NMs have been applied for enhancing seed germination, growth, physiology, productivity and quality attributes of various crops under normal or stress conditions. Up to date, there is no a comprehensive review about the potential role of NMs in attenuating the drought-induced adverse effects in crop plants. Thus, this review will highlight this issue. Generally, NMs minimize drought-induced osmotic stress by accumulation of osmolytes that result in osmotic adjustment and improved plant water status. In addition, NMs play a key role to improve root growth, conductive tissue elements and aquaporin proteins facilitating uptake and translocation of water and nutrients. Furthermore, NMs reduce water loss by stomatal closure due to abscisic acid signaling. However, this leads to reduced photosynthesis and oxidative stress damage. At the same time, NMs increase the content of light-harvesting pigments, enzymatic and non-enzymatic antioxidants leading to enhancing photosynthesis with reducing oxidative stress damage. Overall, NMs can ameliorate the deleterious effects of drought stress in crop plants by regulation of gene expression and alternation of various physiological and biochemical processes

Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt

Monitoring strategic agricultural crops in terms of crop growth performance, by accurate cost-effective and quick tools is crucially important in site-specific management to avoid crop reductions. The availability of commercial high resolution satellite images with high resolution (spatial and spectral) as well as in situ spectra measurements can help decision takers to have deep insight on crop stress in a certain region. The research attempts to examine remote sensing dataset for forecasting wheat crop (Sakha 61) characteristics including the leaf area index (LAI), plant height (plant-h), above ground biomass (AGB) and Soil Plant Analysis Development (SPAD) value of wheat across non-stress, drought and salinity-induced stress in the Nile Delta region. In this context, the ability of in situ spectroradiometry measurements and QuickBird high resolution images was evaluated in our research. The efficiency of Random Forest (RF) and Artificial Neural Network (ANN), mathematical models was assessed to estimate the four measured wheat characteristics based on vegetation spectral reflectance indices (V-SRIs) extracted from both approaches and their interactions. Field surveys were carried out to collect in situ spectroradiometry measurements concomitant with the acquisition of QuickBird imagery. The results demonstrated that several V-SRIs extracted from in situ spectroradiometry data and the QuickBird image correlated with the LAI, plant-h, AGB, and SPAD value of wheat crop across the study site. The determination coefficient (R2) values of the association between V-SRIs of in situ spectroradiometry data and various determined wheat characteristics varied from 0.26 to 0.85. The ANN-GSIs-3 was found to be the optimum predictive model, demonstrating a greater relationship between the advanced features and LAI. The three features of V-SRIs comprised in this model were strongly significant for the prediction of LAI. The attained results indicated high R2 values of 0.94 and 0.86 for the training and validation phases. The ANN-GSIs-3 model constructed for the determination of chlorophyll in the plant which had higher performance expectations (R2 = 0.96 and 0.92 for training and validation datasets, respectively). In conclusion, the results of our study revealed that high resolution remote sensing images such as QuickBird or similar imagery, and in situ spectroradiometry measurements have the feasibility of providing necessary crop monitoring data across non-stressed and stressed (drought and salinity) conditions when integrating V-SRIs with ANN and RF algorithms

Polyphasic Characterization of Four Aspergillus Species as Potential Biocontrol Agents for White Mold Disease of Bean

The genus Aspergillus comprises several species that play pivotal roles in agriculture. Herein, we morphologically and physiologically characterized four genetically distinct Aspergillus spp., namely A. japonicus, A. niger, A. flavus, and A. pseudoelegans, and examined their ability to suppress the white mold disease of bean caused by Sclerotinia sclerotiorum in vitro and under greenhouse conditions. Seriation type of Aspergillus spp. correlates with conidiospores discharge as detected on the Petri glass lid. Members of Nigri section cover their conidial heads with hard shells after prolonged incubation. In addition, sporulation of the tested Aspergillus isolates is temperature sensitive as it becomes inhibited at low temperatures and the colonies become white. Examined Aspergillus spp. were neither infectious to legumes nor aflatoxigenic as confirmed by HPLC except for A. flavus and A. pseudoelegans which, secreted 5 and 1 ppm of aflatoxin B1, respectively. Co-inoculations of Sclerotinia’s mycelium or sclerotia with a spore suspension of Aspergillus spp. inhibited their germination on PDA at 18 °C and 28 °C, and halted disease onset on detached common bean and soybean leaves. Similarly, plants treated with A. japonicus and A. niger showed the highest survival rates compared to untreated plants. In conclusion, black Aspergillus spp. are efficient biocides and safe alternatives for the management of plant diseases, particularly in organic farms

Nanomaterials. Effective tools for field and horticultural crops to cope with drought stress: A review

Drought is the most serious environmental challenge that limits plant growth and causes more severe yield losses than other abiotic stress factors resulting in a serious food shortage. Nanomaterials (NMs) are considered as vital tools to overcome contemporary and future challenges in agricultural production. Recently, NMs have been applied for enhancing seed germination, growth, physiology, productivity and quality attributes of various crops under normal or stress conditions. Up to date, there is no a comprehensive review about the potential role of NMs in attenuating the drought-induced adverse effects in crop plants. Thus, this review will highlight this issue. Generally, NMs minimize drought-induced osmotic stress by accumulation of osmolytes that result in osmotic adjustment and improved plant water status. In addition, NMs play a key role to improve root growth, conductive tissue elements and aquaporin proteins facilitating uptake and translocation of water and nutrients. Furthermore, NMs reduce water loss by stomatal closure due to abscisic acid signaling. However, this leads to reduced photosynthesis and oxidative stress damage. At the same time, NMs increase the content of light-harvesting pigments, enzymatic and non-enzymatic antioxidants leading to enhancing photosynthesis with reducing oxidative stress damage. Overall, NMs can ameliorate the deleterious effects of drought stress in crop plants by regulation of gene expression and alternation of various physiological and biochemical processes

Multi-Indicator and Geospatial Based Approaches for Assessing Variation of Land Quality in Arid Agroecosystems

Novel spatial models for appraising arable land resources using data processing techniques can increase insight into agroecosystem services. Hence, the principal component analysis (PCA), hierarchal cluster analysis (HCA), analytical hierarchy process (AHP), fuzzy logic, and geographic information system (GIS) were integrated to zone and map agricultural land quality in an arid desert area (Matrouh Governorate, Egypt). Satellite imageries, field surveys, and soil analyses were employed to define eighteen indicators for terrain, soil, and vegetation qualities, which were then reduced through PCA to a minimum data set (MDS). The original and MDS were weighted by AHP through experts’ opinions. Within GIS, the raster layers were generated, standardized using fuzzy membership functions (linear and non-linear), and assembled using arithmetic mean and weighted sum algorithms to produce eight land quality index maps. The soil properties (pH, salinity, organic matter, and sand), slope, surface roughness, and vegetation could adequately express the land quality. Accordingly, the HCA could classify the area into eight spatial zones with significant heterogeneity. Selecting salt-tolerant crops, applying leaching fraction, adopting sulfur and organic applications, performing land leveling, and using micro-irrigation are the most recommended practices. Highly significant (p < 0.01) positive correlations occurred among all the developed indices. Nevertheless, the coefficient of variation (CV) and sensitivity index (SI) confirmed the better performance of the index developed from the non-linearly scored MDS and weighted sum model. It could achieve the highest discrimination in land qualities (CV > 35%) and was the most sensitive (SI = 3.88) to potential changes. The MDS within this index could sufficiently represent TDS (R2 = 0.88 and Kappa statistics = 0.62), reducing time, effort, and cost for estimating the land performance. The proposed approach would provide guidelines for sustainable land-use planning in the studied area and similar regions

Hydroxylated Cinnamates Enhance Tomato Resilience to <i>Alternaria alternata</i>, the Causal Agent of Early Blight Disease, and Stimulate Growth and Yield Traits

The important vegetable crop, tomato, is challenged with numerous abiotic and biotic stressors, particularly the newly emerged fungicide-resistant strains of phytopathogenic fungi such as Alternaria alternata, the causal agent of early blight disease. The current study investigated the potential antifungal activity of four cinnamate derivatives including cinnamic acid, ρ-coumaric acid, caffeic acid, and ferulic acid against A. alternata. Our in vitro findings showed that all tested compounds exhibited dose-dependent fungistatic action against A. alternata when their concentrations were increased from 0.1, 0.3, 0.5, and 0.7, to 0.9 mM, respectively. The high concentration of ferulic acid (0.9 mM) completely inhibited the radial mycelial growth of A. alternata and it was comparable to the positive control (difenoconazole fungicide). Additionally, under greenhouse conditions, foliar application of the four tested cinnamates significantly reduced the severity of early blight disease without any phytotoxicity on treated tomato plants. Moreover, it significantly improved the growth traits (plant height, total leaf area, number of leaves per plant, and shoot fresh weight), total chlorophyll, and yield components (number of flowers per plant, number of fruits per plant, and fruit yield) of treated A. alternata-infected plants. Collectively, our findings suggest that cinnamate derivatives could be good candidates as eco-friendly alternatives to reduce the use of chemical fungicides against A. alternata

Geographical Correlation and Genetic Diversity of Newly Emerged Races within the Ug99 Lineage of Stem Rust Pathogen, <i>Puccinia graminis</i> f. sp. <i>tritici</i>, in Different Wheat-Producing Areas

Wheat stem rust caused by Puccinia graminis f. sp. tritici is one of the most destructive wheat diseases worldwide. Identifying stem rust races in general, Ug99 lineage particularly, and determining resistance genes are critical goals for disease assessment. Thirty wheat varieties and monogenic lines with major stem rust resistance genes (Sr) were examined here over the course of three succeeding seasons from 2020 to 2022. Fourteen stem rust races have been identified in ten African countries, as well as Central and West Asia and North Africa (CWANA) and ten European countries. The Ug99 group (Clade I) included four races (TTKSK, TTKST, TTKTK, and TTKTT) and was reported in five African countries (Egypt, Kenya, Rwanda, Tanzania, and Uganda) and Iran, but none of the European countries. On the other hand, none of the races in Clade III-B (TTRTF) and Clade IV-B (TKTTF and TTTTF) were found in Egypt. Furthermore, Egyptian races were clustered separately from races identified from other countries, and six races were found only in Egypt, including PKSTC, RKTTH, TKTTC, TTTSK, TCKTC, and TKTTH. Races from Kenya, Tanzania, Uganda, Rwanda, and Iran were all closely associated with one another, according to correlation analysis. However, most races identified from other investigated regions, including Eritrea, Spain, Ethiopia, Morocco, Italy, Poland, Kenya, Tanzania, and Uganda, were adversely linked with Egyptian races. The diagnostic 350 bp long PCR fragment linked with virulence to Sr31, Clement (Sr31), and Brigardier (Sr31) was used to identify the TTKSK (Ug99) race. The identification of the regional associations and genetic diversity of newly emerged races within the Ug99 lineage of P. graminis tritici in Africa, Asia, and Europe is one of the key goals of this study. It will help plant breeders to develop new resistant lines against the virulent races, especially TTKSK (Ug99) and TTTSK. This helps in ensuring global food security in the context of climate change

Effect of Three Water Regimes on the Physiological and Anatomical Structure of Stem and Leaves of Different Citrus Rootstocks with Distinct Degrees of Tolerance to Drought Stress

Citrus is grown globally throughout the subtropics and semi-arid to humid tropics. Abiotic stresses such as soil water deficit negatively affect plant growth, physiology, biochemistry, and anatomy. Herein, we investigated the effect(s) of three water regimes (control, moderate drought, and severe drought) on the physiological and anatomical structure of 10 different citrus rootstocks with different degrees of tolerance to drought stress. Brazilian sour orange and Gadha dahi performed well by avoiding desiccation and maintaining plant growth, plant water status, and biochemical characters, while Rangpur Poona nucellar (C. limonia) and Sunki × bentake were the most sensitive rootstocks at all stress conditions. At severe water stress, the highest root length (24.33 ± 0.58), shoot length (17.00 ± 1.00), root moisture content (57.67 ± 1.53), shoot moisture content (64.59 ± 1.71), and plant water potential (−1.57 ± 0.03) was observed in tolerant genotype, Brazilian sour orange. Likewise, chlorophyll a (2.70 ± 0.06), chlorophyll b (0.87 ± 0.06) and carotenoids (0.69 ± 0.08) were higher in the same genotype. The lowest H2O2 content (77.00 ± 1.00) and highest proline content (0.51 ± 0.06) were also recorded by Brazilian sour orange. The tolerance mechanism of tolerant genotypes was elucidated by modification in anatomical structures. Stem anatomy at severe drought, 27.5% increase in epidermal cell thickness, 25.4% in vascular bundle length, 30.5% in xylem thickness, 27.7% in the phloem cell area, 8% in the pith cell area, and 43.4% in cortical thickness were also observed in tolerant genotypes. Likewise, leaf anatomy showed an increase of 27.9% in epidermal cell thickness, 11.4% in vascular bundle length, 21% in xylem thickness, and 15% in phloem cell area in tolerant genotypes compared with sensitive ones. These modifications in tolerant genotypes enabled them to maintain steady nutrient transport while reducing the risk of embolisms, increasing water-flow resistance, and constant transport of nutrients across

Durability of Adult Plant Resistance Gene <i>Yr18</i> in Partial Resistance Behavior of Wheat (<i>Triticum aestivum</i>) Genotypes with Different Degrees of Tolerance to Stripe Rust Disease, Caused by <i>Puccinia striiformis</i> f. sp. <i>tritici</i>: A Five-Year Study

Adult plant resistance in wheat is an achievement of the breeding objective because of its durability in comparison with race-specific resistance. Partial resistance to wheat stripe rust disease was evaluated under greenhouse and field conditions during the period from 2016 to 2021. Misr 3, Sakha 95, and Giza 171 were the highest effective wheat genotypes against Puccinia striiformis f. sp. tritici races. Under greenhouse genotypes, Sakha 94, Giza 168, and Shandaweel1 were moderately susceptible, had the longest latent period and lowest values of the length of stripes and infection frequency at the adult stage. Partial resistance levels under field conditions were assessed, genotypes Sakha 94, Giza 168, and Shandaweel1 exhibited partial resistance against the disease. Leaf tip necrosis (LTN) was noted positively in three genotypes Sakha 94, Sakha 95, and Shandaweel1. Molecular analyses of Yr18 were performed for csLV34, cssfr1, and cssfr2 markers. Only Sakha 94 and Shandaweel1 proved to carry the Yr18 resistance allele at both phenotypic and genotypic levels. Scanning electron microscopy (SEM) observed that the susceptible genotypes were colonized extensively on leaves, but on the slow-rusting genotype, the pustules were much less in number, diminutive, and poorly sporulation, which is similar to the pustule of NIL Jupateco73 ‘R’

Investigating the Phenotypic Plasticity of the Invasive Weed <i>Trianthema portulacastrum</i> L.

Phenotypic plasticity is frequently highlighted as a key factor in plant invasiveness, as it enables invasive species to adapt to diverse, complicated habitats. Trianthema portulacastrum is one of the most common aggressive species that threaten different crops around the world. Phenotypic plasticity in T. portulacastrum was investigated by comparing variation in germination, vegetative macromorphology, photosynthetic pigments, stomatal complexes, and seed micromorphological traits of 35 samples collected from 35 different localities. One-way cluster analysis and principal component analysis (PCA) were used to classify samples into homogeneous groups based on the measured traits. Pairwise statistical comparisons were conducted between the three resulting groups. The phenotypic plasticity index (PI) was calculated and compared among different groups of characters. Results showed that photosynthetic pigments and macromorphological characteristics had the highest PI, followed by seed micromorphology, and then stomatal complex traits, while germination parameters showed the lowest PI. We propose that soil moisture, salinity, and temperature are the most determinative and explanative variables of the variation between the three classified groups. We strongly believe that the phenotypic plasticity of T. portulacastrum will support species abundance and spread even under expected changes in climatic conditions, in contrast to the vulnerable traditional crops