Crop Stress Research Articles

Detecting Water Stress in Winter Wheat Based on Multifeature Fusion from UAV Remote Sensing and Stacking Ensemble Learning Method

The integration of remote sensing technology and machine learning algorithms represents a new research direction for the rapid and large-scale detection of water stress in modern agricultural crops. However, in solving practical agricultural problems, single machine learning algorithms cannot fully explore the potential information within the data, lacking stability and accuracy. Stacking ensemble learning (SEL) can combine the advantages of multiple single machine learning algorithms to construct more stable predictive models. In this study, threshold values of stomatal conductance (gs) under different soil water stress indices (SWSIs) were proposed to assist managers in irrigation scheduling. In the present study, six irrigation treatments were established for winter wheat to simulate various soil moisture supply conditions. During the critical growth stages, gs was measured and the SWSI was calculated. A spectral camera mounted on an unmanned aerial vehicle (UAV) captured reflectance images in five bands, from which vegetation indices and texture information were extracted. The results indicated that gs at different growth stages of winter wheat was sensitive to soil moisture supply conditions. The correlation between the gs value and SWSI value was high (R2 > 0.79). Therefore, the gs value threshold can reflect the current soil water stress level. Compared with individual machine learning models, the SEL model exhibited higher prediction accuracy, with R2 increasing by 6.67–17.14%. Using a reserved test set, the SEL model demonstrated excellent performance in various evaluation metrics across different growth stages (R2: 0.69–0.87, RMSE: 0.04–0.08 mol m−2 s−1; NRMSE: 12.3–23.6%, MAE: 0.03–0.06 mol m−2 s−1) and exhibited excellent stability and accuracy. This research can play a significant role in achieving large-scale monitoring of crop growth status through UAV, enabling the real-time capture of winter wheat water deficit changes, and providing technical support for precision irrigation.

Trivalent chromium stress trigger accumulation of secondary metabolites in rice plants: Integration of biochemical and transcriptomic analysis

Trivalent chromium [Cr (III)] is a frequently detected environmental contaminant that negatively affects plant metabolism, growth, and yield. Plant secondary metabolites are non-nutrient compounds involved in diverse physiological functions in response to abiotic stresses. This study performed biochemical and transcriptomic analyses to clarify the protective role and mechanism of secondary metabolites in rice seedlings under Cr(III) stress. The content of measured secondary metabolites i.e., total soluble phenolics, flavonoids, lignin, and anthocyanin in rice tissues was significantly enhanced under Cr(III) exposure. Additionally, the activities of several enzymes including chalcone synthase, phenylalanine ammonialyase, peroxidase, and anthocyanidin synthase, were positively activated. Transcriptomic analysis revealed a number of differentially expressed genes (DEGs) in Cr(III)-treated rice seedlings and their expression patterns are tissue-specific. Additionally, the DEGs involved in secondary metabolism pathways were evident after KEGG enrichment analysis. Cr(III) exposure resulted in distinct genetic regulation strategies in rice tissues, with different DEGs activating various sub-pathways in the secondary metabolism pathways to cope with Cr(III) stress. Furthermore, the integrated correlation analysis of the secondary metabolites and transcriptome data identified key genes involved in different steps of the sub-pathways of secondary metabolism pathway in rice plants under Cr(III) stress. This study indicates that the accumulation of secondary metabolites in rice plants is a survival and detoxification strategy to reduce the adverse effects of toxic compounds. Future research should explore how key genes in secondary metabolism pathways aid in Cr(III) detoxification and enhance crop stress tolerance.

Determination of drought resistance of miniature rose varieties

ABSTRACT The researchers aimed to determine the effects of different irrigation levels on plant water consumption (ET), physiological, morphological and biomass traits of four different miniature rose varieties (Rosa Spp, cv. Mandarin, Orange Juwel, Zwergen Fee 09 and Zwergkönig 78). Four different irrigation levels (100% (control), 75%, 50%, 25%) were created in the experiment. The research was carried out at Çanakkale Onsekiz Mart University, Crop Stress Monitoring and Thermography Laboratory in 2020–2021. Water stress negatively affected the physiological and morphological traits measured in all four varieties. The six-month ET values of Mandarin, Orange Juwel, Zwergen Fee 09 and Zwerkönig 78 miniature rose varieties were 255.7–642.3 mm, 293.6–796.3 mm, 277.3–736.2 mm and 261.8–675.9 mm, respectively. Mandarin is more resistant to drought because its ET values are lower than other varieties.

Mitigating effects of Nigeria seaweed phytonutrients on biochemical and physiological conditions of Lycopersicon esculentum under heavy metal-induced abiotic stress

Abiotic stress has become a significant issue in recent years, affecting various physiological and biochemical aspects of crops and threatening food security. This study aimed to investigate the effects of seaweed on the biochemical and physiological conditions of Lycopersicon esculentum under heavy metal-induced abiotic stress. Lycopersicon esculentum plants were grown in greenhouse bags for four weeks and then exposed to 0.10M Pb Nitrate. They were divided into six groups: one control group sprayed with tap water and five experimental groups sprayed with different seaweed concentrations (0%, 20%, 40%, 60%, and 80%). Results showed that abiotic stress led to notable decreases in root length, shoot length, chlorophyll a, chlorophyll b, stomatal conductance, photosynthetic rate, Rubisco activity, and carotenoids by 48%, 47% 38%, 65%, 61%, 77%, 75%, and 68%, respectively. Seaweed treatment improved these indices, with the 80% seaweed group showing increases of 27%, 21%, 44%, 36%, 56%, and 48%, 54% after 21 days. Additionally, seaweed application enhanced antioxidant activities in the roots (SOD by 71%, CAT by 45%, POD by 51%, and APX by 92%) and in the leaves (SOD by 18%, CAT by 26%, POD by 34%, APX by 58%) compared to the control. The study concluded that seaweeds significantly mitigated oxidative stress in plants, boosting growth, antioxidant potential, mineral absorption, and osmotic protection. Nigeria seaweeds could be a promising tool to enhance food production by reducing oxidative stress in crops.

Tissue-Specific Regulation of Vesicular Trafficking Mediated by Rab-GEF Complex MON1/CCZ1 From Solanum chilense Increases Salt Stress Tolerance in Arabidopsis thaliana.

Salt stress constrains the development and growth of plants. To tolerate it, mechanisms of endocytosis and vacuolar compartmentalization of Na+ are induced. In this work, the genes that encode a putative activator of vesicular trafficking called MON1/CCZ1 from Solanum chilense, SchMON1 and SchCCZ1, were co-expressed in roots of Arabidopsis thaliana to determine whether the increase in prevacuolar vesicular trafficking also increases the Na+ compartmentalization capacity and tolerance. Initially, we demonstrated that both SchMON1 and SchCCZ1 genes rescued the dwarf phenotype of both A. thaliana mon1-1 and ccz1a/b mutants associated with the loss of function, and both proteins colocalized with their functional targets, RabF and RabG, in endosomes. Transgenic A. thaliana plants co-expressing these genes improved salt stress tolerance compared to wild type plants, with SchMON1 contributing the most. At the sub-cellular level, co-expression of SchMON1/SchCCZ1 reduced ROS levels and increased endocytic activity, and number of acidic structures associated with autophagosomes. Notably, greater Na+ accumulation in vacuoles of cortex and endodermis was evidenced in the SchMON1 genotype. Molecular analysis of gene expression in each genotype supported these results. Altogether, our analysis shows that root activation of prevacuolar vesicular trafficking mediated by MON1/CCZ1 emerges as a promising physiological molecular mechanism to increase tolerance to salt stress in crops of economic interest.

Effects of nickel, lead, and copper stress on the growth and biochemical responses of Aegilops tauschii seedlings

Heavy metal pollution causes severe abiotic stress in cereal crops around the world. This study investigated the effects of different concentrations (0, 100, 200, and 300 mg·kg–1) of nickel, lead, and copper stress on the growth and biochemical responses of Aegilops tauschii seedlings, to provide a reference for research on the mechanism of invasion and screening potential sources of wheat tolerance genes. The results showed that nickel, lead, and copper stress caused a significant decrease in the contents of chlorophyll a, chlorophyll b, and chlorophyll (a + b) in A. tauschii, thereby inhibiting photosynthesis to different degrees and hindering seedling growth, which was reflected in significant reductions in plant height and root length, with the most notable effect observed under stress by 300 mg·kg–1 lead. As the concentration of heavy metals increased, the activities of antioxidant enzymes (SOD, POD, and APX), non-enzymatic antioxidants (GSH and AsA), and the contents of osmotic regulatory substances (proline and soluble proteins) in A. tauschii significantly increased. Additionally, heavy metal stress increased H2O2 and TBARS levels. However, when the nickel, lead, and copper concentrations reached 300 mg·kg–1, no significant differences were found in H2O2 or TBARS levels compared to those in the CK group. To summarize, A. tauschii can mitigate the accumulation of ROS and membrane lipid peroxidation caused by heavy metal stress through self-regulation, thus exhibiting a certain degree of tolerance to stress caused by different concentrations of nickel, lead, and copper. Finally, the evaluation using the membership function method revealed that among the three heavy metals, A. tauschii exhibited the strongest adaptation to Cu, followed by Ni and Pb.

Cerium Oxide Nanoparticles (CeO2 NPs) Enhance Salt Tolerance in Spearmint (Mentha spicata L.) by Boosting the Antioxidant System and Increasing Essential Oil Composition

Salinity represents a considerable environmental risk, exerting deleterious effects on horticultural crops. Nanotechnology has recently emerged as a promising avenue for enhancing plant tolerance to abiotic stress. Among nanoparticles, cerium oxide nanoparticles (CeO2 NPs) have been demonstrated to mitigate certain stress effects, including salinity. In the present study, the impact of CeO2 NPs (0, 25, and 100 mg L−1) on various morphological traits, photosynthetic pigments, biochemical parameters, and the essential oil profile of spearmint plants under moderate (50 mM NaCl) and severe (100 mM NaCl) salinity stress conditions was examined. As expected, salinity reduced morphological parameters, including plant height, number of leaves, fresh and dry weight of leaves and shoots, as well as photosynthetic pigments, in comparison to control. Conversely, it led to an increase in the content of proline, total phenols, malondialdehyde (MDA), hydrogen peroxide (H2O2), and antioxidant enzyme activities. In terms of CeO2 NP applications, they improved the salinity tolerance of spearmint plants by increasing chlorophyll and carotenoid content, enhancing antioxidant enzyme activities, and lowering MDA and H2O2 levels. However, CeO2 NPs at 100 mg L−1 had adverse effects on certain physiological parameters, highlighting the need for careful consideration of the applied concentration of CeO2 NPs. Considering the response of essential oil compounds, combination of salinity stress and CeO2 treatments led to an increase in the concentrations of L-menthone, pulegone, and 1,8-cineole, which are the predominant compounds in spearmint essential oil. In summary, foliar application of CeO2 NPs strengthened the resilience of spearmint plants against salinity stress, offering new insights into the potential use of CeO2 NP treatments to enhance crop stress tolerance.

Genome-Wide Identification and Expression Analysis of the PsTPS Gene Family in Pisum sativum

This study aimed to explore the role of the trehalose-6-phosphate synthase (TPS) gene family in the adaptation of peas to environmental stress. A comprehensive analysis of the PsTPS gene family identified 20 genes with conserved domains and specific chromosomal locations. Phylogenetic analysis delineated evolutionary relationships, while gene structure analysis revealed compositional insights, and motif analysis provided functional insights. Cis-regulatory element identification predicted gene regulation patterns. Tissue-specific and stress-induced expression profiling highlighted eight genes with ubiquitous expression, with PsTPS15 and PsTPS18 displaying elevated expression levels in roots, nodules, and young stems, and PsTPS13 and PsTPS19 expression downregulated in seeds. Transcriptome analysis identified a differential expression of 20 PsTPS genes, highlighting the significance of 14 genes in response to drought and salinity stress. Notably, under drought conditions, the expression of PsTPS4 and PsTPS6 was initially upregulated and then downregulated, whereas that of PsTPS15 and PsTPS19 was downregulated. Salinity stress notably altered the expression of PsTPS4, PsTPS6, and PsTPS19. Taken together, these findings elucidate the regulatory mechanisms of the PsTPS gene family and their potential as genetic targets for enhancing crop stress tolerance.

Alleviative effect of iron chlorin e6 on isoproturon phytotoxicity to wheat

Abstract Isoproturon phytotoxicity to wheat (Triticum aestivum L.) is a worry for many farmers in chemical control of weeds in wheat fields, especially in subzero weather conditions. Iron chlorin e6 (ICe6), a new plant growth regulator, has been reported to enhance crop stress resistance to alleviate damage caused by stress; however, it is not clear whether ICe6 has an alleviative effect on isoproturon phytotoxicity to wheat. We determined the alleviative effect of ICe6 on isoproturon phytotoxicity to wheat, and 0.018 g ai ha−1 was the optimal dose. Meanwhile, we also studied the photosynthetic pigment content, photosynthetic parameters, oxidative stress indicators, and antioxidant enzyme activity of wheat treated with the three different treatments. We found that the photosynthetic pigment content, antioxidant enzyme activity, and photosynthesis of wheat damaged by isoproturon were significantly lower than those of the control, and the hydrogen peroxide (H2O2) and malondialdehyde (MDA) content increased. These results indicate that isoproturon stress significantly weakened the photosynthetic and antioxidant capacity of wheat. The photosynthetic pigment content, photosynthetic parameters (excluding intercellular CO2 concentration), and antioxidant enzyme activity of isoproturon+ICe6– treated wheat were significantly higher than those of isoproturon-treated wheat. The H2O2 and MDA content was significantly lower than that of isoproturon-treated wheat. These results indicate that ICe6 treatment maintained the photosynthetic pigment content of wheat and relatively improved photosynthetic capacity, allowing photosynthesis to proceed normally. ICe6 treatment also limits the decrease in antioxidant enzyme activity, effectively clearing excess reactive oxygen species and ultimately alleviating membrane lipid peroxidation damage. In summary, ICe6 not only enhances stress resistance and increases yield in crops such as soybean [Glycine max (L.) Merr.] and canola (Brassica napus L.), but also has an alleviating effect on the isoproturon phytotoxicity to wheat, which is manifested by the improvement of photosynthetic and antioxidant abilities, ultimately leading to an increase in wheat shoot height and shoot fresh weight.

Harnessing the potential of copper-based nanoparticles in mitigating abiotic and biotic stresses in crops.

The demand for crops production continues to intensify with the rapid increase in population. Agricultural crops continue to encounter abiotic and biotic stresses, which can substantially hamper their productivity. Numerous strategies have been focused to tackle the abiotic and biotic stress factors in various plants. Nanotechnology has displayed great potential to minimize the phytotoxic impacts of these environmental constraints. Copper (Cu)-based nanoparticles (NPs) have displayed beneficial effects on plant growth and stress tolerance. Cu-based NPs alone or in combination with plant growth hormones or microorganisms have been documented to induce plant tolerance and mitigate abiotic or biotic stresses in different plants. In this review, we have comprehensively discussed the uptake and translocation of Cu-based NPs in plants, and beneficial roles in improving the plant growth and development at various growth stages. Moreover, we have discussed how Cu-based NPs mechanistically modulate the physiological, biochemical, metabolic, cellular, and metabolic functions to enhance plant tolerance against both biotic (viruses, bacterial and fungal diseases, etc.) and abiotic stresses (heavy metals or metalloids, salt, and drought stress, etc.). We elucidated recent advancements, knowledge gaps, and recommendations for future research. This review would help plant and soil scientists to adapt Cu-based novel strategies such as nanofertilizers and nanopesticides to detoxify the abiotic or biotic stresses. These outcomes may contribute to the promotion of healthy food production and food security, thus providing new avenues for sustainable agriculture production.

Comparative effects of micron-sized silicon sources and Si nanoparticles on growth, defense system and cadmium accumulation in wheat (Triticum aestivum L.) cultivated in Cd contaminated soil

Elevated levels of cadmium (Cd) in soils posesignificant challenges to global agricultural crop production. The potential of silicon (Si) nanoparticles (NPs) and biogenic Si sources of different sizes to mitigate Cd stress in wheat remains largely unexplored. A pot experiment was conducted to evaluate the effectiveness of various sizes of biogenic Si sources: rice husk biochar (RHB), sugarcane bagasse (SB), and rice straw (RS); categorized by particle size (<150 μm, 150–250 μm, and 250–1680 μm, denoted as S1, S2, and S3, respectively), and Si NPs on wheat growth and Cd accumulation. The application of RHB (<150 μm) significantly increased plant height (105 %), spike length (94 %), shoot dry weight (93 %), root dry weight (83 %), and grain weight (89 %) compared to the control. The RHBS1 treatment delivered the greatest reduction in the bioavailable fraction of soil Cd (-74 %), as well as Cd levels in roots (-85 %), shoots (-93 %), and grains (-97 %) compared to the polluted control. Additionally, RHB (<150 μm) showed the highest increase in antioxidant enzyme activities compared to the Cd-spiked treatment. Interestingly, the various biogenic Si sources have the potential to mitigate Cd stress in wheat plants. Further research is required to understand the underlying mechanisms and to investigate the effectiveness of different biogenic Si sources and particle sizes in alleviating Cd stress in crops.

Identifying Crop Distress and Stress-Induced Plant Diseases Using Hyper Spectral Image Analysis

The purpose of this study is to determine whether hyper spectral images can be used to identify plant diseases and crop pressure from aerial photographs. With extensive research on the prevalent methods used closer to the problem, this study offers a potent strategy for identifying crop distress and illnesses using this efficient imaging technique. To identify the spectral fingerprints of common indications and symptoms of plant diseases and crop strains, this study evaluates the available hyper spectral photo datasets. After that, the data are examined using two learning algorithms—the highly randomized trees and the Random Woodland set of rules—to create predictions that are entirely dependent on the results that are discovered. In the end, a benchmarked set of test statistics is used to assess the prediction accuracy. The results of this study show that hyper spectral photo evaluation has a strong and promising utility for crop stress and disease identification. Hyper spectral light evaluation is a method for identifying plant diseases caused by strain on crops. By gathering and evaluating high-dimensional spectral reflection data from satellite or aircraft structures, details regarding the physiological homes of flowers can be identified. The health of plants, illnesses brought on by stress, and agricultural productivity predictions can all be made using these facts. Hyper spectral recordings can also be used to create actions that reduce agricultural losses and enhance the health of plants that are prone to disease.

ROLE OF BIOTECHNOLOGY IN ABIOTIC STRESS TOLERANCE IN PLANTS

As population grows, abiotic stresses reduce plant growth and agricultural output, affecting global food security. Heat, cold, drought, salinity, and heavy metals affect crops. Heat stress from climate change disrupts cellular metabolism and lowers productivity. Tropical and subtropical crops suffer physiologically from cold stress. Climate variability affects drought, reducing crop output and germination. Salinity stunts growth and causes nutritional imbalances in big agricultural areas. Heavy metal buildup in soils threatens plant health. To overcome these problems, plants use osmotic adjustment, antioxidant defenses, and stress signaling pathways. CRISPR/Cas9 and other genetic engineering and molecular breeding methods may improve crop stress tolerance. Using omics technologies (genomics, transcriptomic, proteomics, and metabolomics) in breeding programs helps us understand stress tolerance processes and generate resilient crop types. This research is crucial for sustainable agriculture and global food security.

Co-application of Parthenium biochar and urea effectively mitigate cadmium toxicity during wheat growth

Environmental contamination by cadmium (Cd), a highly toxic heavy metal, poses significant health risks to plants and humans. Biochar has been effectively used to promote plant growth and productivity under Cd stress. This study presents an innovative application of biochar derived from the invasive weed Parthenium hysterophorus to promote plant growth and productivity under Cd stress. Our study includes detailed soil and plant analyses, providing a holistic perspective on how biochar and urea amendments influence soil properties, nutrient availability, and plant physiological responses. To address these, we established seven treatments: the control, Cd alone (5 mg kg−1), biochar alone (5 %), urea alone (3 g kg−1), biochar with Cd, urea with Cd, and a combination of biochar and urea with Cd. Cd stress alone significantly reduced plant growth indicators such as shoot and root length, fresh and dry biomass, chlorophyll content, and grain yield. However, the supplementation of biochar, urea, or their combination significantly increased shoot length (by 48%, 34%, and 65%), root length (by 73%, 46%, and 70%), and fresh shoot biomass (by 4%, 31%, and 4%), respectively. This improvement is attributed to enhanced soil properties and improved nutrient absorption. The biochar–urea combination also enhanced Cd tolerance by improving total chlorophyll content by 14 %, 13 %, and 16 % compared to the control, respectively. Similaly, these treatments significantly (p < 0.05) boosted the activity of antioxidant enzymes such as catalase, peroxidase, and superoxide dismutase by 51 %, 30 %, and 51 %, respectively, thereby mitigating oxidative stress as a defensive mechanism. The Cd tolerance was improved by biochar, urea, and their combinations, which reduced Cd content in the shoots (by 60.5 %, 38.9 %, and 51.3 %), roots (by 47.5 %, 23.9 %, and 57.6 %), and grains (by 58.1 %, 30.2 %, and 38.3 %) relative to Cd stress alone, respectively. The synergistic effects of biochar and urea are achieved through improved soil properties, nutrient availability, activating antioxidant defense mechanisms, and minimizing the accumulation of metal ions in plant tissues, thereby enhancing plant defenses against Cd stress. Conclusively, converting invasive Parthenium weed into biochar and combining it with urea offers an environmentally friendly solution to manage its spreading while effectively mitigating Cd stress in crops.

Foliar application of silicon and selenium reduce the toxicity of cadmium to soybeans

Silicon (Si) and selenium (Se), two environmental protection materials, which are beneficial to plant growth and stress resistance, can also alleviate crop stress induced by heavy metals. However, the effects of Si, Se and their interactions in reducing cadmium (Cd) toxicity and the related mechanisms require further elucidation. Hence, this study implemented a foliar application of Si and Se on soybean (Glycine max L.) that subjected to Cd-induced stress with four treatments (sole/combined application of Si, Se, no fertilizer treatment). The results demonstrated that Si and Se showed effective mitigation of Cd toxicity on soybeans mainly by promoting growth, enhancing photosynthesis, maintaining root vigor, improving antioxidant capacity, alleviating oxidative damage, altering the storage form, subcellular distribution of Cd in soybeans, and was more noticeable when combined overall (Si + Se＞Se＞Si). Si + Se increased root activity by 28% and CAT activity in leaves by 130.65%. Overall, the combined application of Si and Se exhibited a pronounced synergistic effect in enhancing the healthy growth of soybean plants under Cd pollution, with a more prominent impact observed following the second fertilization.

The effect of cadmium on soil and plants, and the influence of Serendipita indica (Piriformospora indica) in mitigating cadmium stress.

Due to environmental pollution, the risk of cadmium stress for crops is soaring, so researchers are exploring inexpensive solutions to enhance cultivated crops in contaminated soil. Using microorganisms to reduce cadmium risk has been one of the most effective strategies in recent decades. Serendipita indica (Piriformospora indica) is one of the best endophyte fungi that, in addition to reducing heavy metal stress for crops, can significantly reduce the threat of other abiotic stresses. As part of this research, cadmium in soil has been investigated, as well as its effects on plants' morphophysiological and biochemical characteristics. The present review has also attempted to identify the role of Serendipita indica in improving the growth and performance of crops, as well as its possible effect on reducing the risk of cadmium. The results showed that Serendipita indica enhance the growth and productivity of plants in contaminated environments by improving soil quality, reducing cadmium absorption, improving the activity of antioxidant enzymes and secondary metabolites, raising water and mineral absorption, and altering morphophysiological structures.

Irrigation using slightly saline water from emerging desalination technologies as a solution to short‐term drought

Societal Impact StatementWith global weather patterns becoming more extreme and unpredictable, sourcing reliable irrigation water is vital for improving food security and conserving drinking water in drought‐prone areas. Emerging desalination technologies, which are still in the development phase, could potentially provide large quantities of slightly saline water for irrigation. However, we must first ensure that any benefits of alleviating drought using this water outweigh the negative impacts of salt stress. We examine the viability of such a system, using Tonga as a case study, with the aim of advocating for future use of emerging desalination technologies for irrigation in low‐ and middle‐income countries.SummaryEmerging desalination technologies have the potential to be a cheap and energy‐efficient source of irrigation water that could be used to alleviate short‐term droughts in low‐ and middle‐income countries. However, the water produced is unlikely to be completely salt‐free, potentially increasing the risk of salt stress in crops. In this review, we give an overview of the various emerging desalination technologies. We then use Tonga as a case study for assessing the viability of temporarily irrigating crops with moderately saline water (≤100 mM salt) and assess whether the benefits of alleviating drought outweigh the negative impacts of salt stress. We conclude that, in Tonga, important food security crops are likely to have higher survival and growth rates if they are provided with moderately saline water during drought, including taro, pumpkin and yam. Water derived using the new technologies would not be prohibitively expensive to produce. Moreover, it would minimise the need to divert a diminishing supply of water away from drinking to irrigation. The continued improvement of emerging desalination technologies, together with field trials, will help to optimise the use of moderately saline water for irrigation. This is likely to be especially beneficial for achieving and maintaining food security in low‐ and middle‐income countries in increasingly capricious conditions for agriculture.

Evaluation of crop water stress index of wheat by using machine learning models.

The Crop Water Stress Index (CWSI), a pivotal indicator derived from canopy temperature, plays a crucial role in irrigation scheduling for water conservation in agriculture. This study focuses on determining CWSI (by empirical method) for wheat crops in the semi-arid region of western Uttar Pradesh, India, subjected to varying irrigation treatments across two cropping seasons (2021-2022 and 2022-2023). The aim is to investigate further the potential of four machine learning (ML) models-support vector regression (SVR), random forest regression (RFR), artificial neural network (ANN), and multiple linear regression (MLR) to predict CWSI. The ML models were assessed based on determination coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE) under diverse scenarios created from eight distinct input combinations of six variables: air temperature (Ta), canopy temperature (Tc), vapor pressure deficit (VPD), net solar radiation (Rn), wind speed (U), and soil moisture depletion (SD). SVR emerges as the top-performing model, showcasing superior results over ANN, RFR, and MLR. The most effective input combination for SVR includes Tc, Ta, VPD, Rn, and U (R2 = 0.997, MAE = 0.901%, RMSE = 2.223%). Meanwhile, both ANN and MLR achieve optimal results with input combinations involving Tc, Ta, VPD, Rn, U, and SD (R2 = 0.992, MAE = 2.031%, RMSE = 3.705%; R2 = 0.759, MAE = 13.95%, RMSE = 19.98%, respectively). For RFR, the ideal input combination comprises Tc, Ta, VPD, and U (R2 = 0.951, MAE = 5.023%, RMSE = 9.012%). The study highlights the considerable promise of ML models in predicting CWSI, proposing their future application in integration into an irrigation decision support system (IDSS) for crop stress mitigation and efficient water management in agriculture.

Two birds with one stone: Multifunctional controlled‐release formulations of pesticides

AbstractControlled release and nanotechnology techniques hold promising potential for propelling the pesticide industry toward the goals of green revolution. This study introduces the concept of atom economy into the multifunctionality of controlled‐release formulations (CRFs) of pesticides from both economic and sustainable perspectives. In addition to their core function of controlling the release of active ingredient, carriers also provide additional benefits, including enhanced foliar adhesion and pesticide translocation, nutritional function, synergistic bioactivity, safety for nontarget organisms, crop stress alleviation, reduced soil leaching, soil remediation, and fluorescence visualization. These additional functions are highlighted and taken seriously. Through ingenious excogitation, the multifunctional CRFs of pesticides can achieve multiple objectives, enhancing input efficiency while minimizing environmental impacts. We tentatively blazed a trail by reviewing the recent advances in multifunctional CRFs of pesticides from the perspective of green chemistry. Additionally, potential development and implementation barriers of CRFs were discussed, emphasizing the necessity for robust field trials and comprehensive systems‐level efficacy/biosafety evaluations to substantially boost the technical readiness and performance of multifunctional CRFs of pesticides. Our goal is to expand the multifunctional concept for pesticide formulations, thereby accelerating the development of global sustainable agrochemical products.

Hyperspectral Imaging for Phenotyping Plant Drought Stress and Nitrogen Interactions Using Multivariate Modeling and Machine Learning Techniques in Wheat

Accurate detection of drought stress in plants is essential for water use efficiency and agricultural output. Hyperspectral imaging (HSI) provides a non-invasive method in plant phenotyping, allowing the long-term monitoring of plant health due to sensitivity to subtle changes in leaf constituents. The broad spectral range of HSI enables the development of different vegetation indices (VIs) to analyze plant trait responses to multiple stresses, such as the combination of nutrient and drought stresses. However, known VIs may underperform when subjected to multiple stresses. This study presents new VIs in tandem with machine learning models to identify drought stress in wheat plants under varying nitrogen (N) levels. A pot wheat experiment was set up in the glasshouse with four treatments: well-watered high-N (WWHN), well-watered low-N (WWLN), drought-stress high-N (DSHN) and drought-stress low-N (DSLN). In addition to ensuring that plants were watered according to the experiment design, photosynthetic rate (Pn) and stomatal conductance (gs) (which are used to assess plant drought stress) were taken regularly, serving as the ground truth data for this study. The proposed VIs, together with known VIs, were used to train three classification models: support vector machines (SVM), random forest (RF), and deep neural networks (DNN) to classify plants based on their drought status. The proposed VIs achieved more than 0.94 accuracy across all models, and their performance further increased when combined with known VIs. The combined VIs were used to train three regression models to predict the stomatal conductance and photosynthetic rates of plants. The random forest regression model performed best, suggesting that it could be used as a stand-alone tool to forecast gs and Pn and track drought stress in wheat. This study shows that combining hyperspectral data with machine learning can effectively monitor and predict drought stress in crops, especially in varying nitrogen conditions.