ACS agricultural science & technology最新文献

In order to solve the insufficiency of traditional pesticide residue detection methods, such as limited detection sensitivity, high time and labor costs, inability to monitor in real time, and easy interference of detection results, a study that combines a microfluidic platform with surface-enhanced Raman scattering (SERS) technology to enable rapid detection of continuous trace amounts is proposed. The microfluidic SERS chip utilizes porous silicon carbide impregnated with silver nanoparticles to construct a high-performance SERS substrate. The three-dimensional structure of porous silicon carbide gives the SERS substrate excellent enhancement performance, with a detection limit as low as 10^–12 M. Its high sensitivity and environmental friendliness makes it a promising tool for biochemical analysis and detection. The porous silicon carbide SERS substrate exhibits a high enhancement factor (EF) of 2.05 × 10¹³ for the R6G solution at 1506 cm^–1.

In recent years, convolutional neural network (CNN) models and deep learning techniques have gained significant attention for plant disease detection. Despite advances, achieving high accuracy across diverse classes remains challenging. Existing CNN models have demonstrated moderate accuracy in classifying a limited number of mango leaf diseases. So, a crucial necessity exists to broaden the scope of precision. Our investigation introduces a CNN model that achieves an impressive 99% accuracy across eight classes of mango leaf diseases. Using advanced data processing, image augmentation, and feature extraction methodologies rooted in artificial intelligence and deep learning, we systematically explored over 20 CNN architectures and various hyperparameters to develop a robust model. Given the global significance of mango cultivation, our model was rigorously trained and tested for reliability. Detailed results and materials are available on GitHub. Additionally, we integrated our CNN model into an Android app, “Mango-SCN”, designed for easy use in managing mango leaf diseases, accessible even to nonexperts.

Many of the carriers used in the delivery of avermectin (Avm) B1a, a widely used crop pesticide, may lead to environmental safety problems. Here, we tested the self-assembly of Avm B1a without an exogenous excipient for improved environmental safety and drug activity. Our results showed that various solvents, including ethanol, methanol, acetone, dimethyl sulfoxide, and N,N-dimethylformamide, can be used to prepare Avm B1a self-assembled nanoparticles. Nuclear magnetic titration experiments revealed that the intermolecular hydrogen bond was the main binding force in Avm B1a self-assembly. Molecular dynamics simulations indicated that the number of hydrogen bonds increased to 10 and 20 in the assembly system of 16 and 32 Avm B1a molecules, respectively, over a period of 500 ns. The assembled Avm B1a presented a structured spherical shape, and particle size could be effectively regulated with the initial concentration. The permeability in soil and anti-UV degradation capacity were, respectively, 3.5 and 2.0 times higher for self-assembled nanoparticles with a size of 128 nm than for pure Avm B1a. The activity of nanoparticles against potato putrid stem nematode was higher than that of pure Avm B1a; in that, particles with a size of 128 nm exhibited the highest activity, and the 24 h and 48 h activity was, respectively, 16 and 20% higher than that of pure Avm B1a. In vivo fluorescence experiments showed that the fluorescence in nematodes increased with the increase in chemical concentration and time.

In arid and semiarid regions, agricultural producers, including cashew growers, grapple with the challenges of cultivating crops in harsh environmental conditions. To address this issue, conditioning materials capable of maintaining soil moisture levels even during droughts presents a promising solution. Herein, we synthesized a superabsorbent hydrogel composite comprised of starch-grafted-poly(sodium acrylate) embedded with 20% (w/w) kaolin (KAO), designed to enhance the quality of cashew seedlings. Characterization of the composite through Fourier transform infrared (FTIR) and X-ray diffraction (XRD) analyses confirmed its successful synthesis. The incorporation of KAO influenced the thermal, morphological, and swelling properties of the composite, as a result of the interaction between the clay and starch. Moreover, the composite exhibited improved water absorption capacity and kinetics, demonstrating a superabsorbent behavior. Our findings demonstrated that the addition of just 1% (w/w) of the composite effectively enhanced soil moisture retention. Notably, the placement of the composite within the soil column proved critical in extending the interval between irrigation cycles. Field experiments revealed that cashew seedlings cultivated in soil conditioned with the composite positioned deeper in the pot exhibited notable improvements in morphological parameters such as plant height, stem diameter, and leaf count, especially over prolonged cultivation periods. Besides, these seedlings displayed increased vigor and overall quality, essential for the establishment of robust and healthy cashew orchards. Overall, this study underscores the potential of this composite as a promising and cost-effective soil conditioning material for enhancing cashews and other crop yields in arid and semiarid regions with limited water availability.

Honey, a valuable and globally consumed food product, has significant market potential linked to its origin. However, authenticating honey is challenging due to sophisticated adulteration techniques. This current research introduces an innovative approach employing YOLOv7, a cutting-edge object detection model, to detect and classify honey pollens, thereby bolstering the authentication of honey. Our methodology involved creating a data set comprising three well-known honey varieties (Sundarban, Litchi, and Mustard), supplemented by three sets of unidentified honey pollen images sourced from Kaggle. Subsequently, we assembled a data set consisting of 3000 images representing the pollen types extracted from the known honey samples. To tackle the challenge of limited sample sizes, we employed data augmentation techniques. The efficacy of our approach was evaluated using established statistical measures including detection accuracy, precision, recall, mAP value, and F1 score, yielding impressive values of 98.3, 99.3, 100, 99.2%, and 0.985, respectively. The YOLOv7 model’s reliability was validated using Kaggle’s unknown honey pollen data sets, which showed that it correctly detected and identified these new pollens based on previous training. Through rigorous experimentation and validation, our study underscores the potential of the YOLOv7 framework in revolutionizing quality control practices within the honey industry, ensuring consumers access to genuine and top-tier honey products through pollen image analysis.

Drought is among the most damaging climatic hazards affecting crop productivity and nutritional quality. Here, we investigated the influence of Cu-based materials at mitigating drought stress in soybeans (Glycine max) during the reproductive stage in order to elucidate effects on productivity. Commercial copper oxide (CuO) nanoparticles (NPs), in-house synthesized copper sulfide (CuS) NPs, and copper sulfate (CuSO₄) were foliar applied at 10 mg Cu/L daily for 1 week to soybean that were exposed to water deficit at the onset of flowering, and plants were harvested 5 days after exposure. Drought inhibited flower production by 27% compared to the nondrought treatment. Notably, both CuS NPs and ionic Cu mitigated the drought-induced inhibition of flower production, showing 41.7 and 33.3% improvement. CuS NPs exhibited the most positive impact on restoring shoot biomass, pod biomass, and shoot moisture content, increasing values by 53, 96, and 10%, respectively, compared to the drought control plants. The Cu-based materials maintained photosynthetic parameters under drought conditions and modulated oxidative damage by enhancing reactive oxygen species-scavenging enzyme activities. Furthermore, CuO NP treatment increased shoot and pod Cu levels by 624 and 54%, respectively, compared to the drought control plants. Taken together, these findings suggest that Cu-based materials modulate plant protective mechanisms against drought stress during the flowering stage, offering a potentially important nanoenabled strategy to promote biofortified climate resilient crops.

Plant diseases significantly threaten global food security, with numerous historical instances of devastating epidemics. This risk is particularly acute in key agricultural and food crops, such as sugarcane. Although recent advancements in molecular diagnostics have improved the detection of sugarcane viruses, these methods are largely confined to lab settings due to their reliance on sophisticated, costly equipment. To overcome this limitation, we have developed a more accessible and cost-effective solution: a magnetic nanozyme-enhanced colorimetric ImmunoFlow-through assay designed for the ultrasensitive detection of sugarcane yellow leaf curl virus (ScYLV). This innovative technique allows for clear optical identification of viral concentrations as low as femtomolar levels. The assay employs cationic magnetic nanoparticles for virus isolation and colorimetric immunolabels for diagnosis, enhancing sensitivity and providing immediate results, comparable to those of established methods like quantitative real-time-polymerase chain reaction (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA). Our assay offers a one-step detection process and a two-step semiquantitative analysis, marking a major breakthrough in plant virus diagnostics. Extensive research into the assay’s design, including its sensing platform, blocking agents, antibody conjugation chemistries, sensitivity, quantification, potential for multiplexing, and field applicability, was carried out. This diagnostic research utilizing Magnetozyme in a flow-through assay represents a pioneering approach to rapid and sensitive diagnosis within plant disease diagnostics. It introduces a promising alternative to traditional molecular diagnostics, potentially transforming plant disease management and enhancing food security globally.

Effective pesticide utilization is an essential matter that needs attention, owing to the vast usage of pesticides worldwide. Herein, a pyrrolidinium-based ionic liquid (IL) 1-hexyl-1-methylpyrrolidinium bromide [PyrC₆]Br^– was chosen to solve the purpose of an adjuvant to enhance the surface activity and wettability of a pesticide nitenpyram (NTP). The critical micellar concentration of IL-NTP was evaluated using surface tension and spectrophotometric techniques, viz., UV–visible and steady state fluorescence. ΔG_ads⁰ and ΔG_mic⁰ were also calculated, and it was found that the adsorption process was favored over micellization. The sizes and stability of IL-NTP aggregates were analyzed using DLS and zeta potential measurements, respectively, which indicated optimum stability for IL-NTP when IL was present at its cmc value. The wettability of IL-NTP was found to be enhanced as compared to NTP in aqueous solution by evaluating it on various crop leaves using static contact angle measurements. Further, DFT calculations were performed which revealed complex formation between IL and NTP and various thermal and physiochemical parameters were obtained and it was found that IL and NTP bind through electrostatic interactions. Our results suggest an improved effect of IL on NTP, which could help in developing an IL-NTP composition that might result in better activity on crops.

This study investigated the seed priming effects with aqueous extracts from the cyanobacterium Anabaena minutissima (AM) and the brown seaweed Sargassum vulgare (SV) on the growth and nutritional properties of China Rose (CR), Daikon (D), and Sango Red (SR) radish varieties. AM and SV biomasses were chemically analyzed. FTIR spectra of biomasses exhibited functional groups characteristic of amides I and II of proteins in AM and functional groups associated with the pyranose ring of carbohydrates in SV. The extracts differed in total proteins, phycobiliproteins, carbohydrates, chlorophylls, carotenoids, and antioxidant activity. Seed priming with AM and SV particularly increased seed germination (2% in CR), moisture (5% in D with AM), sprout weight (35% with AM), and height (12% with SV). In the elemental analysis of sprouts, Na, Ca, and Mg levels increased variably across all varieties of both extracts. Principal component analysis revealed significant separation among treatments in SR and D varieties, confirming the effectiveness of the seed priming.

Copper (Cu) contamination in paddy fields leads to excessive Cu in rice grains and a low grain yield, posing a serious threat to sustainable agricultural production. We propose the application of seed priming with silver ions (Ag⁺) as biostimulants to trigger reactive oxygen species (ROS) production and enhance immune responses, thereby improving rice resistance to Cu stress. The results showed that seed priming with 10 μM Ag⁺ significantly improved rice tolerance to Cu, increased the fresh biomass by 22.1%, and reduced the Cu content in the roots and shoots by 25.3 and 13.4%, respectively, compared to the hydropriming treatments. Furthermore, seed priming with 10 μM Ag⁺ increased nutrient uptake in rice, leading to higher contents of Ca (15.1%), Fe (14.9%), and Mg (10.2%) in the shoots as well as Ca (21.0%), Mn (37.0%), and Mg (29.1%) in the roots. More Cu was immobilized in the root cell wall, thereby significantly enhancing root cell viability, maintaining the root morphology, and reducing malondialdehyde accumulation. Transcriptomics analyses revealed that Ag⁺-priming activated the phytohormone signal transduction and mitogen-activated protein kinase (MAPK) signaling pathway and other kinase signaling pathways in rice roots under Cu stress. These signals triggered the upregulation of defense-related gene expression, including the Cu vesicle transporter gene, oxidoreductase activity genes, and hydrogen peroxide catabolic process genes, amino acid metabolism, purine metabolism, and starch and sucrose metabolism. This study suggests that seed Ag⁺-priming is a simple and effective way to alleviate Cu toxicity and decrease Cu accumulation in rice, which ensures safe rice production in a sustainable way.