Search Results (1,387)

In the realm of global food security, plants serve as the primary source of sustenance. However, plant diseases pose a significant threat to this security. The process for diagnosing these diseases forms the bedrock of disease control efforts. The precision and expediency of these diagnoses wield substantial influence over disease management and the consequent reduction of economic losses. This research endeavors to diagnose the prevalent crops in Jordan, as identified by the Jordanian Department of Statistics for the year 2019. These crops encompass four key agricultural varieties: cucumbers, tomatoes, lettuce, and cabbage. To facilitate this, a novel dataset known as “Jordan22” was meticulously curated. Jordan22 was compiled by collecting images of diseased and healthy plants captured on Jordanian farms. These images underwent meticulous classification by a panel of three agricultural specialists well-versed in plant disease identification and prevention. The Jordan22 dataset comprises a substantial size, amounting to 3210 images. The results yielded by the CNN were remarkable, with a test accuracy rate reaching an impressive 0.9712. Optimal performance was observed when images were resized to 256 × 256 dimensions, and max pooling was used instead of average pooling. Furthermore, the initial convolutional layer was set at a size of 32, with subsequent convolutional layers standardized at 128 in size. In conclusion, this research represents a pivotal step towards enhancing plant disease diagnosis and, by extension, global food security. Through the creation of the Jordan22 dataset and the meticulous training of a CNN model, we have achieved substantial accuracy in disease detection, paving the way for more effective disease management strategies in agriculture. Full article

The impact of macroalgae species on rumen function remains largely unexplored. This present study aimed to identify the biocompounds of the three types of marine macroalgae described: Macrocystis pyrifera (Brown), Ulva spp. (Lettuce), Mazzaella spp. (Red) and their effect on species-specific modulations of the rumen microbiome. The macroalgae were characterized using GC-MS. Twelve Rambouillet lambs were randomly assigned to one of four experimental diets (n = 3 per treatment): (a) control diet (CD); (b) CD + 5 g of Red algae; (c) CD + 5 g of Brown algae; and (d) CD + 5 g of Lettuce algae. After the lambs ended their fattening phase, they donated ruminal fluid for DNA extraction and 16S rRNA gene V3 amplicon sequencing. Results: The tagged 16S rRNA amplicon sequencing and statistical analysis revealed that the dominant ruminal bacteria shared by all four sample groups belonged to phyla Firmicutes and Bacteroidota. However, the relative abundance of these bacterial groups was markedly affected by diet composition. In animals fed with macroalgae, the fibrinolytic and cellulolytic bacteria Selenomonas was found in the highest abundance. The diversity in chemical composition among macroalgae species introduces a range of bioactive compounds, particularly VOCs like anethole, beta-himachalene, and 4-ethylphenol, which demonstrate antimicrobial and fermentation-modulating properties. Full article

Understanding the interactions among biochar, plants, soils, and microbial communities is essential for developing effective and eco-friendly soil remediation strategies. This study investigates the role of cystamine-modified biochar (Cys-BC) in alleviating cadmium (Cd) toxicity in lettuce, comparing its effects to those of raw biochar. Lettuce plants were exposed to Cd stress (1–5 mg kg⁻¹), and the effects of Cys-BC were assessed by measuring plant biomass, photosynthetic efficiency, antioxidant activity, Cd bioavailability, and soil microbial diversity. Cys-BC significantly enhanced plant biomass, with increases in above-ground growth (40.54–44.95%) and root biomass (37.54–47.44%) compared to Cd-stressed controls. Photosynthetic parameters improved by up to 91.02% for chlorophyll-a content and 37.93% for the net photosynthetic rate. Cys-BC mitigated oxidative stress, increasing antioxidant activities by 73.83% to 99.39%. Additionally, Cys-BC reduced available Cd levels in the soil, primarily through enhanced cation exchange rather than changes in pH. Plant responses to Cd stress included increased glutathione reductase activity and elevated cysteine levels, which further contributed to Cd passivation. Microbial diversity in the soil increased, particularly among sulfur- and nitrogen-cycling bacteria such as Deltaproteobacteria and Nitrospira, suggesting their role in mitigating Cd stress. These findings highlight the potential of Cys-BC as an effective agent for the remediation of Cd-contaminated soils. Full article

Global pollution caused by micro/nanoplastics (M/NPs) is threatening agro-ecosystems, compromising food security and human health. Also, the increasing use of graphene-family nanomaterials (GFNs) in agricultural products has led to their widespread presence in agricultural systems. However, there is a large gap in the literature on the combined effects of MNPs and GFNs on agricultural plants. This study was conducted to explore the individual and combined impacts of polystyrene microplastics (PSMPs, 1 μm) or nanoplastics (PSNPs, 50–100 nm), along with agriculturally relevant graphene oxide (GO), on the seed germination and seedling growth of lettuce (Lactuca sativa). The results showed that the combined effects of mixtures of PSMPs/PSNPs and GO exhibited both synergism and antagonism, depending on different toxicity indicators. The cellular mechanism underlying the combined effects on the roots and shoots of seedlings involved oxidative stress. Three SOD family genes, namely, Cu/Zn-SOD, Fe-SOD, and Mn-SOD, played an important role in regulating the antioxidant defense system of seedlings. The extent of their contribution to this regulation was associated with both the distinct plastic particle sizes and the specific tissue locations within the seedlings. Full article

The widespread application of LED plant factories has been hindered by the high energy consumption and low light use efficiency. Adjustment of the daily light integral (DLI) offers a promising approach to enhance the light use efficiency in hydroponic cultivation within LED plant factories. However, most LED plant factories use a constant DLI during the cultivation process, which often leads to excessive light intensity in the early growth stage and insufficient light intensity in the later stage. To address this issue, this study aimed to improve the photon yield of hydroponic lettuce by optimizing the DLI at different growth stages. A logistic growth model was employed to segment the lettuce growth process, with variable DLI levels applied to each stage. DLIs of 11.5, 14.4, and 18.0 mol m⁻²·d⁻¹ were implemented at the slow growth stage, and the DLIs were adjusted to 14.4, 17.3, and 21.2 mol m⁻²·d⁻¹ at the rapid growth stage. Photoperiods of 16 h·d⁻¹ and 20 h·d⁻¹ were used for the two growth stages, and LED lamps with white and red chips (ratio of red to blue light was 1.5) were used as the light source. The results indicated that the photoperiod had no significant impact on the shoot fresh weight and photon yield under the constant DLI conditions at the slow growth stage (12 days after transplanting). The 14.4 mol m⁻²·d⁻¹ treatment resulted in the highest photon yield due to the significant increases in the light absorption and net photosynthetic rate of the leaves compared to the 11.5 mol m⁻²·d⁻¹ treatment. No significant differences in the specific leaf area (SLA) and leaf light absorption were observed between the 14.4 and 18.0 mol m⁻²·d⁻¹ treatments; however, the photon yield and actual photochemical efficiency (ΦPSII) significantly decreased. Compared with the DLI of 14.4 mol m⁻²·d⁻¹ at the rapid growth stage (24 days after transplanting), the 17.3 mol m⁻²·d⁻¹ treatment with 20 h·d⁻¹ increased the leaf light absorption by 5%, the net photosynthetic rate by 35%, the shoot fresh weight by 25%, and the photon yield by 19%. However, the treatments with DLIs above 17.3 mol m⁻²·d⁻¹ resulted in notable decreases in the photon yield, ΦPSII, and photosynthetic potential. In conclusion, it is recommended to implement a 20 h·d⁻¹ photoperiod coupled with a DLI of 14.4 mol m⁻²·d⁻¹ for the slow growth stage and 17.2 mol m⁻²·d⁻¹ for the rapid growth stage of hydroponic lettuce cultivation in an LED plant factory. Full article

This study utilized eggshell biomass as a calcium precursor for synthesizing hydroxyapatite (Hap) through a co-precipitation method assisted by a combined microwave-ultrasound (Mu/Us) crystallization process. Different milling techniques (mortar, high-energy mill, and sieving) were employed to prepare the eggshell biomass and identify the most effective calcium precursor. The precursor derived from high-energy milling, followed by sieving and thermal treatment at 750 °C (designated as Sample Hap-H3 750), was selected due to its higher porosity, enhanced crystallinity, and smaller particle size than other synthesized materials. This sample was subsequently used as a carrier for the plant hormone forchlorfenuron (FCF), forming the composite Hap-FCF. Comprehensive characterization was conducted using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), specific surface area analysis (BET method), zeta potential (ZP), scanning electron microscopy (SEM), and bright-field transmission electron microscopy (BFTEM), ensuring reliable and robust data. The in silico evaluation of the phytohormone FCF with two receptors, gibberellin (GA3Ox2) and auxin (IAA7), produced notable results. Docking and molecular dynamics (MD) simulations demonstrated that the gibberellin receptor was preferentially stimulated, as shown by the higher binding affinity and the receptor’s sustained stability during the MD simulations. These findings underscore the potential applications of this research, emphasizing its significance in materials science and biochemistry. Moreover, the in vitro assessment of Hap-H3 750, Hap-FCF, FCF, and the control (distilled water) on the germination and growth of butterhead lettuce seeds (Lactuca sativa) over 30 days revealed that Hap-H3 750 and Hap-FCF promoted plant growth by 275–330% relative to the control. This effect was attributed to the preferential stimulation of the gibberellin receptors responsible for stem and root elongation. These results suggest that HAP nanoparticles could facilitate the controlled delivery of FCF in the agricultural sector, promising to be an effective nanofertilizer. Full article

Monitoring anthocyanins is essential for assessing nutritional value and the growth status of plants. This study aimed to utilize hyperspectral technology to non-destructively monitor anthocyanin levels. Spectral data were preprocessed using standard normal variate (SNV) and first-derivative (FD) spectral processing. Feature wavelengths were selected using uninformative variable elimination (UVE) and UVE combined with competitive adaptive reweighted sampling (UVE + CARS). The optimal two-band vegetation index (VI2) and three-band vegetation index (VI3) were then calculated. Finally, dung beetle optimization (DBO), subtraction-average-based optimization (SABO), and the whale optimization algorithm (WOA) optimized the extreme learning machine (ELM) for modeling. The results indicated the following: (1) For the feature band selection methods, the UVE-CARS-SNV-DBO-ELM model achieved an R_m² of 0.8623, an RMSE_m of 0.0098, an R_v² of 0.8617, and an RMSE_v of 0.0095, resulting in an RPD of 2.7192, further demonstrating that UVE-CARS enhances feature band extraction based on UVE and indicating a strong model performance. (2) For the vegetation index, VI3 showed a better predictive accuracy than VI2. The VI3-WOA-ELM model achieved an R_m² of 0.8348, an RMSE_m of 0.0109 mg/g, an R_v² of 0.812, an RMSE_v of 0.011 mg/g, and an RPD of 2.3323, demonstrating good performance. (3) For the optimization algorithms, the DBO, SABO, and WOA all performed well in optimizing the ELM model. The R² of the DBO model increased by 5.8% to 27.82%, that of the SABO model by 2.92% to 26.84%, and that of the WOA model by 3.75% to 27.51%. These findings offer valuable insights for future anthocyanin monitoring using hyperspectral technology, highlighting the effectiveness of feature selection and optimization algorithms for accurate detection. Full article

Aquaponics is an innovative agricultural method combining aquaculture and hydroponics. However, this balance can lead to the gradual depletion of essential micronutrients, particularly iron. Over time, decreasing iron levels can negatively impact plant health and productivity, making the monitoring and management of iron in aquaponic systems vital. This study investigates the use of Fe-Alg-CaCO₃ microparticles (MPs) as foliar fertilizer on lettuce plants in an aquaponic system. The research investigated Lactuca sativa L. cv. Foglia di Quercia Verde plants as the experimental cultivar. Three iron concentrations (10, 50, and 250 ppm) were tested, with 15 plants per treatment group, plus a control group receiving only sterile double-distilled water. The Fe-Alg-CaCO₃ MPs and ultrapure water were applied directly to the leaves using a specialized nebulizer. Foliar nebulization was chosen for its precision and minimal resource use, aligning with the sustainability goals of aquaponic cultivation. The research evaluated rosette diameter, root length, fresh weight, soluble solids concentration, levels of photosynthetic pigments, and phenolic and flavonoid content. The 250 ppm treatment produced the most notable enhancements in both biomass yield and quality, highlighting the potential of precision fertilizers to boost sustainability and efficiency in aquaponic systems. In fact, the most significant increases involved biomass production, particularly in the edible portions, along with photosynthetic pigment levels. Additionally, the analysis of secondary metabolite content, such as phenols and flavonoids, revealed no reduction compared to the control group, meaning that the proposed fertilizer did not negatively impact the biosynthetic pathways of these bioactive compounds. This study opens new possibilities in aquaponics cultivation, highlighting the potential of precision fertilizers to enhance sustainability and productivity in soilless agriculture. Full article

For accurate segmentation of lettuce canopy images, dealing with uneven illumination and background interference, hyperspectral imaging technology was applied to capture images of lettuce from the rosette to nodule stages. The spectral ratio method was used to select the characteristic wavelengths, and the characteristic wavelength images were denoised and image fused before being processed by filtering and threshold segmentation. To verify the accuracy of this segmentation method, the manual segmentation method and the segmentation method used in this study were compared, and the area overlap degree ($AOM$) and misclassification rate ($ME$) were used as criteria to evaluate the segmentation results. The results showed that the segmentation effect was the best when 553.8 nm, 702.5 nm and 731.3 nm were selected as the characteristic wavelengths of lettuce for the spectral ratio method, with an $AOM$ of 0.9526 and an $ME$ of 0.0477. Both have a variance of less than 0.01 and have the best stability. Hyperspectral imaging technology combined with multi-wavelength image and multi-threshold segmentation can achieve accurate segmentation of lettuce canopy images. Full article

Organic soil amendments, such as composts, mitigate the negative impacts on the environment that are caused by poor waste management practices. However, in the sub-Saharan African region, and Malawi in particular, studies investigating the agronomical efficacy and their ability to ameliorate drought stress when used as a soil amendment are minimal. This study aimed to evaluate the efficacy of sewage sludge and municipal solid waste (MSW) co-compost to ameliorate drought stress and improve crop productivity. Three experiments were conducted (i) to determine optimal application rate for co-compost, (ii) to evaluate yield response of maize and lettuce to co-compost application under contrasting soils, and (iii) to assess the effect of co-compost under water-limited conditions. Our results indicate that an application rate of 350 g co-compost per station was the most effective. This rate is 50% and 37% lower than the currently recommended rate for applying conventional compost to green vegetables and maize, respectively. In addition, under drought conditions, the co-compost application enhanced growth in lettuce, with less wilting, increased biomass and yield, approximately 130% greater leaf yield, and a 138% improvement in root growth. Furthermore, the relative root mass ratio (RRMR) was enhanced with the co-compost application by 103% under drought stress. This suggests that the co-compost amendment resulted in a greater allocation of biomass to the roots, which is a crucial morphological attribute for adapting to drought conditions. The concentration of K in the leaves and roots of plants treated with co-compost was significantly increased by 44% and 61%, respectively, under drought conditions, which may have contributed to osmotic adjustment, resulting in a significant increase in leaf relative water content (RWC) by a magnitude of 11 times. Therefore, in light of the rising inorganic fertilizer costs and the limited availability of water resources, these results demonstrate the potential of MSW and sludge co-composting in ameliorating the drastic effects of water- and nutrient-deficient conditions and optimizing growth and yield under these constraining environments. Full article

Background: The rapid development of refrigerated transportation technology for fresh vegetables has extended their shelf life. Some vegetables may appear undamaged on the surface, but their freshness may have decreased, often resulting in the phenomenon of passing off inferior vegetables as good. It is very important to establish a detection method for identifying and assessing the freshness of vegetables. Methods: Therefore, based on metabolomics methods, this study innovatively employed UHPLC-Q-Exactive Orbitrap MS and GC–MS techniques to investigate the metabolites in the refrigerated storage of four vegetables, namely chard (Beta vulgaris var. cicla L), lettuce (Lactuca sativa var. ramose Hort.), crown daisy (Glebionis coronaria (L.) Cass. ex Spach), and tomato (Solanum lycopersicum L.), exploring key biomarkers for assessing their freshness. UPLC-TQ MS was used for the quantitative analysis of key metabolites. Results: The results showed that arginine biosynthesis and the metabolism of alanine, aspartate, and glutamate are key pathways in vegetable metabolism. Four key metabolites were selected from chard, five from lettuce, three from crown daisy, and five from tomato. Conclusions: Comparing the content of substances such as alanine and arginine can help infer the freshness and nutritional value of the vegetables, providing important references for detecting spoilage, determining storage time, and improving transportation conditions. This research holds significant relevance for the vegetable transportation industry. Full article

Heat stress represents a significant challenge to global agricultural production, with particular emphasis on air temperature stress. Despite considerable attention to this issue, limited information is available regarding the impact of irrigation water temperature on the quality of vegetable crops. In this study, kohlrabi, tomato, and lettuce were subjected to three distinct irrigation temperatures: 17 °C, 24 °C, and 34 °C. A variety of parameters were measured for the three vegetables, including seedling height, relative chlorophyll content (SPAD), mass of the green part (FW), mass of roots (FW), dry weight (DW) of the green part, DW of roots, and leaf area. The results indicated a significant decrease in oxygen (O₂) content with rising water temperature, with a 20.8% reduction at 34 °C compared to 17 °C. Notably, the highest temperature of 34 °C exerted the most positive influence on the studied parameters, particularly evident in kohlrabi and tomato. This study addresses a critical knowledge gap by elucidating the impact of irrigation water temperature on the growth and development of vegetable seedlings. The findings presented here lay the groundwork for further investigations into the effects of heat stress on agricultural practices. Full article

Weed management plays a crucial role in the growth and yield of lettuce, with timely and effective weed control significantly enhancing production. However, the increasing labor costs and the detrimental environmental impact of chemical herbicides have posed serious challenges to the development of lettuce farming. Mechanical weeding has emerged as an effective solution to address these issues. In precision agriculture, the prerequisite for autonomous weeding is the accurate identification, classification, and localization of lettuce and weeds. This study used an intelligent mechanical intra-row lettuce-weeding system based on a vision system, integrating the newly proposed LettWd-YOLOv8l model for lettuce–weed recognition and lettuce localization. The proposed LettWd-YOLOv8l model was compared with other YOLOv8 series and YOLOv10 series models in terms of performance, and the experimental results demonstrated its superior performance in precision, recall, F1-score, mAP50, and mAP95, achieving 99.732%, 99.907%, 99.500%, 99.500%, and 98.995%, respectively. Additionally, the mechanical component of the autonomous intra-row lettuce-weeding system, consisting of an oscillating pneumatic mechanism, effectively performs intra-row weeding. The system successfully completed lettuce localization tasks with an accuracy of 89.273% at a speed of 3.28 km/h and achieved a weeding rate of 83.729% for intra-row weed removal. This integration of LettWd-YOLOv8l and a robust mechanical system ensures efficient and precise weed control in lettuce cultivation. Full article

In this study, physicochemical and proteomic analyses were performed to investigate the effect of modified atmosphere packaging (MAP) on the quality of postharvest loose-leaf lettuce. The results showed that MAP enhanced the sensory characteristics of loose-leaf lettuce and delayed the incidence of postharvest deterioration by suppressing weight loss, electrolyte leakage, and reactive oxygen species levels. MAP-inhibited storage-induced programmed cell death may be attributed to a lower expression of protein disulfide isomerase and a higher expression of oligonucleotide/oligosaccharide binding fold nucleic acid binding site protein and reducing glutamine synthase levels. Also, we explore the potential of MAP to protect against oxidative damage in loose-leaf lettuce by potentially modulating the expression levels of NAC family proteins, which may enhance signaling and the expression of cytochrome c oxidase and membrane-bound pyrophosphate in the oxidative phosphorylation pathway. In addition, MAP potentially delayed postharvest senescence and extended the shelf life of lettuce by regulating key protein metabolic pathways that may reduce respiration rates. These include the NAC family of proteins, enzymes in the oxidative phosphorylation pathway, glutamine synthetize, and other crucial metabolic routes. These findings provide a scientific basis for enhancing the postharvest preservation of leafy vegetables, such as loose-leaf lettuce, through MAP technology. Full article

This study aimed to produce livestock manure biochar to decrease environmental problems from livestock manure and evaluate its effectiveness as an organic fertilizer by examining the growth and nutrient use efficiency of crops. A plot experiment was conducted to investigate the characteristics of lettuce growth and nitrogen use efficiency in upland soils treated with cow manure biochar. The cow manure biochar was applied at rates of 0, 3, 5, 7, and 10 t ha⁻¹ (referred to as CMB0, CMB3, CMB5, CMB7, and CMB10, respectively), along with inorganic fertilizer (IF, NPK—200-59-12 kg ha⁻¹). The lettuce cultivation test was carried out for 42 days, during which the fresh weight, dry weight, length, and number of lettuce leaves were measured. Nitrogen use efficiency was evaluated by determining the agronomic efficiency of N and the apparent recovery fraction of N. Overall, as the cow manure biochar application rate increased, crop growth and nitrogen uptake improved. Soils treated with CMB5 and CMB7 showed higher lettuce growth, nitrogen content, and nitrogen uptake compared to soils under other treatments. Nitrogen use efficiency followed a pattern similar to that of crop productivity, with cow manure biochar application levels playing a significant role. In particular, the agronomic efficiency of N and the apparent recovery fraction of N, which are both related to crop nutrient utilization, were significantly higher in the CMB5 treatment compared to the IF treatment. These results indicate that nitrogen use efficiency can be enhanced through biochar application when growing crops on agricultural land. Therefore, it is suggested that the appropriate application of cow manure biochar can reduce inorganic fertilizer use and increase crop productivity, thereby enabling sustainable and eco-friendly agriculture. Full article