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Tomato (Solanum lycopersicon L.) is one of the most widely consumed and produced vegetable crops worldwide. It offers numerous health benefits due to its rich content of many therapeutic elements such as vitamins, carotenoids, and phenolic compounds. Biotic stressors such as bacteria, viruses, fungi, nematodes, and insects cause severe yield losses as well as decreasing fruit quality. Conventional breeding strategies have succeeded in developing resistant genotypes, but these approaches require significant time and effort. The advent of state-of-the-art genome editing technologies, particularly CRISPR/Cas9, provides a rapid and straightforward method for developing high-quality biotic stress-resistant tomato lines. The advantage of genome editing over other approaches is the ability to make precise, minute adjustments without leaving foreign DNA inside the transformed plant. The tomato genome has been precisely modified via CRISPR/Cas9 to induce resistance genes or knock out susceptibility genes, resulting in lines resistant to common bacterial, fungal, and viral diseases. This review provides the recent advances and application of CRISPR/Cas9 in developing tomato lines with resistance to biotic stress. [ABSTRACT FROM AUTHOR]

Tomato (Solanum lycopersicum L.), as one of the most valuable horticulture crops, was chosen to investigate the effect of nanoparticles (NPs) in the form of nano-ZnO combined with conventional fertilizer on the quality of tomato fruits, including their antioxidant potential (total antioxidant activity, lycopene and β-carotene content), sugars content and allergenic potential (profilin and Bet v 1 content). Nano-ZnO was implemented during plant cultivation, applied by foliar spraying or directly via soil, at three different concentrations (50, 150 and 250 mg/L). The obtained results suggest that the usage of NPs during tomato plant cultivation had minor impacts on parameters such as total antioxidant activity or the content of selected allergens. Even though the total antioxidant activity was not affected by nano-ZnO, the malondialdehyde activity (MDA) content was notably decreased in fruits under nano-ZnO treatment. The content of lycopene and β-carotene was significantly affected by the use of nano-ZnO. Moreover, the usage of nano-ZnO significantly increased the total sugar content in fruits treated with nanoparticles via foliar spraying. Based on the obtained results, it can be stated that nano-ZnO, regardless of the method of application, significantly affected tomato fruits which can be beneficial for fruit production. [ABSTRACT FROM AUTHOR]

The tomato potato psyllid, Bactericera cockerelli Šulc, originating from North and Central America, poses a serious threat to Solanaceae crops in Australia. This study investigates the potential of the Australian native and commercially available green lacewing, Mallada signatus Schneider, as a biological control agent for B. cockerelli. The effect of feeding on B. cockerelli on the development rate and survival, of M. signatus were evaluated. Further, a greenhouse cage study was conducted to determine the optimal density of M. signatus larvae needed to effectively control an established B. cockerelli population. In our study, the third instar larvae of M. signatus consumed over 75 B. cockerelli nymphs in 24 h. Following the introduction of M. signatus larvae to caged tomato plants, eight M. signatus larvae per caged tomato plant decreased B. cockerelli population by 64% at the end of the sampling. These results indicated M. signatus, particularly at the larval stage, is an effective biological control option for B. cockerelli, especially in greenhouse tomato cultivation. This research offers valuable insights for the Australian horticultural industry, presenting a viable, eco‐friendly alternative to traditional, chemical pesticide‐reliant pest management strategies. [ABSTRACT FROM AUTHOR]

Long-term continuous cropping affects the soil microecological community and leads to nutrient imbalances, which reduces crop yields, and crop rotation can increase soil productivity. To study the effects of the cultivation of tomato (Solanum lycopersicum) and corn (Zea mays) on the microbial community, physical and chemical factors and the structure of aggregates in cotton (Gossypium hirsutum) long-term continuous cropping soils were examined. Four cropping patterns were established, including one continuous cropping pattern and three crop rotation patterns, and the diversity of the soil microecological community was measured using high-throughput sequencing. The physical and chemical properties of different models of soil were measured, and the soil aggregate structure was determined by dry and wet sieving. Planting of aftercrop tomato and corn altered the bacterial community of the cotton continuous soil to a lesser extent and the fungal community to a greater extent. In addition, continuous cropping reduced the diversity and richness of the soil fungal community. Different aftercrop planting patterns showed that there were very high contents of soil organic carbon and organic matter in the cotton-maize rotation model, while the soil aggregate structure was the most stable in the corn-cotton rotation model. Planting tomato in continuous cropping cotton fields has a greater effect on the soil microbial community than planting maize. Therefore, according to the characteristics of different succeeding crop planting patterns, the damage of continuous cropping of cotton to the soil microenvironment can be alleviated directionally, which will enable the sustainable development of cotton production. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest challenges to the world at present. Tomato is also suffered from devastating yield loss due to climate change. The domesticated tomato (Solanum lycopersicum) is presumed to be originated from the wild tomato (S. pimpinellifolium). In this study, we compared the climate data of S. pimpinellifollium with the domesticated tomato, predicted the suitable regions of S. pimpinellifollium in China using MaxEnt model and assessed their tolerance to drought stress. We found that the predicted suitable regions of wild tomato are highly consistent with the current cultivated regions of domesticated tomato, suggesting that the habitat demand of domesticated tomato descended largely from its ancestor, hence the habitat information of wild tomato could provide a reference for tomato cultivation. We further predicted suitable regions of wild tomato in the future in China. Finally, we found that while average drought tolerance between wild and domesticated tomato accessions shows no difference, tolerance levels among wild tomato accessions exhibit higher variation, which could be used for future breeding to improve drought resistance. To summarize, our study shows that suitable regions of wild tomato provide insights into domesticated tomato cultivation in China. [ABSTRACT FROM AUTHOR]

In 2014, Physostegia chlorotic moitié virus (PhCMoV) was discovered in Austria in Physostegia virginiana. Subsequent collaborative efforts established a link between the virus and severe fruit symptoms on important crops such as tomato, eggplant, and cucumber across nine European countries. Thereafter, specific knowledge gaps, which are crucial to assess lhe risks PhCMoV can pose for production and how to manage it, needed to be addressed. In this study, the transmission, prevalence, and disease severity of PhCMoV were examined. This investigation led to lhe identification of PhCMoV presence in a new country, Switzerland. Furthermore, our research indicates that the virus was already present in Europe 30 years ago. Bioassays demonstrated PhCMoV can result in up to 100% tomato yield losses depending on the phenological stage of the plant at the lime of infection. PhCMoV was found to naturally infect 12 new host plant species across eight families, extending its host range to 21 plant species across 15 plant families. The study also identified a polyphagous leafhopper (genus Anaceratagallia) as a natural vector of PhCMoV. Overall, PhCMoV was widespread in small-scale diversified vegetable farms in Belgium where tomato is grown in soil under tunnels, occurring in approximately one-ihird of such farms. However, outbreaks were sporadic and were associated al least once with the cultivation in tomato tunnels of perennial plants that can serve as a reservoir host for the virus and its vector. To further explore this phenomenon and manage the virus, studying the ecology of the vector would be beneficial. [ABSTRACT FROM AUTHOR]

Automated assessment of tomato crop maturity is vital for improving agricultural productivity and reducing food waste. Traditionally, farmers have relied on visual inspection and manual assessment to predict tomato maturity, which is prone to human error and time-consuming. Computer vision and deep learning automate this process by analysing visual characteristics, enabling data-driven harvest decisions, optimising quality, and reducing waste for sustainable and efficient agriculture. This research demonstrates deep learning models accurately classifying tomato maturity stages using computer vision techniques, utilising a novel dataset of 4,353 tomato images. The Vision Transformer (ViT) model exhibited superior performance in classifying tomatoes into three ripeness categories (immature, mature, and partially mature), achieving a remarkable testing accuracy of 98.67% and the Convolution neural network (CNN) models, including EfficientNetB1, EfficientNetB5, EfficientNetB7, InceptionV3, ResNet50, and VGG16, achieved testing accuracies of 88.52%, 89.84%, 91.16%, 90.94%, 93.15%, and 92.27%, respectively, when tested with unseen data. ViT significantly surpassed the performance of CNN models. This research highlights the potential for deploying ViT in agricultural environments to monitor tomato maturity stages and packaging facilities smartly. Transformer-based systems could substantially reduce food waste and improve producer profits and productivity by optimising fruit harvest time and sorting decisions. [ABSTRACT FROM AUTHOR]

Enhancing saline water productivity in arid regions is essential for sustainable agriculture. Adding biochar can improve the quantity and quality of tomato yield under higher levels of salinity and lower levels of irrigation. The experiment aimed to evaluate the effects of biochar on enhancing tomato fruit quality and yield under salinity and drought stress. The experiment combines two treatments for irrigation water quality (0.9 and 2.3 dS m−1), four irrigation levels (40, 60, 80, and 100%) of crop evapotranspiration (ETc), and the addition of 5% of biochar to treated soil (BC5%) and untreated soil (BC0%). The results showed that the decrease in the water quality and irrigation levels negatively impacted the yield and properties of tomato fruit, while 5% of biochar application positively improved the yield. Adding biochar decreased the tomato yield by 29.33% and 42.51% under lower-saline-irrigation water than the control, negatively affecting the fruit's physical parameters and mineral content. In contrast, adding biochar and irrigating with saline water at 60% of ETc improved the firmness and quality characteristics of the fruit by 56.60%, 67.19, 99.75, and 73.57% for vitamin C (VC), total titratable acidity (TA), total soluble solids (TSS), and total sugars (TS), respectively, compared to the control, and also reduced the sodium content of the fruits under all irrigation levels compared to untreated plants by biochar. Generally, biochar with saline water under deficit irrigation with 80 and 60% of ETc could be an excellent strategy to enhance the qualitative characteristics of tomato fruits and save approximately 20–40% of the applied water. [ABSTRACT FROM AUTHOR]

Background and aims: Plants alter root placement patterns to respond nutrients and neighbors, but whether neighbors influence the root architecture by modifying the availability of nutrients is still unclear. Here we aimed to screen intercropping plants cause changes in tomato root architecture and explore the role and potential activation pathways of N and P nutrients. Methods: We carried out the experiments of tomato-neighbor interactions to survey root plastic responses of target tomato seedlings and root placement patterns to intercropping soybean under different P or N levels. In addition, we investigated the effects and physiological mechanisms of intercropping soybean on P capture of tomatoes. Results: The intercropping soybean changed the horizontal symmetry of tomato roots, the dry weight and total root length of tomato roots in the 'Toword' region were significantly higher than those in the 'Away' region, while other intercropping plants did not. P rather than N levels, significantly affected the tomato root placement patterns in soybean intercropping systems. Under phosphorus deficiency condition, tomato roots showed a tendency to soybean. This phenomenon disappeared when the P supply increased. Under low P condition, intercropping soybean significantly increased P concentration of tomato plants and rhizosphere soil available P content. Compared with tomatoes, soybean roots secreted more acid phosphatase, protons and organic acids. Conclusions: Soybean triggered tomato root horizontal asymmetry through modifying tomato P rather than N capture mediated by root exudates under low nutrient condition, which contributes to the selection and application of tomato cultivation models in low input agriculture. [ABSTRACT FROM AUTHOR]

Target detection algorithms can greatly improve the efficiency of tomato leaf disease detection and play an important technical role in intelligent tomato cultivation. However, there are some challenges in the detection process, such as the diversity of complex backgrounds and the loss of leaf symmetry due to leaf shadowing, and existing disease detection methods have some disadvantages in terms of deteriorating generalization ability and insufficient accuracy. Aiming at the above issues, a target detection model for tomato leaf disease based on deep learning with a global attention mechanism, TDGA, is proposed in this paper. The main idea of TDGA includes three aspects. Firstly, TDGA adds a global attention mechanism (GAM) after up-sampling and down-sampling, as well as in the SPPF module, to improve the feature extraction ability of the target object, effectively reducing the interference of invalid targets. Secondly, TDGA uses a switchable atrous convolution (SAConv) in the C3 module to improve the model's ability to detect. Thirdly, TDGA adopts the efficient IoU loss (EIoU) instead of complete IoU loss (CIoU) to solve the ambiguous definition of aspect ratio and sample imbalance. In addition, the influences of different environmental factors such as single leaf, multiple leaves, and shadows on the performance of tomato disease detection are extensively experimented with and analyzed in this paper, which also verified the robustness of TDGA. The experimental results show that the average accuracy of TDGA reaches 91.40%, which is 2.93% higher than that of the original YOLOv5 network, which is higher than YOLOv5, YOLOv7, YOLOHC, YOLOv8, SSD, Faster R-CNN, RetinaNet and other target detection networks, so that TDGA can be utilized for the detection of tomato leaf disease more efficiently and accurately, even in complex environments. [ABSTRACT FROM AUTHOR]

The application of organic fertilizers is one of the most important agricultural measures aimed at improving the flavor and productivity of Lycopersicon esculentum, with the granulation and coating of organic fertilizers, which can reduce seepage losses of great significance to the ecosystem. In this study, Jingcai 8 tomato was selected as the test material. Headspace solid-phase microextraction and gas chromatography–mass spectrometry (HS-SPME-GC-MS) methods were used to investigate the effects of different pelletized organic fertilizers and various coating materials on the flavor profile of the tomatoes. The results indicated that 67 volatile organic compounds (VOCs) were identified in the tomato fruits and 62 volatile compounds were identified in the leaves under different fertilizer treatments. The volatile compound content of the fruits in the BP treatment group was 35.38 μg/g, which was higher than that in other treatment groups, and the volatile compound content of the leaves was lower. A differential compound analysis with log2|fold change| ≥ 1 and variable important in projection (VIP) > 1 highlighted styrene, 3-methyl-1-butanol, and (E, E)-2,4-hexadienal as the major up-regulated compounds and methyl salicylate as the major down-regulated compound in the tomato fruit BCK (control) vs. BP. Moreover, the α-phellandrene content decreased in the tomato leaves. In addition, an analysis of the tomato fruit differential compounds and compounds with odor activity values (OAV) of ≥ 1, considering the OAV values of characteristic aroma compounds, identified key compounds affecting the flavor of the tomato fruits under the BP treatment. These included 2-nonenal, (E)-2-pentylfuran, trans-β-ionone, 1-penten-3-one, (E, E)-2,4-hexadienal, and 3-hexenol (fruity, floral, and herbaceous odors), (E, E)-2,4-heptadienal (fatty odor), and hexanal (green odor). The combined results analysis of the volatile compound content, differential compounds, and OAV values of characteristic aroma compounds aimed to clarify that the BP treatment group, which applied pelletized, large-grain organic fertilizer with polyurethane (pozzolanic + small-grain oil-coated + 2% paraffinic + 4% polyurethane) as a coating material, proved to be most effective in influencing the flavor of the tomato fruits. This finding lays the foundation for its potential commercial application in artificial orchards. [ABSTRACT FROM AUTHOR]

The irrigation systems require modernization and management by evaluating water system prerequisites precisely. A study was carried out at Srinagar during kharif 2022 to determine the crop water demands, irrigation scheduling and simulation of moisture movement under different irrigation regimes on tomato crop in open field conditions using CROPWAT and HYDRUS-1D models. The results revealed that the average crop water requirement at 100% ETC per plant per day was 0.24 l plant-1 day-1 during the initial stage, 0.37 l plant-1 day-1 during development stage, 0.85 l plant-1 day-1 during mid-stage and 0.74 l plant-1 day-1 during the end stage. Soil water content was simulated by HYDRUS-1D model in 0 to 30 cm of soil profile. Higher values (0.86 to 0.95) of coefficient of determination (R² ) indicated that observed and simulated values of moisture content are highly correlated and the model predicts that lower values of mean absolute error (MAE) and root mean square error (RMSE) indicates that the HYDRUS-1D model is more accurate at simulating the movement of moisture under different irrigation regimes. [ABSTRACT FROM AUTHOR]

To achieve higher economic returns, we employ inexpensive valley electricity for night-time supplementary lighting (NSL) of tomato plants, investigating the effects of various durations of NSL on the growth, yield, and quality of tomato. Tomato plants were treated with supplementary light for a period of 0 h, 3 h, 4 h, and 5 h during the autumn–winter season. The findings revealed superior growth and yield of tomato plants exposed to 3 h, 4 h, and 5 h of NSL compared to their untreated counterparts. Notably, providing lighting for 3 h demonstrated greater yields per plant and per trough than 5 h exposure. To investigate if a reduced duration of NSL would display similar effects on the growth and yield of tomato plants, tomato plants received supplementary light for 0 h, 1 h, 2 h, and 3 h at night during the early spring season. Compared to the control group, the stem diameter, chlorophyll content, photosynthesis rate, and yield of tomatoes significantly increased upon supplementation with lighting. Furthermore, the input–output ratios of 1 h, 2 h, and 3 h NSL were calculated as 1:10.11, 1:4.38, and 1:3.92, respectively. Nonetheless, there was no detectable difference in yield between the 1 h, 2 h, and 3 h NSL groups. These findings imply that supplemental LED lighting at night affects tomato growth in the form of light signals. Night-time supplemental lighting duration of 1 h is beneficial to plant growth and yield, and its input–output ratio is the lowest, which is an appropriate NSL mode for tomato cultivation. [ABSTRACT FROM AUTHOR]

Verticillium dahliae (Vd) and Fusarium oxysporum f. sp. lycopersici (Fol) are two major fungal pathogens that infect tomato plants, causing significant challenges in their control since both pathogens can persist in the soil for several years even in the absence of a host plant and no effective fungicides are available at present. This study investigated the efficacy of two biocontrol formulations, Clonotri (containing Trichoderma and Clonostachys microorganisms) and Strepse (comprising Streptomyces and Pseudomonas microorganisms), against Vd and Fol and their impact on tomato fruit quality and yield under greenhouse conditions. The pathogenicity experiment demonstrated that the Clonotri formulation, containing Trichoderma and Clonostachys spores, significantly reduced Fusarium wilt disease by 32% compared to the control group. However, in the Vd pathogenicity experiment, the formulations did not exhibit disease reduction, although treatment with Strepse, containing Streptomyces and Pseudomonas microorganisms, resulted in a preserved total fruit number when compared to uninfected plants. Analysis of fruit quality attributes revealed no significant differences among the various interventions. Furthermore, Fol infection in the first fruit set significantly increased fruit firmness, while Vd infection resulted in elevated levels of total soluble solids in fruits. These findings demonstrate that the evaluated biocontrol formulations provide a degree of protection against fungal wilt pathogens in tomato plants and can increase yield in greenhouse conditions while having minimal impact on overall fruit quality attributes. [ABSTRACT FROM AUTHOR]

This study investigated the effects of irrigation with a fully inorganic nutrient solution (control; NNNN) and an organic instead of an inorganic nutrient solution (OIINS) at the flowering–fruit setting (ONNN), fruit expanding (NONN), color turning (NNON), and harvest (NNNO) stages of the first spike on the type and content of tomato fruit volatiles to provide a theoretical basis for tomato aroma improvement and high-quality cultivation. Compared with the control (NNNN), the results showed that all OIINS-related treatments decreased the number of fruit volatiles and increased the relative content of common volatile compounds, characteristic effect compounds, aldehydes, and cis-3-hexenal. In particular, the relative order of performance of the OIINS-related treatments was NNNO > NNON > ONNN > NONN in terms of the relative content of characteristic compounds. For all treatments, the relative cis-3-hexenal and trans-2-hexenal percentages were 20.99–51.49% and 20.22–27.81%, respectively. Moreover, hexanal was only detected in tomato fruits under the NNNN and NNNO treatments. The effects of irrigation with OIINS on tomato fruit volatiles were related to the fruit developmental stage. At the mature stage, the organic nutrient solution was conducive to the accumulation of characteristic compounds and improved the fruit aroma quality. [ABSTRACT FROM AUTHOR]

The presence of high salt in soils is a substantial abiotic constraint for agricultural activities worldwide, particularly in Mediterranean regions. Researchers have discovered a simple and efficient way to repair soils that have suffered from excessive salt use. They use plants that can overcome salt, like halophytes, to improve the soil quality. This research aimed to evaluate the tomato productivity and quality cultivated using different methods. We look at three different ways to grow tomatoes with the halophyte Salicornia europaea L. in a moderately salty soil: monoculture (only tomatoes), intercropping (mixed cultivation), and sequential cropping (growing tomatoes where halophytes were grown before). We considered how the different ways of managing crops affected tomato yield, biochemical factors in tomato plants (like phenolic and flavonoid contents), antioxidant levels, carotene profiles, and fruit quality and production. Sequential cropping showed the highest tomato productivity, while intercropping exhibited high concentrations of total phenolics, total flavonoids, carotenoids, and antioxidant capacity. The tomatoes had a sweet taste due to the higher total soluble solid content (TSSC) and maintained their quality due to the higher titratable acidity (TA). [ABSTRACT FROM AUTHOR]

Seaweed extracts have several functions in agriculture due to their composition that is rich in nutrients, plant hormones, and bioactive substances. It is a natural product used as a biostimulant especially to promote the growth and development of plants and their tolerance to environmental stresses. The objective of this study was to analyze the response to a biostimulant containing seaweed extract derived from Ascophyllum nodosum in the cultivation of tomato and eggplant seedlings, analyzing the growth and physiological parameters in two different regions of Brazil. Cherry tomato and eggplant were cultivated in polyethylene trays for 30 days. In each crop, five treatments were tested, comparing the use of a commercial seaweed extract in application doses and forms, which were the control (without seaweed application); 0.1%, 0.2%, and 0.3% of the seaweed extract applied by irrigation water; and treatment with 0.2% of the seaweed extract by foliar application. This study confirms the efficacy of incorporating seaweed extract from Ascophyllum nodosum as a bio-input into the production phase of Solanaceae seedlings. The seedlings which received the seaweed extract significantly increased some morphological parameters, mainly regarding the biomass and length of leaves, stems, and roots. In general, applying both methods through irrigation water and foliar application were effective in providing benefits compared to the control treatment. The intermediate dose (0.2%) was the most effective in promoting improvement in the analyzed parameters. This underscores the importance of obtaining quality seedlings for subsequent planting in the field, potentially leading to better acclimatization and initial adaptation. [ABSTRACT FROM AUTHOR]

Tomato (Solanum lycopersicum) is a widely consumed vegetable crop with significant economic and nutritional importance. This review paper discusses the recent advancements in gene-based approaches to enhance the quality of tomatoes, particularly focusing on firmness, shelf life, and adaptations to pre- and post-harvest stresses. Utilizing genetic engineering techniques, such as Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated proteins 9 (CRISPR/Cas9) and Transcription Activator-like Effector Nucleases (TALENs), researchers have made remarkable progress in developing tomatoes with improved traits that address key challenges faced during cultivation, storage, and transportation. We further highlighted the potential of genetic modifications in enhancing tomato firmness, thereby reducing post-harvest losses and improving consumer satisfaction. Furthermore, strategies to extend tomato shelf life through genetic interventions are discussed, emphasizing the importance of maintaining quality and freshness for sustainable food supply chains. Furthermore, the review delves into the ways in which gene-based adaptations can bolster tomatoes against environmental stresses, pests, and diseases, thereby enhancing crop resilience and ensuring stable yields. Emphasizing these crucial facets, this review highlights the essential contribution of genetic advancements in transforming tomato production, elevating quality standards, and promoting the sustainability of tomato cultivation practices. [ABSTRACT FROM AUTHOR]

The study aimed to evaluate the effect of adding wheat straw fermented with the oyster mushroom Pleurotus ostreatus on the growth and productivity of tomato plants grown in mini-plots in the greenhouse. The results showed that the treatment of soil + animal manure + plant waste + wheat straw mushroom compost (sterilized) (T9) was better than the other treatments, as it led to a significant increase in the growth indicators of tomato plants, especially the plant height and the number of leaves, flowers, and fruits, compared to the lowest values of the indicators compared to the treatment of wheat straw mushroom compost only (T6). On the other hand, the treatment of soil + animal manure + plant waste + unsterilized wheat straw mushroom compost (T8) outperformed the other treatments in terms of the biochemicals, vitamins, and other nutrients in the tomato fruits. [ABSTRACT FROM AUTHOR]

Tomato is one of the most popular and most important food crops consumed globally. The quality and quantity of yield by tomato plants are affected by the impact made by various kinds of diseases. Therefore, it is essential to identify these diseases early so that it is possible to reduce the occurrences and effect of the diseases on tomato plants to improve the overall crop yield and to support the farmers. In the past, many research works have been carried out by applying the machine learning techniques to segment and classify the tomato leaf images. However, the existing machine learning-based classifiers are not able to detect the new types of diseases more accurately. On the other hand, deep learning-based classifierswith the support of swarm intelligence-based optimization techniques are able to enhance the classification accuracy, leading to the more effective and accurate detection of leaf diseases. This research paper proposes a new method for the accurate classification of tomato leaf diseases by harnessing the power of an ensemble model in a sample dataset of tomato plants, containing images pertaining to nine different types of leaf diseases. This research introduces an ensemble model with an exponential moving average function with temporal constraints and an enhanced weighted gradient optimizer that is integrated into fine-tuned Visual Geometry Group-16 (VGG-16) and Neural Architecture Search Network (NASNet) mobile training methods for providing improved learning and classification accuracy. The dataset used for the research consists of 10,000 tomato leaf images categorized into nine classes for training and validating the model and an additional 1,000 images reserved for testing the model. The results have been analyzed thoroughly and benchmarked with existing performance metrics, thus proving that the proposed approach gives better performance in terms of accuracy, loss, precision, recall, receiver operating characteristic curve, and F1-score with values of 98.7%, 4%, 97.9%, 98.6%, 99.97%, and 98.7%, respectively. [ABSTRACT FROM AUTHOR]

Introduction: Tomato cultivation across the world is severely affected by emerging plant viruses. An effective method for protection of commercial crops against viral threats is the use of cultivars harboring resistance genes. Tomato brown rugose fruit virus (ToBRFV), a recently emerged tobamovirus, is able to overcome the dominant Tm-2² resistance that is present in the majority of commercial tomato cultivars. In an effort to alleviate the severe consequences of ToBRFV on tomato production, tomato breeding companies are developing new cultivars with varying levels of resistance against ToBRFV. Methods: In the present study, cultivars with a new resistant phenotype against ToBRFV were screened against a wild-type isolate of ToBRFV, and subsequently, their performance under commercial greenhouse conditions was monitored. Following the identification of ToBRFV symptoms in a commercial greenhouse--where both new resistant and susceptible cultivars were interplanted--these cultivars were more closely examined. Results: The presence of ToBRFV was molecularly confirmed on both cultivar types suggesting that the new resistance had been broken. High-throughput sequencing (HTS) was used to study the complete genomes of viral isolates present in the two cultivar types. The analysis revealed a single amino acid change at position 82 of the movement protein of ToBRFV in the isolate present in the new resistant cultivar compared with the isolate identified in the susceptible cultivar. Discussion: A screening bioassay, that was performed to compare the infectivity of the two ToBRFV isolates, confirmed that only the isolate with this specific amino acid change could successfully infect the resistant cultivar, overcoming the new resistance against ToBRFV. [ABSTRACT FROM AUTHOR]

Introduction: The study investigates the potential of Plasma Activated Water (PAW) as an innovative irrigation medium to enhance growth and defense responses in tomato seedlings. It explores PAW's utility in both healthy seedlings and those inoculated with Tomato mottle mosaic virus (ToMMV). Methods: PAW, produced through a dielectric barrier volume discharge, serves as a chemical-free alternative to traditional fertilizers. Tomato seedlings were irrigated with PAW or control solutions. The study employs biometric measurements to assess growth and biochemical analysis to evaluate antioxidant levels and pigments. Gene expression analysis was conducted to evaluate the plant response, while the distribution of macro and micronutrients was assessed through micro X-ray fluorescence. Results and discussion: Results indicate that PAW-irrigated seedlings exhibit significant growth enhancement compared to those receiving conventional fertilization. Increased levels of antioxidant molecules and pigments suggest improved photosynthetic activity and stress tolerance. Gene expression analysis shows up-regulation of defense genes in PAW-treated plants postviral infection. The up-regulation of defense genes and the restoration of mineral nutrient distribution in PAW-treated, virus-infected plants highlight PAW's role in enhancing plant resilience against pathogens and mitigating nutrient deficiencies. These findings emphasize PAW's potential as a sustainable agricultural solution, promoting plant growth, enhancing defense mechanisms, and reducing biotic stress due to virus infections. [ABSTRACT FROM AUTHOR]

Tomato grafting is an effective practice in increasing the profitability of fresh-market tomato cultivation, especially in greenhouses, and is also considered a strategy for enhancing fruit quality. In this study, selected quanti-qualitative traits, and the of bioactive health-promoting compound and organic acid contents of cherry tomato fruits from three different scion/rootstock combinations (Sunstream/Top Bental, Sunstream/Kaiser and Sunstream/Suzuka) grown under a greenhouse hydroponic system were evaluated in three different harvests (beginning, middle and end of the whole harvesting period) and on three different bunch portions (proximal, central and distal). Although the tomato productive performance was influenced by the rootstock, with Suzuka and Kaiser grafted plants showing the highest total marketable yield (9.8 kg plant−1, i.e., 20% more than Top Bental), the yield-related traits (bunch number, weight and length per plant, and fruit number per bunch) and the qualitative characteristics of the fruits (color, equatorial and polar diameters, dry matter and solid soluble contents, pH and titratable acidity) showed less variability, by displaying, along with the bioactive compound contents (total polyphenols, lycopene, β-carotene), DPPH free radical scavenging activity and organic acids contents (lactic and acetic), a significant effect of the harvesting time and bunch portion. Fruits from the beginning of the harvesting period showed better qualitative and functional properties, with the lycopene and β-carotene contents equal to 178.6 and 3 mg 100 g−1 fw, and fruits from proximal and central bunch portions had lycopene and β-carotene contents equal to 203.1 and 2.9 mg 100 g−1 fw. [ABSTRACT FROM AUTHOR]

To explore the compensation effect of aeration on tomato vegetative and reproductive growth in arid and semi-arid areas, a two-year field experiment was conducted with four micro-nano aeration ratios (0%, 5%, 10%, and 15%) and three nitrogen topdressing levels (80, 60, and 40 kg·ha−1) during the tomato growth period in Ningxia, China. The results showed that increasing the aeration ratio in the range of 0–15% was conducive to the enhancement of tomato root vigor (the ability of triphenyltetrazolium chloride to be reduced, 3–104%) and the leaf net photosynthetic rate (14–63%), favorable to the facilitation of plant dry matter accumulation (3–59%) and plant nitrogen accumulation (2–70%), and beneficial to the improvement of tomato yield (12–44%) and fruit quality. Interestingly, since the aeration ratio exceeded 10%, the increase in the aeration ratio showed no significant effects on the single-fruit weight, tomato yield, and fruit quality. Moreover, with aerated underground drip irrigation, properly reducing the traditional nitrogen topdressing level (80 kg·ha−1) by 25% was favorable for enhancing tomato root vigor (5–31%), increasing tomato yield (0.5–9%), and improving fruit soluble solid accumulation (2–5%) and soluble sugar formation (4–9%). Importantly, increasing the aeration ratio by 5% could compensate for the adverse effects of reducing the nitrogen topdressing level by 25% by improving the leaf photosynthetic rate, promoting plant dry matter accumulation, increasing tomato yield, and enhancing the soluble solid and soluble sugar accumulation in tomato fruits. Synthetically considering the decrease in the nitrogen topdressing amount, leading to plant growth promotion, a tomato yield increase, and fruit quality improvement, a favorable nitrogen topdressing level of 60 kg·ha−1 and the corresponding proper aeration ratio of 10% were suggested for tomato underground drip irrigation in the Yinbei Irrigation District of Ningxia. [ABSTRACT FROM AUTHOR]

Tomatoes possess significant nutritional and economic value. However, frequent diseases can detrimentally impact their quality and yield. Images of tomato diseases captured amidst intricate backgrounds are susceptible to environmental disturbances, presenting challenges in achieving precise detection and identification outcomes. This study focuses on tomato disease images within intricate settings, particularly emphasizing four prevalent diseases (late blight, gray leaf spot, brown rot, and leaf mold), alongside healthy tomatoes. It addresses challenges such as excessive interference, imprecise lesion localization for small targets, and heightened false-positive and false-negative rates in real-world tomato cultivation settings. To address these challenges, we introduce a novel method for tomato disease detection named TomatoDet. Initially, we devise a feature extraction module integrating Swin-DDETR's self-attention mechanism to craft a backbone feature extraction network, enhancing the model's capacity to capture details regarding small target diseases through self-attention. Subsequently, we incorporate the dynamic activation function Meta-ACON within the backbone network to further amplify the network's ability to depict disease-related features. Finally, we propose an enhanced bidirectional weighted feature pyramid network (IBiFPN) for merging multi-scale features and feeding the feature maps extracted by the backbone network into the multi-scale feature fusion module. This enhancement elevates detection accuracy and effectively mitigates false positives and false negatives arising from overlapping and occluded disease targets within intricate backgrounds. Our approach demonstrates remarkable efficacy, achieving a mean Average Precision (mAP) of 92.3% on a curated dataset, marking an 8.7% point improvement over the baseline method. Additionally, it attains a detection speed of 46.6 frames per second (FPS), adeptly meeting the demands of agricultural scenarios. [ABSTRACT FROM AUTHOR]

Tomatoes are frequently challenged by various pathogens, among which Phytophthora capsici (P. capsici) is a destructive soil‐borne pathogen that seriously threatens the safe production of tomatoes. Plant growth‐promoting rhizobacteria (PGPR) positively induced plant resistance against multiple pathogens. However, little is known about the role and regulatory mechanism of PGPR in tomato resistance to P. capsici. Here, we identified a new strain Serratia plymuthica (S. plymuthica), HK9‐3, which has a significant antibacterial effect on P. capsici infection. Meanwhile, stable colonization in roots by HK9‐3, even under P. capsici infection, improved tomato growth parameters, root system architecture, photosynthetic capacity, and boosted biomass. Importantly, HK9‐3 colonization significantly alleviated the damage caused by P. capsici infection through enhancing ROS scavenger ability and inducing antioxidant defense system and pathogenesis‐related (PR) proteins in leaves, as evidenced by elevating the activities of peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), and chitinase, β‐1,3‐glucanase, and increasing the transcripts of POD, SOD, CAT, APX1, PAL1, PAL2, PAL5, PPO2, CHI17 and β‐1,3‐glucanase genes. Notably, HK9‐3 colonization not only effectively improved soil microecology and soil fertility, but also significantly enhanced fruit yield by 44.6% and improved quality. Our study presents HK9‐3 as a promising and effective solution for controlling P. capsici infection in tomato cultivation while simultaneously promoting plant growth and increasing yield, which may have implications for P. capsici control in vegetable production. [ABSTRACT FROM AUTHOR]

The pests and agricultural diseases are estimated to be responsible for the loss of ten percent of the annual productivity throughout the globe. Most farmers are unable to identify visually, whether a crop has been infected with a disease or not. This is due to a lack of crop morphological knowledge, or a lack of technical knowledge about disease forecast, or temporal features understanding in protecting the crops from being afflicted in the future. The high variability and complexity of leaf diseases, which make accurate identification difficult, is the principal barrier in tomato leaf disease detection. Convolutional Neural Networks (CNN) and U-Net architecture-based models can be implemented to address this issue. In our method, deep learning associated image processing techniques facilitate the preprocessing of tomato leaf images, enhancement of leaf image quality for feature extraction, and extraction of pertinent information for accurate leaf disease diagnosis. CNN enables efficient feature extraction, whereas U-Net enables accurate segmentation and localization of disease areas in tomato leaf images, resulting in enhanced disease detection and diagnosis. Our model uses images of tomato leaves, to construct a deep learning model, which uses a sequential model to identify illnesses, which affect plants. After using the U-Net architecture for image segmentation and localization, the convolutional neural network is capable of carrying out classification of tomato leaf diseases with an accuracy of 92.77% on training dataset, 94.85% on testing dataset and 83% on random generated dataset. [ABSTRACT FROM AUTHOR]

Tomato fruit blotch virus (ToFBV) (Blunervirus solani, family Kitaviridae) was firstly identified in Italy in 2018 in tomato plants that showed the uneven, blotchy ripening and dimpling of fruits. Subsequent High-Throughput Sequencing (HTS) analysis allowed ToFBV to be identified in samples collected in Australia, Brazil, and several European countries, and its presence in tomato crops was dated back to 2012. In 2023, the virus was found to be associated with two outbreaks in Italy and Belgium, and it was included in the EPPO Alert list as a potential new threat for tomato fruit production. Many epidemiologic features of ToFBV need to be still clarified, including transmission. Aculops lycopersici Massee (Acariformes: Eriophyoidea), the tomato russet mite (TRM), is a likely candidate vector, since high population densities were found in most of the ToFBV-infected tomato cultivations worldwide. Real-time RT-PCR tests for ToFBV detection and TRM identification were developed, also as a duplex assay. The optimized tests were then transferred to an RT-ddPCR assay and validated according to the EPPO Standard PM 7/98 (5). Such sensitive, reliable, and validated tests provide an important diagnostic tool in view of the probable threat posed by this virus–vector system to solanaceous crops worldwide and can contribute to epidemiological studies by simplifying the efficiency of research. To our knowledge, these are the first molecular methods developed for the simultaneous detection and identification of ToFBV and TRM. [ABSTRACT FROM AUTHOR]

Tomato (Solanum lycopersicum) is the most important vegetable and fruit crop in the family Solanaceae worldwide. Numerous pests and pathogens, especially viruses, severely affect tomato production, causing immeasurable market losses. In Taiwan, the cultivation of tomato crops is mainly threatened by insect-borne viruses, among which pepper veinal mottle virus (PVMV) is one of the most prevalent. PVMV is a member of the genus Potyvirus of the family Potyviridae and is non-persistently transmitted by aphids. Its infection significantly reduces tomato fruit yield and quality. So far, no PVMV-resistant tomato lines are available. In this study, we performed nitrite-induced mutagenesis of the PVMV tomato isolate Tn to generate attenuated PVMV mutants. PVMV Tn causes necrotic lesions in Chenopodium quinoa leaves and severe mosaic and wilting in Nicotiana benthamiana plants. After nitrite treatment, three attenuated PVMV mutants, m4-8, m10-1, and m10-11, were selected while inducing milder responses to C. quinoa and N. benthamiana with lower accumulation in tomato plants. In greenhouse tests, the three mutants showed different degrees of cross-protection against wild-type PVMV Tn. m4-8 showed the highest protective efficacy against PVMV Tn in N. benthamiana and tomato plants, 100% and 97.9%, respectively. A whole-genome sequence comparison of PVMV Tn and m4-8 revealed that 20 nucleotide substitutions occurred in the m4-8 genome, resulting in 18 amino acid changes. Our results suggest that m4-8 has excellent potential to protect tomato crops from PVMV. The application of m4-8 in protecting other Solanaceae crops, such as peppers, will be studied in the future. [ABSTRACT FROM AUTHOR]

The availability of water is a major concern in regions with limited water resources. In such regions, the focus of irrigation management shifted from producing per unit area to producing per unit of water consumed, water productivity. An experiment was carried out, for two consecutive years(2020 and 2021) at the research farm of Shire-Maitsebri Agricultural Research Center, Tselemty district, Tigray, Ethiopia to exmine the response of tomato to deficit irrigation at various growth stages. A randomized complete block design with three replications was used. Combination of three irrigation regimes (100%, 50%, and 25% of full irrigation requirement) and four FAO-defined tomato growth stages (initial, developmental, mid, and late seasons) were considered to form a total of nine treatments. Data on agronomy and irrigation water were collected and analyzed statistically. The results revealed that reducing irrigation amount up to 75% during the development growth stage significantly decreased marketable yield by 66.5%. However, the highest water use efficiency (9.2 kg/m3) was achieved by reducing irrigation amount by 75% during the end-growth stage of tomatoes. Treatments with the lowest water use efficiency (3.5 kg/m3) were those receiving 75% less irrigation amount than the full requirement during the development growth stage. Reducing irrigation to less than 75% of the full requirement during tomato development stages can greatly impact marketable yield and water use efficiency. Therefore, the tomato crop is highly susceptible to water stress when receiving more than 50% of the full irrigation requirement during its developmental growth stage. [ABSTRACT FROM AUTHOR]

The tomato variety 'Provence' was used as the material, and the artificial light supplement test was carried out in the double-arch steel frame solar greenhouse, and T1 (2R3B, the ratio of red/blue light beads R:B=2:3), T2 (4R1B), T3 (6R1B), T4 (7R1B) four groups of red and blue light treatments were set up, and no artificial light was used as the control (CK) to explore the optimal red and blue light ratio for greenhouse tomato growth and photosynthetic response. The results showed that after 35 days of T1 treatment, the plant height, SPAD, transpiration rate (Tr) and photochemical quenching coefficient (qP) of tomato were significantly increased by 26.7%, 19.6%, 107.6% and 34.3%, respectively, compared with the control group. After 35 days of T3 treatment, the stem diameter, flower number, net photosynthetic rate (Pn), intercellular CO2 concentration (Ci), stomatal conductance (Gs), actual photochemical efficiency (ΦPSII) and electron transport rate (ETR) of tomato were significantly increased by 26.9%, 38.6%, 133.7%, 5.9%, 183.3%, 31.3% and 30.9%, respectively, compared with the control group. After 35 days of T4 treatment, the maximum photochemical efficiency (Fv/Fm) was significantly increased by 4.0% compared with the control group. Compared with the control group, the growth and photosynthesis of tomato could be significantly promoted under different red and blue light supplement treatments. Among the four red and blue combination light treatments of 2R3B, 4R1B, 6R1B and 7R1B in this experiment, the comprehensive effect of each index under 6R1B treatment was the best, which could provide some theoretical guidance for LED light supplement in greenhouse tomato cultivation. [ABSTRACT FROM AUTHOR]

Agrivoltaics or agrophotovoltaics (APV), which simply describes farming under a canopy of PV panels, has been recently gaining a wider implementation to improve farming yields as well as generate electricity on the same piece of land. The presented study undertakes an economic analysis to justify the implementation of agrivoltaics in a tomato farm. Three research cases are investigated; Case 1 is the control scenario which is just ordinary tomato farming that is used as a baseline. And then there are Cases 2 and 3, which are low‐density and high‐density agrivoltaics, respectively. The farm is irrigated from a borehole using a diesel generator in Case 1 and solar pumps in the Agrivoltaics Cases 2 and 3. The study found that tomato harvest is reduced by a minimum of 16% in agrivoltaics setup. However, this reduced harvest is compensated by the PV output. The payback period has been calculated considering the capital costs of the PV system and other operational costs within the farm, and it is found that Case 2 and Case 3 have 3 years and 3.6 years payback periods, respectively. While on the other hand, ordinary tomato farming is unattractive with a lengthy payback period of 17.5 years. Net present value analysis is also used to determine the profitability of the three scenarios over a 10‐year period, and the agrivoltaics scenarios are calculated to be profitable while ordinary tomato farming is not profitable. Therefore, this study justifies economic investment in agrivoltaics for tomato farming in Botswana. [ABSTRACT FROM AUTHOR]

The aim of this work was to determine the effect of saturating the irrigation solution with air (MNBA) or oxygen nanobubbles (MNBO) on relevant agronomic, productive, and postharvest parameters of tomato crops (Solanum lycopersicum L.) in greenhouses. As a control, conventional management was established, without nanobubbles, under the best possible agronomic conditions used in commercial greenhouses in southeastern Spain. No significant differences were found in the soil properties analysed or in the ionic concentration of the pore water extracted with Rhizon probes. Both MNBA and MNBO modified the root distribution and improved the N uptake efficiency and field water uptake efficiency compared to the control. MNBA had the highest harvest index. The total or marketable production was not affected, although it did increase the overall size of the fruit and the earliness with which they were produced compared to the control. MNBA significantly decreased titratable acidity and soluble solids content compared to the control in the last harvests. Both nanobubble treatments improved postharvest storage under room-temperature (20–25 °C) conditions. [ABSTRACT FROM AUTHOR]

Biostimulants (Bio-effectors, BEs) comprise plant growth-promoting microorganisms and active natural substances that promote plant nutrientacquisition, stress resilience, growth, crop quality and yield. Unfortunately, the effectiveness of BEs, particularly under field conditions, appears highly variable and poorly quantified. Using random model meta-analyses tools, we summarize the effects of 107 BE treatments on the performance of major crops, mainly conducted within the EU-funded project BIOFECTOR with a focus on phosphorus (P) nutrition, over five years. Our analyses comprised 94 controlled pot and 47 field experiments under different geoclimatic conditions, with variable stress levels across European countries and Israel. The results show an average growth/yield increase by 9.3% (n=945), with substantial differences between crops (tomato > maize > wheat) and growth conditions (controlled nursery + field (Seed germination and nursery under controlled conditions and young plants transplanted to the field) > controlled > field). Average crop growth responses were independent of BE type, P fertilizer type, soil pH and plant-available soil P (water-P, Olsen-P or Calcium acetate lactate-P). BE effectiveness profited from manure and other organic fertilizers, increasing soil pH and presence of abiotic stresses (cold, drought/heat or salinity). Systematic meta-studies based on published literature commonly face the inherent problem of publication bias where the most suspected form is the selective publication of statistically significant results. In this meta-analysis, however, the results obtained from all experiments within the project are included. Therefore, it is free of publication bias. In contrast to reviews of published literature, our unique study design is based on a common standardized protocol which applies to all experiments conducted within the project to reduce sources of variability. Based on data of crop growth, yield and P acquisition, we conclude that application of BEs can save fertilizer resources in the future, but the efficiency of BE application depends on cropping systems and environments. [ABSTRACT FROM AUTHOR]

An experiment was conducted during kharif season to investigate the performance of tomato cultivation under plastic mulch and without mulch condition. Five different treatments were designed in which T1-Lakshmi, T2-Swaraksha, T3-Swarna Sampda, T4-Vidya and T5-Ashok varieties were sown under drip irrigated fertigation system with four replications. The mortality rate of T1, T2 and T3 were 22.5%, 24.2% and 25.3% more as compared to without plastic mulch condition. It was observed that mulch condition that weeds was found to be very low in comparison to without mulch condition which was 42 g/m² and 1665 g/m² respectively. The highest yield of 19.2 t/ha was recorded for treatment T1 (Lakshmi) under plastic mulch condition. The statistical analysis revealed that during kharif season cultivation of tomato crops under mulch condition is more profitable in comparison to without mulch condition. [ABSTRACT FROM AUTHOR]

Salt stress is a major factor restricting the growth, distribution, and yield of crops. Previous studies on NRT (nitrate transporter) have mainly focused on the nitrogen transport and response to metal ion stress. Suaeda salsa L. is a characteristic halophyte that can grow normally at a salt concentration of 200 mM. In this study, we want to know the S. salsa's NRT-related genes and whether they can improve plant salt stress. So we use bioinformatics and molecular biology to verify our hypothesis. Transcriptome data revealed that the S. salsa NRT1.1D (SsNRT1.1D) gene was upregulated under salt stress. The SsNRT1.1D open reading frame is 1743 bp and has MFS and PTR2 conserved domains. Subcellular localization revealed that SsNRT1.1D is primarily located in the endoplasmic reticulum. qRT-PCR results showed that SsNRT1.1D gene is mainly expressed in S. salsa leaves. The expression of the SsNRT1.1D gene in S. salsa leaves was highest at 12 h after 400 mM sodium chloride (NaCl) treatment. Transgenic tomato plants containing the overexpression vector (35S::SsNRT1.1D) were generated and grown under field conditions to obtain the T3 generation transgenic tomato seeds. The results showed that transgenic tomato plants had higher salt tolerance than the wild-type plants. Overall, our results demonstrate that the SsNRT1.1D gene can improve plant salt tolerance. This study provides a theoretical basis for improving the utilization of saline-alkaline land and the yield of tomatoes. [ABSTRACT FROM AUTHOR]

Due to the influence of the Asian southwest monsoon, seasonal drought is serious and water resources are scarce in the Yunnan province of Southwest China. More effective water-saving irrigation methods should be developed to solve the problem of water scarcity in the dry season. In this study, a subsurface drip irrigation method was used to improve the water productivity of tomato cultivation. Deficit irrigation was conducted. We controlled the lower limit of soil moisture at three different levels (55~65%, 65~75%, and 75~85% of the field capacity). The results indicated that the subsurface drip irrigation treatment significantly increased tomato height in the later stage of tomato growth. Due to the buried pipes, the root/shoot ratio was 8~18% higher for subsurface drip irrigation than for surface drip irrigation methods. Though the yields using subsurface drip irrigation methods were slightly lower than those obtained using surface drip irrigation methods, the tomato quality and water productivity improved significantly. The subsurface drip irrigation methods improved the water productivity by 8.5~21.8% at different soil moisture levels and improved the chlorophyll content by 9.1~17.3%. The VC, soluble sugar, soluble solids, and the ratio of sugar to acid increased by 6.5~15.2%, 7.3~21.6%, 4.1~6.6%, and 3.2~20.8%. This study also indicated that by optimizing the irrigation methods and patterns, water productivity and fruit quality could be improved by more than 50%. This research will be helpful for guiding irrigation during the drought season in the southwest monsoon area in Asia. [ABSTRACT FROM AUTHOR]

Aculops lycopersici (Acari: Eriophyoidea) is a pest in tomato cultivation worldwide. In recent years, the number of reports of A. lycopersici infestations in tomato have increased in Germany. In the first half of 2019, a survey of 50 tomato producing farms was conducted to assess the occurrence of A. lycopersici and the impact this pest has on tomato cultivation in Germany. The participating farms represented ~ 3.5% of the 1448 farms in Germany with protected tomato production in 2019. Total tomato production area considered in the survey was 131.8 ha which corresponds to ~ 34% of the 385.63 ha of protected tomato production area in Germany in this year. A. lycopersici presence was reported by 33 of the 50 surveyed farms, within the last 5 years. Amongst these 50 participants it was the pest with the highest relative importance in terms of plant protection effort exerted. A. lycopersici occurrence was reported more frequently from production systems with a higher intensification. For instance, heating in cold months and a larger production area were considered intensification factors in this study. However, due to autocorrelation between intensification factors it was not possible to link increased occurrence to specific factors. As the intensification factors favouring A. lycopersici occurrence are more prevalent in integrated production, those farms faced A. lycopersici occurrence more often than the organic growers in this study. Plant protection strategies often combine broad treatments of sulphur with local abamectin treatments, removal of infested plant material and the introduction of natural enemies. [ABSTRACT FROM AUTHOR]

The cultivation area and production amount of tomato, which is economically important and included in plant production, is decreasing every year. In this research, which examines the problems of producers in the production and marketing of labor-intensive and high-cost tomato production, the situation of quit tomato cultivation is also examined. A survey was conducted with 76 tomato producers in the villages of Tokat province. It has been observed that the producers among the active working population have 25 years of tomato growing experience and their education level is at primary school level. While the biggest problem of tomato producers in production is disease and product loss, the biggest problem in marketing is low prices and price instability. It was determined that 49% of producers gave up tomato cultivation. The reasons why producers give up tomato production are; Because it is not profitable, product disease is a product marketing problem and input costs are high. In line with the research results, it may be recommended that producers organize seminar courses on the disease. It is thought that both product and price stability can be achieved by developing policies for price instability and, most importantly, by establishing marketing cooperatives specific to this product in the region. [ABSTRACT FROM AUTHOR]

Background: Phosphorus (P) fertilizers, made from rock phosphate, increase crop yields. However, rock phosphate is a finite resource, stressing the need for more P‐efficient crops. Aims: This study aims to exploit P‐adaptive traits that enhance P‐acquisition and P‐use efficiency in crops, as a potential sustainable P‐use management method in agricultural settings. Methods: This study investigates the biostimulant effects of Aphanothece sp. extracts (ApE) on P absorption efficiency traits of tomato plants supplied with triple super phosphate fertilizer (0.3, 0.6, and 1.2 mM Pi). Results: ApE extracts exhibited significant effects on P uptake, Lycopersicum esculentum high‐affinity phosphate transporter (LePT) genes, chlorophyll, and lipid contents, compared with control plants. ApE significantly enhanced leaf LePT4 in ApE‐treated plants supplied with 0.3 mM Pi, and root LePT2 in ApE‐treated plants supplied with 0.6 mM Pi. According to principal component analysis, P concentration in roots (root Pi) was closely associated with root dry weight (DW), root LePT2, and leaf LePT4. The phytohormone, gibberellin gibberellic acid 4, slightly correlated with root Pi, LePT2 (0.18), LePT4 (0.28), and more with root (0.72) and shoot DW (0.60), whereas abscisic acid correlated with chlorophyll content (0.60), LePT2 (0.50), and LePT4 (0.49), and slightly with root Pi (0.22). Gas chromatography–mass spectrometry analysis also showed that the application of ApE to plants stimulated the biosynthesis of several metabolites. The metabolic pathway analysis using MetaboAnalyst revealed that ApE treatment induced the unsaturated fatty acid, steroid, cutin, suberin, and wax biosynthesis pathways. Conclusions: ApE application to tomato plants stimulated P uptake by roots through enhanced expression of high‐affinity P transporters (root LePT2 and leaf LePT4), positively correlated with root DW and root Pi. The study also suggests that algal extracts stimulate plant growth through improved P uptake and modulate the plant's metabolic pathways that favor crop performance in tomato plants under normal Pi conditions. [ABSTRACT FROM AUTHOR]

Background: Tomato (Lycopersicon esculentum Mill) is a widely cultivated vegetable crop worldwide, including in Fiji. However, the suitability of tomato cultivation under greenhouse conditions in the central region of Fiji, which experiences salinity issues, remains unclear. Methods: A pot experiment was conducted at the Instructional Agricultural Farm Complex of the College of Agriculture, Fisheries and Forestry, Fiji National University, Fiji, to determine the effect of different levels of salinity on the growth and yield of tomato (Lycopersicon esculentum Mill) varieties. The experiment included two factors: three tomato varieties (V1= Melrose; V2= Alton; V3= Alafua Large) and four levels of NaCl salinity (T1= Control; T2= 2 dSm-1; T3= 4 dSm-1 and T4= 8 dSm-1) randomized thrice in a randomized complete block design. The effects of various varieties and salinity levels on tomato yield were studied in this experiment. Result: The results revealed that variety Alafua Large performed comparatively better in all cases. This recorded maximum fruit length (4.22 cm), fruit breadth (3.31 cm), individual fruit weight (45.60 g), number of fruits (7.83) and fruit yield (352.10 g) whereas Alton recorded the minimum of the above yield attributes. In the case of the combined effect of variety and salinity, Alafua Large showed better yield (432.17 g and 394.51 g) per plant than the other varieties when combined with the lower salinity level i.e., EC 2 dSm-1 and 4 dSm-1, respectively. The yield of tomato varieties declined with the increasing salinity level condition. The yield of Alafua Large was 194.54 g when applied with the highest level of salinity i.e., EC 8 dSm-1 and the yield of Alton was 64.69 g which was the lowest yield among the varieties with the highest level of salinity condition. Therefore, from the results, Alafua Large is comparatively more salt tolerant than the other varieties which were studied in this experiment. [ABSTRACT FROM AUTHOR]

To compare the economics of different systems of organic tomato production, two models were created, one assuming outdoor production, and the other representing production in a protected area under a greenhouse, based on the data obtained through interviews with organic tomato producers from Vojvodina. The cost and sensitivity analysis revealed that the greenhouse model yields better results overall (a financial result of €273/100 m2 compared to €58/100 m2), despite the higher costs due to amortization, interest and costs related to the higher yield obtained. The production model also showed less dependence on the change in organic tomato yield and price, as well as key cost groups and post-harvest losses, which in both cases were mediated by growing coriander as an intercrop. This research improves the knowledge of the economics of organic tomato cultivation and at the same time proposes a methodology to analyze the economic impact of other organic productions. [ABSTRACT FROM AUTHOR]

Tomato (Solanum lycopersicum L.) ranks as the second most important vegetable crop globally, but its production and quality are known to be largely affected by many pest and diseases. One of the major hindrances to tomato production is the fungal disease caused by Alternaria spp. In the current study we isolated, visually examined and characterized the fungal pathogen both morphologically and at the molecular level were carried by employing standard techniques for tissue isolation, microscopic observations and PCR methods. Under the microscope, morphological features like dark brown to blackish mycelium with prominent septations and muriform conidia with horizontal and transverse septations were observed. To delve deeper into their genetic makeup, the molecular characterization of pathogens was done by amplification, sequencing of Internal Transcribed Spacer (ITS1/ITS4) and phylogenetic analysis. This allowed us to gain insights into the genetic identity of these pathogens. Furthermore, phylogenetic analysis shed light on the evolutionary relationships within the group of fungi we studied. This comprehensive approach provides a deeper understanding of Alternaria spp. in the context of tomato cultivation and offers valuable knowledge for disease management and sustainable tomato production. [ABSTRACT FROM AUTHOR]

Featured Application: This study explores the potential application of tomato fruit production within the agrivoltaic system, aiming to evaluate its contribution to food security in the context of climate change. Specifically, the study compares tomato cultivation under agrivoltaic conditions with shaded areas created by PV panels to traditional cultivation under full sunlight conditions. The experiments primarily focus on investigating the impact of different watering conditions in both shaded areas and the full sunlight, in order to discern the differences in yield and tomato fruit quality. Climate change, with rising temperatures, water crises, and an increased frequency of climate disturbances, poses a threat to the ability of agroecosystems to ensure human access to food by affecting both the quantity and quality of crop production. Currently, there is growing knowledge about the fact that agrivoltaic systems may represent a direct strategy to cope with climate change driven by carbon dioxide emissions for energy production, preserving the capacity of agroecosystems to maintain food security. The aim of this work was to investigate the impact of environmental conditions generated by photovoltaic (PV) panels for sustaining open-field tomato (Solanum lycopersicum L.) fruit production under varying water supply regimes. Tomato plants were grown beneath PV panels or in full sunlight. In each scenario, two plots with an equal number of plants were subjected to different irrigation levels: high watering (HW) and low watering (LW). The results showed a lower number of tomato fruit produced grown under the PV panels, with an increased fruit size and water content under a normal water supply. The Brix degrees of the tomato fruits grown under the panel were more comparable to the fruits commercially available on the market than the Brix degree of the fruits grown in open-field sunlight. Thus, our data supported the conclusion that the agrivoltaic system, in the context of climate change with the enduring drought and long-term water scarcity, can be a good adaptation strategy to maintain favorable tomato production compared to the full sunlight conditions. Furthermore, these results can be important for planning breeding programs, since in many cases, the tomato fruits grown in full sunlight were seedless. [ABSTRACT FROM AUTHOR]

Water scarcity has necessitated the adoption of water-saving techniques in both protected and non-protected farming. This study aimed to evaluate the performance of a water-saving soilless cultivation technique and compare it to conventional soil-based cultivation in protected farming. The soilless technique utilized local gravel and a mixture of peat moss, humin-substrate, and perlite in a 4:3:1.5 ratio. During the tomato growth cycle, three irrigation regimes were imposed using drip irrigation: 8 Lh−1 design discharge (D1) emitters, 6 Lh−1 design discharge (D0.75) emitters, and 4 Lh−1 design discharge (D0.5) emitters for both cultivation methods. Vegetative growth, fruit yield, and water consumption were measured and water productivity was determined. Additionally, an economic assessment was conducted by estimating and comparing economic coefficients for both cultivation methods. Estimated coefficients included revenues, net profit, benefit–cost ratio, breakeven levels of production and prices, revenues over variable cost, and revenues on investment. The tomato fruit yield under soil-based cultivation surpassed the yield under soilless cultivation. Water productivity under soilless cultivation was nearly double (24.3 kg m−3) that of soil-based cultivation (15.5 kg m−3). Soilless cultivation saved 50% of the irrigation water applied by the conventional soil-based method, conserving energy and protecting the soil from deterioration. Revenues and net profits, driven by higher yield and lower variable costs, favored soil-based cultivation. The economic assessment demonstrated that both cultivation methods were economically viable. However, the soil-based cultivation method was more profitable due to its higher fruit yield. Overall, the results of this study suggest that the soilless cultivation technique is a feasible option for water-saving cultivation. However, the soil-based cultivation method remains more profitable due to its superior fruit yield. The soilless cultivation technique offers significant water savings but needs further improvements to achieve comparable economic returns to traditional farming. [ABSTRACT FROM AUTHOR]

A consumption of 46.9 million tons of processed tomatoes was reported in 2022 which is merely 20% of the total consumption. An increase of 3.3% in consumption is predicted from 2024 to 2032. Tomatoes are also rich in iron, potassium, antioxidant lycopene, vitamins A, C and K which are important for preventing cancer, and maintaining blood pressure and glucose levels. Thus, tomatoes are globally important due to their widespread usage and nutritional value. To face the high demand for tomatoes, it is mandatory to investigate the causes of crop loss and minimize them. Diseases are one of the major causes that adversely affect crop yield and degrade the quality of the tomato fruit. This leads to financial losses and affects the livelihood of farmers. Therefore, automatic disease detection at any stage of the tomato plant is a critical issue. Deep learning models introduced in the literature show promising results, but the models are difficult to implement on handheld devices such as mobile phones due to high computational costs and a large number of parameters. Also, most of the models proposed so far work efficiently for images with plain backgrounds where a clear demarcation exists between the background and leaf region. Moreover, the existing techniques lack in recognizing multiple diseases on the same leaf. To address these concerns, we introduce a customized deep learning-based convolution vision transformermodel. The model achieves an accuracy of 93.51% for classifying tomato leaf images with plain as well as complex backgrounds into 13 categories. It requires a space storage of merely 5.8 MB which is 98.93%, 98.33%, and 92.64% less than state-of-the-art visual geometry group, vision transformers, and convolution vision transformermodels, respectively. Its training time of 44 min is 51.12%, 74.12%, and 57.7% lower than the above-mentioned models. Thus, it can be deployed on (Internet of Things) IoT-enabled devices, drones, or mobile devices to assist farmers in the real-time monitoring of tomato crops. The periodicmonitoring promotes timely action to prevent the spread of diseases and reduce crop loss. [ABSTRACT FROM AUTHOR]

Modern greenhouses are characterized by scale, standardization, and efficiency. Some indoor agricultural facilities spread across over $100000~{\mathrm {m^{2}}}$ while being inhabited by dozens of species in a fragile balance. Timely monitoring is crucial for these greenhouses, and both speed and precision are required to minimize the potential yield loss. Human inspection is prone to error and time-consuming, thus expensive. On the other hand, collecting samples and analyzing them in the laboratory outside the agricultural facility is even more time-consuming and economically infeasible. Consequently, inspection by an autonomous robot that performs visual plant analysis gains traction. This work is devoted to the data acquisition and training of a neural network-based classifier that solves the problem of powdery mildew identification. The data collection was performed with user-grade RGB cameras while in motion. The infection identification accuracy of 85% was reached with a small computational load on the robot’s computer, which proves that the target problem could be solved under challenging circumstances. In order to carry out the experiments, an autonomous robot capable of greenhouse monitoring was developed and tested in a real environment. It is supposed to be deployed in modern greenhouses equipped with rails.

The yield, quality, and water–fertilizer use efficiency of crops are important parameters for assessing rational water and fertilizer management. For an optimal water and fertilizer system with respect to the nutrient solution irrigation of greenhouse tomatoes using cultivation substrates, a two-year greenhouse cultivation experiment was conducted from 2022 to 2023. Three drip fertigation treatments (T1, T2, and T3) were implemented in the experiment, where nutrient solutions were supplied when the substrate's water content reached 60%, 70%, and 80%. The frequency of nutrient solution applications is based on weighing coconut coir strips in the morning and evening at 7:00 to determine the daily water consumption of plants. Nutrient solutions were supplied when the substrate's water content reached the lower limit, and the upper limit for nutrient supply was set at 100% of the substrate water content. The nutrient solution application was carried out multiple times throughout the day, avoiding the midday heat. The nutrient solution formula used was the soilless tomato cultivation formula from South China Agricultural University. The results show that plant height and the leaf area index rapidly increased in the early and middle stages, and later growth tended to stabilize; the daily transpiration of tomatoes increased with an increase in nutrient solution supply, and it was the greatest in the T3 treatment. Between the amount of nutrient solution application and the number of years, the yield increased with the increase of the amount of nutrient solution, showing T3 > T2 > T1. Although the average yield of the T2 treatment was slightly lower than that of the T3 treatment by 3.65%, the average irrigation water use efficiency, water use efficiency, and partial fertilizer productivity of the T2 treatment were significantly higher than those of the T3 treatment by 29.10%, 19.99%, and 28.89%, respectively (p < 0.05). Additionally, soluble solid, vitamin C, and soluble sugar contents and the sugar–acid ratio of tomatoes in the T2 treatment were greater than those in the other two treatments (p < 0.05). Using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, it was concluded that the nutrient solution application rate of 70% can significantly increase water and fertilizer use efficiency and markedly improve the nutritional and flavor quality of the fruit without a significant reduction in yield. This finding provides significant guidance for the high-yield, high-quality, and efficient production of coconut coir-based cultivated tomatoes in greenhouses. [ABSTRACT FROM AUTHOR]