Search Results (1,871)

Constructing a temperature and humidity prediction model for greenhouse-grown tomatoes is of great significance for achieving resource-efficient and sustainable greenhouse environmental control and promoting healthy tomato growth. However, traditional models often struggle to simultaneously capture long-term temporal trends, short-term local dynamic variations, and the coupling relationships among multiple variables. To address these issues, this study develops an iT-LSTM-CA multi-step prediction model, in which the inverted Transformer (iTransformer, iT) is employed to capture global dependencies across variables and long temporal scales, the Long Short-Term Memory (LSTM) network is utilized to extract short-term local variation patterns, and a cross-attention (CA) mechanism is introduced to dynamically fuse the two types of features. Experimental results show that, compared with models such as Gated Recurrent Unit (GRU), Temporal Convolutional Network (TCN), Recurrent Neural Network (RNN), LSTM, and Bidirectional Long Short-Term Memory (Bi-LSTM), the iT-LSTM-CA achieves the best performance in multi-step forecasting tasks at 3 h, 6 h, 12 h, and 24 h horizons. For temperature prediction, the R² ranges from 0.96 to 0.98, with MAE between 0.42 °C and 0.79 °C and RMSE between 0.58 °C and 1.06 °C; for humidity prediction, the R² ranges from 0.95 to 0.97, with MAE between 1.21% and 2.49% and RMSE between 1.78% and 3.42%. These results indicate that the iT-LSTM-CA model can effectively capture greenhouse environmental variations and provide a scientific basis for environmental control and management in tomato greenhouses. Full article

For future Mars colonization, crop production will be a challenge due to the chemical composition of the Martian Regolith, which contains perchlorates and heavy metals. This research was conducted to determine if the use of Arbuscular Mycorrhizal Fungi (AMF), Plant Growth-Promoting Bacteria (PGPB), and fertilization have a positive effect on tomato growth in a Martian Regolith Analog. The analog contains 52.54% SiO₂, 1.81% TiO₂, 17.66% Al₂O₃, 9.46% Fe₂O₃, 0.145% MnO, 3.43% MgO, 7.09% CaO, 3.95% Na₂O, 1.96% K₂O, and 0.55% P₂O₅. Two hundred and forty tomato plants were grown for 45 days. One hundred and twenty tomato plants grown over perchlorate-polluted analog (1% m/m) died in less than 2 weeks, while 120 tomato plants grown in a non-polluted analog survived. Forty-eight plants supplemented with Long–Ashton solution increased their shoot length 100% more than the control plants and the plants inoculated with the commercial AMF formulation TM-73^MR and PBB; the latter showed 25% mycorrhizal colonization. There was no significant difference between the growth parameters of inoculated plants and non-inoculated plants. However, there was a significant difference compared to the plants supplemented with Long–Ashton solution. The perchlorate is toxic to tomato plants, and the metal content of the analog was not a limiting factor for tomato growth or AMF colonization. Full article

Root restriction is an agronomic technique that influences plant morphology, physiology, and productivity. This study investigates the effects of root restriction on tomato growth, fruit quality, yield, and rhizosphere microbial communities using three distinct substrates: sand, soil, and peanut shell substrate (PSS), within a Simplified Automatic Soilless Culture System (SAS). Results demonstrated that root restriction at 8 cm height significantly enhanced fruit quality indicators: soluble sugar content increased by 69.01% (sand), 53.84% (soil), and 37.67% (PSS); soluble protein increased by 77.23%, 48.14%, and 66.51%; and lycopene increased by 100.03%, 62.33%, and 74.59%, respectively, compared to the 24 cm baseline. However, single-plant yield declined by 28.30% (sand), 64.28% (soil), and 22.06% (PSS). TOPSIS analysis (Technique for Order Preference by Similarity to Ideal Solution) identified PSS at 8 cm as the optimal combination for balancing quality and yield (Cj = 0.631). Microbial amplicon sequencing revealed higher rhizosphere microbial diversity in tomatoes grown in soil and peanut shell substrate compared to sand. These three types of growing media (soil, sand, and peanut shell substrate) establish the rhizosphere of bacterial and fungal communities by selecting specific microbial taxa. Changes in container height drive the reduction–oxidation functional divergence of bacterial communities, affecting the connectivity and complexity of microbial networks. Full article

To further improve the prediction accuracy for greenhouse crop evapotranspiration (ET) under different irrigation conditions and enhance irrigation water use efficiency, this study proposes three methods to revise the Priestley–Taylor (PT) model coefficient α for calculating ET at different growth stages: (1) considering the leaf senescence coefficient f_S, plant temperature constraint parameter f_t, and soil water stress index f_sw to correct α (MPT model); (2) combining the Penman–Monteith (PM) model to inversely calculate α (PT-M model); (3) using the machine learning XGBoost algorithm to optimize α (PT-M_(XGB) model). Accordingly, this study observed the cumulative evaporation (Ep) of a 20 cm standard evaporation pan and set two different irrigation treatments (K0.9: 0.9Ep and K0.5: 0.5Ep). We conducted field measurements of meteorological data inside the greenhouse, tomato physiological and ecological indices, and ET during 2020 and 2021. The above three methods were then used to dynamically simulate greenhouse tomato ET. Results showed the following: (1) In 2020 and 2021, under K0.9 and K0.5 irrigation treatments, the MPT model mean coefficient α for the entire growth stage was 1.27 and 1.26, respectively, while the PT-M model mean coefficient α was 1.31 and 1.30. For both models, α was significantly lower than 1.26 (conventional value) during the seedling stage and the flowering and fruiting stage, rose rapidly during the fruit enlargement stage, and then gradually declined toward 1.26 during the harvest stage. (2) Predicted ET (ET_e) using the PT-M model underestimated the observed ET (ET_m) by 8.71~16.01% during the seedling stage and the harvest stage, and overestimated by 1.62~6.15% during the flowering and fruiting stage and the fruit enlargement stage; the errors compared to ET_m under both irrigation treatments over two years was 0.1~3.3%, with an R² of 0.92~0.96. (3) The PT-M_(XGB) model achieved higher prediction accuracy, with errors compared to ET_m under both irrigation treatments over two years of 0.35~0.65%, and R² above 0.98. The PT-M_(XGB) model combined with the XGBoost algorithm significantly improved prediction accuracy, providing a reference for the precise calculation of greenhouse tomato ET. Full article

Background: Proteasomes are protein complexes that mediate proteolysis to degrade unneeded or damaged proteins, and they play an indispensable role in plant growth and development. However, their regulatory effects on tomato fruit quality and the underlying metabolic mechanisms remain largely elusive. This study aimed to elucidate the metabolic regulatory mechanisms of proteasomes in tomato fruits through untargeted metabolome analysis. Methods: An untargeted metabolomics approach was employed to profile the metabolic changes in tomato fruits. Metabolites were detected and identified under both positive and negative ion modes. Metabolic profiles were compared between wild-type (WT) tomato fruits and SlPBB2 RNA interference (SlPBB2-RNAi) lines. Specifically, the SlPBB2-RNAi line refers to a transgenic tomato line constructed via Agrobacterium-mediated transformation, where the expression of the proteasome component gene SlPBB2 was stably downregulated by RNA interference technology to clarify its regulatory role in fruit metabolism. KEGG enrichment analysis was performed to annotate the functions of differential metabolites. Results: A total of 568 and 333 metabolites were identified in positive and negative ion modes, respectively. Comparative analysis revealed 43 differentially abundant metabolites between WT and SlPBB2-RNAi fruits, including D-glucose, pyruvic acid, leucine, and naringenin. KEGG enrichment analysis further identified key metabolites involved in the carbon fixation pathway of photosynthetic organisms, with L-malic acid being a prominent representative. Reduced accumulation of D-glucose and pyruvic acid in SlPBB2-RNAi fruits suggested the inhibition of the citrate cycle, a core pathway in cellular energy metabolism. This metabolic perturbation was associated with decreased chlorophyll content in SlPBB2-RNAi plants, implying impaired photosynthetic carbon fixation and energy metabolism. Conclusions: This study uncovers the metabolic regulatory role of SlPBB2-mediated proteasome function in tomato fruits, providing novel insights into the link between proteasomal activity and fruit metabolic homeostasis from a metabolomic perspective. These findings offer new theoretical foundations for developing strategies to improve tomato nutritional quality. Full article

In facility tomato production, the excessive application ratio of ammonium nitrogen (NH₄⁺-N) often leads to root acidification and calcium-magnesium antagonism. Although amide nitrogen (urea-N) has better buffering properties, it needs to be hydrolyzed before utilization, resulting in a lag effect. Previous studies have mostly focused on a single nitrogen source or a fixed proportion, and there is still a lack of systematic evidence on the nitrogen supply effects of different nitrogen application combinations at different growth stages of tomatoes. Therefore, in this experiment, tomato cultivar ‘Jingfan 502’ was used. All treatments received the same total nitrogen concentration (15 mM), but the nitrogen was supplied as different combinations of ammonium nitrogen (AN) and amide nitrogen (UN). Six AN–UN ratio treatments were designed: CK (0% AN, 0% UN), T1 (100% AN, 0% UN), T2 (0% AN, 100% UN), T3 (25% AN, 75% UN), T4 (50% AN, 50% UN), and T5 (75% AN, 25% UN). T3 (25% NH₄⁺ + 75% urea) increased single-plant yield by 64.04% and 5.10%, and total N, P, K, and Mg accumulation by 29.0% and 20.7%, relative to T1 and T2. In addition, compared to T1 and T2, the nitrogen fertilizer uptake rate of the T3 treatment increased by 17.00% and 24.90%, respectively, and the electrical conductivity (EC) increased by 27.04% and 44.84%, respectively. Redundancy Analysis (RDA) showed that enzyme activities, total N and electrical conductivity were positively linked to microbial communities in T3 and T4, whereas communities in CK, T1, T2 and T5 correlated with nutrients and pH. Under controlled pot conditions, T3 optimizes the rhizosphere micro-environment, enhances microbial abundance and nutrient uptake, and provides a theoretical basis for precise N management in tomato. Full article

Phosphorus (P) is an essential nutrient in plant development, but its availability in the soil is often limited due to chemical fixation and poor solubility. This study presents the development, characterization and evaluation of a novel granular bioinoculant formulated with Aspergillus tubingensis (P-solubilizing) and Trichoderma virens (P-mineralizing) using clinoptilolite (CZ) as a carrier to improve P bioavailability. The formulation process included the evaluation of the proposed components, the standardization of conidia production in different media cultures and conditions, the elaboration and characterization of the bioinoculant and its evaluation in plants. In this study, in vitro analysis demonstrated the synergistic effect of the components, showing that in all treatments with dual inoculation and CZ, the amount of soluble phosphorus (SP) was higher than in their counterparts (from 27.8 to 36.8 mg·L⁻¹). A concentration greater than 1 × 10⁹ CFU·mL⁻¹ was obtained by standardizing the production of conidia in different media (PDA, V8-Agar and Molasses Agar), which were then used to produce granular batches containing at least 2 × 10⁷ CFU·g⁻¹. Furthermore, the size (88% of the granules measured <4.5 mm), purity (<2 CFU·g⁻¹ in 10⁻⁴ dilution), and moisture content of the prototype granules (3.3–3.8%) were confirmed to be within established international quality parameters. Plant evaluations in chili and tomato demonstrated the formulation efficacy, showing an increase in both soluble and foliar P content (with at least 30% more than controls), alongside improvements in all parameters evaluated that are related to plant growth promotion (with at least 15% more growth than controls). The development of this formulation prototype represents a focused effort toward process standardization and optimization required to validate developed formulations, thus promoting the advancement of applied biotechnology. Full article

Salt stress is a major agricultural issue. A promising modern agriculture method is the foliar treatment of zinc oxide nanoparticles (ZnONPs). This approach has shown promise in boosting challenged tomato yields, fruit quality, and leaf extract antibacterial activity against pathogens. A greenhouse experiment was conducted. The previously synthesized and characterized ZnONPs were used to alleviate the harmful effects of NaCl stress. Tomato fruit weight from different treatments was determined, and the gas–liquid chromatography device was used to observe the changes in fatty acid production. The antimicrobial activities of the aqueous and diethyl ether extracts from tomato leaves were determined against six bacterial and six fungal strains. The plants that were salinity-stressed and sprayed with 0.075 and 0.15 g/L ZnONPs showed a better improvement compared to the salinity-stressed plants. Also, the sprayed plants that were not stressed at all showed promising results compared to the control and the other different treatments. Through the process of molecular docking, it was shown that caffeic acid, ferulic acid, p-coumaric acid, sinapic acid, and apigenin-7-glucoside are essential chemicals that possess antibacterial and antifungal effects against the DNA Gyrase inhibitor and the sterol 14-alpha demethylase (CYP51) enzyme, respectively. It is concluded that salt stress can negatively affect the growth, quality, and variant plant features. However, the foliar application of ZnONPs is able to overcome those adverse effects in the stressed plants, and enhance the non-stressed as well. Full article

Calcium (Ca) is essential for tomato (Solanum lycopersicum L.) fruit quality and for preventing physiological disorders such as blossom-end rot. However, high total soil Ca does not necessarily translate into plant-available Ca due to factors such as soil pH and limited mobility. This study evaluated soil Ca availability and the effect of a chicken manure-based soil amendment on the growth and yield of four tomato genotypes (Pony Express F1, Palomo F1, Toro F1, and Perseo F1) grown on a loam–clay–sand soil containing 4886 ppm Ca. In the first cycle, conducted in a shade house, two Ca application levels (0% and 25% of the crop’s requirement) were tested. The 0% treatment outperformed the 25% treatment regarding yield-related traits, indicating that native soil Ca met crop demand; application of 25% Ca reduced total fruit weight and fruit number by 19.7% and 5.9%, respectively, while the 0% treatment produced 40.8% more first-quality fruits. Perseo F1 (Perseo) produced the highest yield of first-quality fruits (20.61 t ha⁻¹), exceeding Pony Express F1 (Pony express), Palomo F1 (Palomo), and Toro F1 (Toro) by 10.8%, 6.6%, and 51.4%, respectively. In a second cycle under open-field conditions, incorporation of the chicken manure amendment significantly enhanced growth and yield: treated plants reached a 0.85 m height 58 days after transplanting, and overall yield increased to 70.08 t ha⁻¹ compared with 50.30 t ha⁻¹ in the control (21.9% increase). These results indicate that, while native soil Ca can satisfy crop requirements under the studied conditions, soil amendment under field conditions substantially improves plant performance and commercial yield potential. Full article

The quality and yield of grafted tomato seedlings are significantly influenced by the selection of high-quality and robust rootstocks. The effectiveness of these rootstocks is dependent on various environmental factors and genetic traits. One of the most critical factors in cultivation is light, as its intensity plays a vital role in seedling growth, overall development, metabolic processes, the efficiency of the photosynthetic system, and other essential plant functions. The aim of this study was to investigate the changes in the photosynthetic system activity and the growth of tomato rootstocks depending on the light intensity. The study was conducted at the Institute of Horticulture, Lithuanian Center for Agricultural and Forestry Sciences, focusing on four tomato rootstock varieties grown in a controlled environment. The plants were grown at a temperature of +23/19 °C and a relative humidity of 55–60%, under different levels of illumination (high-pressure sodium lamps), PPFD: 150, 250 and 350 ± 10 µmol m⁻² s⁻¹. The results indicated that optimal growth and biomass accumulation occurred at around 250 µmol m⁻² s⁻¹, with the most significant growth observed in the rootstocks ‘Auroch’ and ‘Goldrake’. Higher light intensities, specifically at 350 µmol m⁻² s⁻¹, did not consistently enhance growth and could even lead to a reduction in leaf area and overall growth in some cultivars such as ‘Auroch’ and ‘TOR23901’. Although photosynthetic parameters improved with increased light intensity up to 350 µmol m⁻² s⁻¹, these enhancements did not translate into additional growth benefits. Full article

Tomatoes are a rich source of nutrients that are essential for human health. However, in greenhouse environments, the complex growth patterns of tomatoes and stems often result in mutual obstruction and overlapping, posing significant challenges for accurate ripeness detection and stem segmentation. Furthermore, the current detection and segmentation tasks are typically executed in isolation, resulting in suboptimal inference efficiency and substantial computational expenses. To address these issues, this study proposes the YOLOP-Tomato (YOLO-Based Panoptic Perception for Tomato) based on YOLOv8n, enabling simultaneous tomato detection and stem and branch segmentation. Two RSU (ReSidual U-blocks) modules establish feature connection mechanisms between the backbone and head. SPPCTX (SPP Context) was developed at the neck of the model to perform multi-scale contextual feature fusion and enhancement. The SCDown (Spatial-Channel Decoupled downsampling) is employed to lightweight the backbone’s terminal structure. The experimental results demonstrate that YOLOP-Tomato achieves precision, recall, mAP₅₀, and mAP_50–95 of 94.9%, 85.0%, 93.6%, and 60.9% for detection, and mIoU of 77.6% for segmentation. These results represent improvements of 2.5%, 0.1%, 0.5%, 1.1%, and 1.4%, over YOLOv8n. The trained model was deployed on the NVIDIA Jetson AGX Orin platform, an efficient inference speed of 5.67 milliseconds was achieved. The proposed YOLOP-Tomato provides reliable and efficient technical support for tomato detection, ripeness identification, stem and branch segmentation in greenhouses, and holds great significance for improving the level of intelligent agricultural production. Full article

The nitrate signaling core regulator NLP7 is known to negatively regulate salt tolerance in Arabidopsis thaliana, but the function of the (SsNLP7A) gene in the halophyte Suaeda salsa remains unclear. To investigate whether SsNLP7A participates in salt stress responses, this study heterologously overexpressed the gene in tomato (Solanum lycopersicum) and systematically evaluated its function under salt stress through phenotypic, physiological, and transcriptomic analyses. The results indicate that SsNLP7A overexpression significantly promotes tomato root development and alleviates growth inhibition caused by salt stress. Under salt treatment, transgenic plants exhibited significantly higher chlorophyll content, accumulation of osmotic regulators (proline and soluble sugars), and antioxidant enzyme (POD, CAT, SOD) activity compared to wild-type plants. Transcriptome analysis further revealed that SsNLP7A enhances salt tolerance by regulating carbon metabolism, phytohormone signaling pathway, photosynthesis, and antioxidant pathways. Collectively, this study elucidates the positive regulatory role of SsNLP7A in salt stress response, providing new insights into its molecular mechanisms. Full article

Irrigation effects on processing tomato have been comprehensively studied, whereas the integrated effects of irrigation and agronomic measures lack systematic investigations. This study employed a two-year field experiment to investigate the interactive effects of irrigation, fertilizer, and tillage practices on the crop growth, total yield, and fruit quality of processing tomato. The experimental treatments comprised three irrigation levels (full irrigation, mild water deficit, and moderate water deficit), combined with two fertilizer strategies (synthetic fertilizer only and partial substitution of synthetic fertilizer with manure), and two tillage practices (ridge planting and flat planting). It was found that the partial organic fertilizer substitution and the ridge planting significantly improved the total tomato yield by 13.11% and 75.54% on average, respectively, compared to the synthetic fertilizer application and flat planting, although they led to more salt accumulation in the top soil layer. However, the extent of the increase greatly varied over different irrigation levels and years. The mild water deficit led to a yield increase of 9.22% compared to full irrigation, while the moderate water deficit resulted in an obvious yield loss of 25.95%. Moreover, the ridge planting, the partial organic fertilizer substitution, and water deficit had strong positive effects on the fruit quality and the tillage–irrigation interaction had strong effects on the fruit quality, but it showed negligible effects on the tomato yield. In contrast, the tomato yield was very sensitive to the fertilizer–irrigation interaction, while the fruit quality showed nonsignificant sensitivity to the tillage–irrigation interaction. Finally, the combination of ridge planting, partial organic fertilizer substitution, and a mild water deficit was highlighted as a sustainable cropping production system for processing tomato to achieve an enhanced total yield and fruit quality. Full article

As an important plant immune inducer, Dufulin has long been thought to enhance plant resistance to multiple plant viruses through activating the salicylic acid (SA) pathway. However, whether this immune inducer responds to tomato brown rugose fruit virus (ToBRFV) infection in the same way remains uncertain. In this study, we systematically analyzed the multiple effects of Dufulin treatment on the physiological, biochemical and gene expression patterns in tomato under ToBRFV infection. The results showed that the application of Dufulin could significantly increase the chlorophyll content; elevate the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT); reduce the ToBRFV viral load; and enhance plant growth. Moreover, we found that Dufulin treatment could increase both SA and abscisic acid (ABA) contents. However, SA-related genes were not strongly activated as the genes involved in ABA biosynthesis and signal transduction pathways. This suggested that ABA likely plays an unrecognized role in the formation of this induced resistance. Through weighted gene co-expression network analysis (WGCNA) and cis-element analysis of the target gene promoters, we identified that SlABI5-like and SlWRKY4 might be the key potential transcription factor genes for Dufulin-induced tomato resistance to ToBRFV, and constructed their molecular regulatory network. We also conducted qRT-PCR assay to verify the gene expression patterns involved in this study. These findings potentially provide new insights into the mechanism of Dufulin-induced antiviral resistance, and enlarge important molecular targets for ToBRFV prevention and control. Full article

The Gretchen Hagen 3 (GH3) gene family, a key component of the early auxin-responsive gene family, plays a pivotal role in regulating plant growth, development, and stress responses. However, to date, a comprehensive genome-wide analysis of the GH3 gene family and its potential role in plant defense against viruses, such as tomato yellow leaf curl virus (TYLCV), has not been conducted in Nicotiana benthamiana. Here, the GH3 gene family was thoroughly examined in N. benthamiana using a comprehensive genome-wide bioinformatic approach. A total of 25 potential GH3 genes were discovered in N. benthamiana. Phylogenetic analysis classified these NbGH3s into three different clades. Chromosomal distribution and synteny analyses revealed that NbGH3s are unevenly distributed across 14 chromosomes, with 20 segmental and one tandem duplication pairs. Promoter analysis suggested their involvement in phytohormone signaling and stress responses. Quantitative PCR showed that several NbGH3s are transcriptionally responsive to TYLCV infection, with five of them significantly upregulated in infected leaves. Furthermore, virus-induced gene silencing revealed that the suppression of NbGH3-3 and NbGH3-9 markedly increased host susceptibility to TYLCV, underscoring their critical roles in plant antiviral defense mechanisms. This research establishes a framework for understanding the functions of NbGH3s in plant growth and their response to TYLCV infection. Full article