Tomato Cultivation Research Articles

AquaCrop model to optimize water supply for a sustainable processing tomato cultivation in the Mediterranean area: A multi-objective approach

CONTEXTEfficient irrigation management must consider multiple aspects of cropping systems, such as productivity, water use efficiency, and economic viability. Crop simulation models like AquaCrop are essential tools for analyzing crop responses under different irrigation scenarios. Organizing the model's outputs into standardized parameters allows for a multi-objective evaluation, which can be consolidated into a single index for optimizing irrigation strategies. OBJECTIVEThis study aims to formalize the response of processing tomato cropping systems in Southern Italy to various irrigation regimes and develop a framework to identify optimal irrigation volumes for production, water use efficiency, and economic returns. METHODSAquaCrop was used to assess the effects of different seasonal water supplies on dry yield, water use efficiency, and irrigation water use efficiency. Sustainability was evaluated via the blue water footprint and drainage, while economic sustainability was measured through net income and irrigation economic efficiency. A multi-objective evaluation framework was built, developed to consolidate performance indices into a single multi-aggregated index (Imobj). The AquaCrop model was calibrated and validated using field data, with high accuracy in simulating canopy cover, biomass, and dry yield (NRMSE < 30 %, r > 0.90, and d > 0.97). Polynomial regression was used to model the relationships between irrigation volumes and cropping system variables. Each variable was assigned a truth value (TWi), derived from regression coefficients, statistical significance, and model fit. These values were normalized using a sigmoid function and consolidated into the Imobj index, providing an overall measure of irrigation performance. RESULTS AND CONCLUSIONSAquaCrop accurately simulated canopy cover, biomass, and dry yield. Multi-objective analysis showed yield and profitability were most sensitive to irrigation changes, followed by drainage, blue water footprint, and water use efficiency. The 500 mm irrigation regime yielded the highest productivity and profitability but negatively impacted water use efficiency and environmental sustainability. Irrigation volumes above 500 mm worsened all water-related variables, while volumes of 400 mm reduced profitability but improved the sustainability. The Imobj index identified that irrigation between 300 mm and 400 mm provided the best trade-off across all evaluated variables. SIGNIFICANCEThis study highlights the value of integrating crop productivity, economic viability, and sustainability into irrigation management. The proposed framework, combined with AquaCrop, offers a holistic tool for optimizing irrigation strategies in agriculture. It emphasizes the need for balanced irrigation that not only maximizes yield but also enhances resource efficiency and environmental sustainability.

Development of an Optimized YOLO-PP-Based Cherry Tomato Detection System for Autonomous Precision Harvesting

An accurate and efficient detection method for harvesting is crucial for the development of automated harvesting robots in short-cycle, high-yield facility tomato cultivation environments. This study focuses on cherry tomatoes, which grow in clusters, and addresses the complexity and reduced detection speed associated with the current multi-step processes that combine target detection with segmentation and traditional image processing for clustered fruits. We propose YOLO-Picking Point (YOLO-PP), an improved cherry tomato picking point detection network designed to efficiently and accurately identify stem keypoints on embedded devices. YOLO-PP employs a C2FET module with an EfficientViT branch, utilizing parallel dual-path feature extraction to enhance detection performance in dense scenes. Additionally, we designed and implemented a Spatial Pyramid Squeeze Pooling (SPSP) module to extract fine features and capture multi-scale spatial information. Furthermore, a new loss function based on Inner-CIoU was developed specifically for keypoint tasks to further improve detection efficiency.The model was tested on a real greenhouse cherry tomato dataset, achieving an accuracy of 95.81%, a recall rate of 98.86%, and mean Average Precision (mAP) scores of 99.18% and 98.87% for mAP50 and mAP50-95, respectively. Compared to the DEKR, YOLO-Pose, and YOLOv8-Pose models, the mAP value of the YOLO-PP model improved by 16.94%, 10.83%, and 0.81%, respectively. The proposed algorithm has been implemented on NVIDIA Jetson edge computing devices, equipped with a human–computer interaction interface. The results demonstrate that the proposed Improved Picking Point Detection Network exhibits excellent performance and achieves real-time accurate detection of cherry tomato harvesting tasks in facility agriculture.

Quick In Vitro Screening of PGPMs for Salt Tolerance and Evaluation of Induced Tolerance to Saline Stress in Tomato Culture

Quick In Vitro Screening of PGPMs for Salt Tolerance and Evaluation of Induced Tolerance to Saline Stress in Tomato Culture

Effects of Different Nitrogenous Fertilizers and Potassium Doses on Yield, Yield Components, and Fruit Quality of Tomato Grown in Alkaline and Acidic Soils

Different nitrogen fertilizers and potassium applications have an important impact on the yield and yield components and fruit-quality parameters of tomatoes in both alkaline and acidic reaction soils. This study investigated the effects of different nitrogenous fertilizers and potassium doses on the yield, yield components, and fruit quality of tomatoes grown on alkaline and acidic soils. The experiment was carried out in the research greenhouse of the Agriculture Faculty, at Selcuk University. It was performed by using two different soil types, three nitrogen fertilizers [ammonium sulfate (AS), ammonium sulfate with inhibitor (AS+inh.), and calcium nitrate (CaNit)], and three different concentrations of potassium sulfate (0, 240, and 480 mg K2O kg-1). We conducted the study by using a randomized experimental plot design with four replications. According to the research results, the highest fruit yield in alkaline soil was 'inh. AS and 480 mg K2O kg-1', while the highest fruit yield in acid soils was obtained with 'calcium nitrate and 240 mg K2O kg-1'. Furthermore, different nitrogen sources and potassium doses significantly affected tomato yield components such as stem diameter, plant height, number of fruits per plant, fruit weight, fruit diameter, fruit hardness, fruit pH, and Brix values. According to the results of the completed soil analysis, the applications demonstrated the importance of accurate and balanced fertilization for high-yield and quality tomato production in different soils. In conclusion, this study highlights the importance of selecting appropriate nitrogen fertilizers and potassium doses to increase tomato yield and yield components in alkaline and acidic soils. It provides valuable insights for tomato farmers and researchers seeking to improve tomato cultivation techniques in different soil conditions.

Antagonist activity of bacteria isolated from “Solanum elaeagnifolium” green compost against Fusarium oxysporum f.sp.radicis-lycopersici

In the present study, 14 bacteria were isolated from “Solanum elaeagnifolium” green compost belonging to 12 species: Paenibacillus macerans, Bacillus circulans, Geobacillus thermoglucosidasius, Bacillus licheniformis, Serratia liquefaciens, Bacillus megaterium, Paenibacillus glucanolyticus, Serratia marescens, Pseudomonas aeruginosa, Sporosarcina pasteurii, Lysinibacillus sphaericus and Brevibacillus laterosporus. For Pseudomonas aeruginosa and Brevibacillus laterosporus, two different strains were obtained for each species. All the 14 isolates were tested for their antagonistic activity on Fusarium oxysporum f.sp.radicis-lycopersici the causal agent of tomato crown and root rot (FCRR). The assessment of the in vitro interactions between bacterial strains and the phytopathogenic fungi was performed by dual confrontation assays on PDA medium. All the 14 bacteria were antagonistic against the phytopathogen, with an inhibitory effect varying between 67,14% and 52,85%. Sporosarcina pasteurii and Brevibacillus laterosporus (S12-2) showed antifungal effect higher than the other bacteria, where they exhibit an significant reduction in fungal mycelium growth about 67,14%. The presences of different antagonist species of bacteria witnessed the maturity of the green compost and make it as a good organic amendment for tomato plant culture for stimulate their growth and to protect them from FORL. The inventory of the bacterial community of this compost was necessary to determine its quality for an appropriate application of them in future as a biological control agent against FORL in tomato cultivation.

Doses of fertirrigated potassium in tomato cultivation in a semi-hydroponic system

Doses of fertirrigated potassium in tomato cultivation in a semi-hydroponic system

Optimization of Concentration and Frequency of Liquid Organic Fertilizer Application on Cherry Tomato Plants (Lycopersicum esculentum var. Ruby) Growth and Yield

Cherry tomatoes (Lycopersicum esculentum var. Ruby) represent a significant segment of global vegetable production. In Indonesia, there is a notable demand for cherry tomatoes, as they serve dual purposes: they can be enjoyed fresh as a dessert or thirst quencher, and they can also be incorporated into a variety of culinary dishes and beverages. Their distinctive flavor and appearance make them popular for diverse culinary applications. The economic potential of cherry tomatoes is substantial, driven by strong demand in both local and international markets. However, cherry tomato cultivation's low productivity levels do not match this high consumer interest. An alternative approach to enhance productivity is using liquid organic fertilizer (POC), which is rich in various macro and micronutrients. This research aims to assess the impact of different concentrations and application frequencies of Hantu POC on the growth and yield of cherry tomato plants. A factorial randomized block design was employed, focusing on two primary variables: the concentration of Hantu POC (0 ml/l, 5 ml/l, 10 ml/l, and 15 ml/l) and the frequency of application (every 4 days, 7 days, and 10 days). Key parameters measured included plant height, leaf count, fruit quantity, and weight. Findings indicated that a concentration of 10 ml/l applied every 7 days yielded optimal results. Conversely, extending the application beyond 7 days resulted in suboptimal outcomes, with an average plant height of 49.44 cm and a total fruit weight of 311.94 grams. This study underscores the importance of identifying Hantu POC's appropriate concentration and application frequency to enhance cherry tomato production and promote sustainable agricultural practices.

Evaluate the integrative effects of irrigation water level, furrow irrigation methods, and nitrogen fertilizer rate on tomato yield in semi-arid southern Ethiopia.

This study investigates the integrative effects of irrigation water management allowable depletion (MAD), furrow irrigation methods (FIM), and nitrogen fertilizer application rate (NFAR) on tomato yield components. These yield components include marketable, unmarketable, and total yield. Additionally, the study examines crop agronomy components such as plant height, number of branches, and root depth in semi-arid Southern Ethiopia. The research employs a factorial and split-plot design. Three types of FIM are assigned as the main plot, while three levels of irrigation water (50%, 75%, and 100% MAD) and four levels of NFAR (0%, 50%, 100%, and 150% NFAR) serve as the subplots, with three replications. The study results reveal significant impacts of these factors. All p-values for tomato yield and agronomy-measured components are less than 0.05. FIM, irrigation water level, and NFAR interaction affect marketable, unmarketable, and total tomato yield. The results ranged from 2.3 tons ha⁻1-43.9 tons ha⁻1 for marketable yield, 0.8 tons ha⁻1-8 tons ha⁻1 for unmarketable yield, and 6.3 tons ha⁻1-45.2 tons ha⁻1 for total yield. The integration of 75% MAD with 100% NFAR under conventional furrow irrigation, and 100% MAD with 100% NFAR under alternative furrow irrigation, was most preferable. This approach resulted in no loss of nitrogen fertilizer and saved 25% of irrigation water without reducing tomato yield. However, the interaction of deficit nitrogen fertilizer rate application, with or without full application of MAD and conventional or other furrow irrigation methods, caused the total yield to decrease. CFIM and AFIM with 100% MAD and 100NFAR treatments yielded the highest profits, while the FFIM approach under 50%MAD and 0%NFAR conditions negatively impacted profitability. Therefore, by adopting the preferable practices, farmers can achieve higher productivity and sustainability in tomato cultivation. This approach addresses the challenges posed by water scarcity and nutrient limitations.

Hydroponic tomato cultivation using organic fertilizer from bonito fish-based soluble

Hydroponic tomato cultivation using organic fertilizer from bonito fish-based soluble

Soil classification and land suitability evaluation for tomato cultivation using analytic hierarchy process under different land uses.

Population growth has led to excessive land use, affecting soil suitability and sustainability. Detailed soil characterization and land evaluation for various land uses are essential steps toward achieving food security and sustaining the environment. This study classifies soils and assesses their suitability for tomato cultivation using the FAO Land Assessment Framework and Analytical Hierarchy Process (AHP) model. The land use requirements were matched with land suitability criteria, and the Analytical Hierarchy Process (AHP) was used to determine the relative importance of each evaluation criterion. Soil morphological and physicochemical properties were analyzed across different land uses. Based on USDA Soil Taxonomy, the soils under land use HK1 were identified as Typic Endoaqualfs, HK2 as Typic Albaqualfs and Inceptic Haplustalfs, while HK3 was categorized as Typic Haplustalfs and Typic Plinthaqualfs. The World Reference Base classification system identified these soils as Gleysols for soil unit HK1, Luvisols for pedon HK2P1, and Lixisols for the remaining soil units. This study demonstrates the effectiveness of the AHP method in logically determining the weights of multiple parameters in a multi-criterion approach. The results show that 89.73% of the area is highly suitable for tomato cultivation, while 10.27% is moderately suitable. The primary limitations of these soils are low fertility and poor drainage. The study suggests that management techniques including incorporation of organic matter, inorganic fertilizers and improved drainage conditions are needed for sustainable productivity.

Assessment of Alternaria Toxins and Pesticides in Organic and Conventional Tomato Products: Insights into Contamination Patterns and Food Safety Implications.

Alternaria toxins (ATs) are a group of toxins produced by Alternaria fungi that frequently contaminate tomatoes and tomato products. Recently, the European Food Safety Authority evaluated ATs for their genotoxic and carcinogenic properties. Alternaria infestation is often controlled using ad hoc treatment strategies (fungicides). In this study, two analytical methods were developed, validated and applied for the determination of five ATs and 195 pesticides in tomato products collected from the Italian market. Two distinct groups, organic (n = 20) and conventional (n = 20) Italian tomato sauces, were characterized in depth. Tenuazonic acid, alternariol and alternariol monomethyl ether were found up to 517, 27 and 7.1 µg/kg, respectively, while pesticides were detected between 0.0026 and 0.0421 mg/kg in conventional products, and, interestingly, up to 0.0130 mg/kg in organic products. No correlation emerged between the detected levels of ATs and pesticides and the type of tomato cultivation, but the probability of pesticide contamination in conventional products was eight times higher than in organics. Some considerations about exposure assessment and risk characterization for ATs were also proposed in the overall population and in more sensitive and/or exposed subgroups, underlining the need for new focused toxicological and monitoring studies to establish reliable reference values. Moreover, these data highlight that fungicide treatments may not protect tomatoes from ATs contamination, although it may remove fungi infestation. As organic product consumption is increasing, it is important to lay down dedicated regulations for maximum permitted levels to ensure the food safety of these products that are often perceived by consumers as a healthier and environmentally friendlier choice.

Soil application of dazomet combined with 1,3-dichloropropene against soilborne pests for tomato production

There is a growing problem in China, whereby tomato replant disease is being affected by Fusarium spp., Meloidogyne spp., and Phytophthora spp. To address these pests that live in the soil, we evaluated how well applying a dazomet (DZ) and 1,3-dichloropropene (1,3-D) combination directly to the soil works in three different tomato trials. The combined treatment of DZ + 1,3-D (25 + 10 g a.i. m⁻²), applied at a 50% reduction rate, effectively decreased Meloidogyne spp. populations in the soil by more than 94%. This resulted in low root galling indices of 2.67%, 4.17%, and 10.83% in the different trials. In addition, it significantly decreased the number of Fusarium spp. and Phytophthora spp. colonies by more than 82%, resulting in low root disease indices of 3.33%, 10.00%, and 10.42%, respectively. This also greatly increased tomato yield and profit for growers. The results obtained with DZ alone and methyl bromide (MB) at 50 g a.i. m⁻² were similar. However, these results were better than those obtained with 1,3-D at 20 g a.i. m⁻² alone in controlling soilborne fungi in trials I and III. Compared to the untreated controls and the soil solarization disinfestation treatments, all the chemical treatments performed significantly better. Due to its effectiveness in controlling pests and its economic advantages, soil fumigation with DZ + 1,3-D (25 + 10 g a.i. m⁻²) is recommended in pest management programs for tomato cultivation in China. This treatment is highly effective in managing pests that reside in the soil.

Hormonal efficiency and net return of BARI Tomato-4 enhanced under polytunnels during rainy summer season

An experiment was conducted at the department of Horticulture, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh to evaluate the benefit cost ratio of summer tomato variety BARI tomato 4. The experiment was laid out in a split plot design with 18 treatments and three replications by maintaining a spacing of 60 cm x 40 cm. It comprised of two cultivation method as main plot viz. Open cultivation (P0) and Cultivation under poly tunnel (P1) and nine levels of growth regulators as sub-plot viz. T0 (Control), T1 (GA3@30 ppm), T2 (GA3@60 ppm), T3 (NAA @30 ppm), T4 (NAA @60 ppm), T5 (MH @30 ppm), T6 (MH @60 ppm), T7 (Tomatotone @30 ppm) and T8 (Tomatotone @60 ppm). Application of growth regulators was influenced in all studied parameters over control. Majority of the parameters responded better with the increased concentration of growth regulators. Tomatotone @ 60 ppm gave the highest yield per hectare (5.38 and 20.82 t) under open and poly tunnel condition, respectively. In open and poly tunnel condition, tomatotone @ 60 ppm showed the highest profitability and benefit cost ratio 1.16: 3.19, respectively. Despite of poly tunnel was being costly to establish (41% of total input cost), but it gave 3-4 times higher economic return. Higher values in respect of economy were obtained from the plants cultivated under poly tunnel with tomatotone @60 ppm. Therefore, tomatotone @ 60 ppm can be used as potential treatment for summer tomato cultivation under open and poly tunnel conditions to get highest profitability.

Optimizing water‐nitrogen regulation for enhanced carbon absorption and reduced greenhouse gas emissions in greenhouse tomato cultivation

AbstractTo study the impact of different water‐nitrogen regulation modes on the carbon cycle of greenhouse tomatoes and determine optimal irrigation and nitrogen application levels to enhance carbon absorption and minimize greenhouse gas emissions. This study employed three irrigation levels (100%, 80%, and 60% of ET0) and three nitrogen application levels (240, 192, and 144 kg·ha−1), along with a control group (W1N1, i.e., 100% ET0‐240 kg·ha−1). Gas‐chromatography methods were used to monitor CH4 and soil CO2 emissions, while assessing dry matter, carbon content, and carbon fixation capacity of tomato organs throughout the growth period. Additionally, a system for evaluating the net ecosystem carbon budget of facility tomatoes was developed based on net primary productivity. Results indicated reduced CH4 and soil CO2 emissions with decreased irrigation and nitrogen application. Dry matter, carbon content, and carbon fixation of tomato organs initially increased with reduced nitrogen and irrigation but then declined. The W2N2 (80% ET0‐192 kg·ha−1) treatment showed maximal values for dry matter, carbon content, carbon fixation, net primary productivity (NPP), and gross primary productivity (GPP). Findings suggest a positive net ecosystem carbon budget under reduced water and nitrogen conditions, indicating carbon absorption. Specifically, the W2N2 treatment outperformed others in net carbon absorption, highlighting its potential as an effective mode for enhancing carbon sequestration in the region.

Substitution of Chemical Fertilization using PGRs Evident in Growth and Yield of Tomato

The excessive utilization of synthetic fertilizers and chemicals poses a significant threat to both environment and human well-being. A pot experiment was done between December 2022 and April 2023 using a factorial randomized complete block design, which involved combining fertilizers and plant growth regulators (PGRs). The objective was to decrease the utilization of artificial fertilizers through the application of PGRs. The experiment involved applying fertilizers at 80, 90, 100 and 110% of the recommended doses. The recommended doses consist of 12 grams (g) of urea, 10 g of TSP, 5 g of MoP, 3 g of gypsum, 0.5 g of zinc sulphate, and 0.5 g of boric acid per plant. Furthermore, PGRs including gibberellic acid (GA3), naphthalene acetic acid (NAA), 4-chlorophenoxy acetic acid (4-CPA), and salicylic acid (SA) were applied at a concentration of 50 ppm. The results showed that there were no significant differences in growth and yield-contributing features when the fertilizer dose was increased from 80% to 110% of the recommended amount. Nonetheless, there were significant differences compared to the control group. However, PGRs showed significant variability in the morphological and reproductive responses of tomatoes under the conditions being researched. The GA3 treatment resulted in significantly greater plant height, base diameter, number of branches and leaves per plant, canopy spread, and internode length. Moreover, GA3 at 50 ppm produced the highest number of flowers and fruits/plant, with a single fruit weighing 67.83 g and a total fruit production of 6.61 kg/plant of tomato. Among the other PGRs, salicylic acid showed statistical equivalence to GA3 treatment. Nonetheless, there was a notable decrease in both vegetative and reproductive features, including yield, when NAA and 4-CPA were used. The interaction between fertilizers and PGRs showed that combining GA3 and SA with any of the tested fertilizer rates resulted in statistically distinct and improved vegetative and reproductive responses. However, the combination of fertilizer with NAA and 4-CPA produced highly unsatisfactory outcomes. Therefore, GA3 at 50 ppm and SA at 50 ppm can effectively be employed as substitute of synthetic chemical fertilizers in tomato cultivation. J. of Sci. and Tech. Res. 6(1): 53-64, 2024

Rapid on-site detection of crop RNA viruses using CRISPR/Cas13a.

Plant viruses are destructive pathogens for various crop species. Rapid, sensitive, and specific detection is crucial for the effective containment of emerging and resistance-breaking viruses. CRISPR/Cas has been established as a new tool for plant virus identification. However, its application for direct detection of viruses in the field is still limited. In this study, we present a CRISPR/Cas13a-based method for rapid detection of different viruses directly from RNA of several crop species, including tomato, cucumber and rapeseed. This method was used to identify the emerging tomato brown rugose fruit virus (ToBRFV), a prominent pathogen in tomato cultivation, and distinguish it from closely related viruses in infected tomato plants. ToBRFV could be identified in a 100-fold dilution and early during infection, prior to the onset of viral symptoms. Finally, we developed a user-friendly, extraction-free, 15-minute protocol for on-site virus detection using a portable fluorescent viewer and a mobile phone camera. This protocol was successfully applied for ToBRFV identification in several commercial greenhouses. These results demonstrate that CRISPR/Cas13a is a robust technology for on-site detection of multiple viruses in different crop plants. This method could be swiftly adapted to identify newly emerging pests, which threaten global food security.

Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images.

Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. Tomato (Solanum lycopersicum), a vegetable crop, frequently suffers from pest damage and drought, leading to reduced yields and financial losses to farmers. Accurate detection and classification of tomato pests are the primary steps of integrated pest management practices, which are crucial for sustainable agriculture. This paper explores using Convolutional Neural Networks (CNNs) to classify tomato pest images automatically. Specifically, we investigate the impact of various optimizers on classification performance, including AdaDelta, AdaGrad, Adam, RMSprop, Stochastic Gradient Descent (SGD), and Nadam. A diverse dataset comprising 4263 images of eight common tomato pests was used to train and evaluate a customized CNN model. Extensive experiments were conducted to compare the performance of different optimizers in terms of classification accuracy, convergence speed, and robustness. RMSprop achieved the highest validation accuracy of 89.09%, a precision of 88%, recall of 85%, and F1 score of 86% among the optimizers, outperforming other optimizer-based CNN architectures. Additionally, conventional machine learning models such as logistic regression, random forest, naive Bayes classifier, support vector machine, decision tree classifier, and K-nearest neighbors (KNN) were applied to the tomato pest dataset. The best optimizer-based CNN architecture results were compared with these machine learning models. Furthermore, we evaluated the cross-validation results of various optimizers for tomato pest classification. The cross-validation results demonstrate that the Nadam optimizer with CNN outperformed the other optimizer-based approaches and achieved a mean accuracy of 79.12% and F1 score of 78.92%, which is 14.48% higher than the RMSprop optimizer-based approach. The state-of-the-art deep learning models such as LeNet, AlexNet, Xception, Inception, ResNet, and MobileNet were compared with the CNN-optimized approaches and validated the significance of our RMSprop and Nadam-optimized CNN approaches. Our findings provide insights into the effectiveness of each optimizer for tomato pest classification tasks, offering valuable guidance for practitioners and researchers in agricultural image analysis. This research contributes to advancing automated pest detection systems, ultimately aiding in early pest identification and proactive pest management strategies in tomato cultivation.

Technology Change in Hybrid Tomato Production: A Field Based Study

The study was conducted for analyzing impact of technology change in hybrid tomato production, comparing with inputs, or improving productivity. While measuring the sources of output growth, the contribution of total productivity is always estimated as residual after accounting for the growth of the inputs. The results revealed that the contribution of technology to the differential output was higher in the case of Arka Vishall (14.52%) compared to Arka Vikas (11.71%) and Arka Vardan (-4.58%). This output differential was decomposed into changes in technology and changes in input levels. First, the contribution of technology (Hybrid) in total change in output was estimated to be 3.82 %. Second, the concerned input level effects, the positive contributions of labour (7.18 %), farmyard manure (0.039%), irrigation (0.78%), and other costs (2.24%) to total change in output were observed. The negative contributions were found in the case of seedlings (-0.78%), fertilizers (-0.29%), and plant protection chemicals (-1.5%). The total input level effect on output change was estimated to be 8.10%. Third, the estimated change in output (11.92%) was almost equal to the actual change of 11.71%. Therefore, there is a need for appropriate policy interventions and efforts by the concerned to address these constraints in adopting new tomato hybrids and to make tomato cultivation a viable and profitable enterprise.

Water productivity and economic feasibility of drip irrigation system investment in tomato cultivation: Case of northeastern Tunisia

AbstractTunisia is characterized by water scarcity, growing water demand and considerable waste of this resource especially in the agricultural sector. To cope with this situation and enhance water productivity, appropriate utilization of advanced irrigation methods such as drip irrigation is highly needed. Hence, this research aims to evaluate the profitability of drip irrigation systems compared with surface irrigation systems at the perimeter of Echraf, which is located in the northeastern of Tunisia. Primary data were collected from 25 adopters of the Drip Irrigation System and 13 non‐adopters. The results of the partial budget analysis revealed that the average total cost for adopters was higher than that for non‐adopters. However, the net margin was higher for adopters than for non‐adopters. This is due to the greater increase in gross revenue for adopters than for non‐adopters. Additionally, drip irrigation resulted in more efficient water use and water values than did the surface irrigation system. Economic profitability analysis via the benefit cost ratio and net present value tools revealed that the drip irrigation system is profitable. The benefit cost ratio is equal to 1.65, and the net present value is approximately 2938 Tunisian National Dinar. Finally, the sensitivity analysis reveals the extent to which profitability is sensitive to the scenarios of subsidy levels.

Improving Irrigation Water Use Efficiency and Maximizing Vegetable Yields with Drip Irrigation and Poly-Mulching: A Climate-Smart Approach

Water management is a significant aspect of sustainable vegetable farming, especially in water-scarce regions. This, in addition to weed infestations, limits vegetable yields, which negatively affect food security in developing regions, particularly East Africa, where livelihoods chiefly depend on rain-fed agriculture. Vegetable farming, especially tomato cultivation, requires more water. By promoting mulching, a soil water conservation tool, we can control surface evaporation (E), which, together with irrigation, enhances effective water use and vegetable yields. The experiments for this study were conducted at the Tokyo University of Agriculture, Japan, to evaluate the influences of different irrigation conditions and poly-mulching on weed control, tomato yields, and water use efficiency. The study was conducted from May to September 2018 on a 30 m2 plot in an open-ended greenhouse using drip irrigation for tomato cultivation. Three predetermined irrigation conditions of 4, 3, and 2 mm/day were applied on black poly-mulched and bare ridges. Data on soil conditions—soil temperature, as well as meteorological variables, including solar radiation and temperature—were measured using thermocouple sensors and micro-hobo weather stations, respectively, during the tomato cultivation, while yield components—growth, yield, water productivity, and sugar content—were determined after harvest. The results of a two-way ANOVA show that irrigation conditions with poly-mulching reduced the weed biomass significantly, and improved yields and water use efficiency compared to the irrigation conditions on bare ridges. The application of 4, 3, and 2 mm/day irrigation with poly-mulching significantly reduced the weed biomass by 5% compared to the same irrigation conditions on bare ridges. Similarly, 4 and 3 mm/day irrigation conditions with poly-mulching significantly increased the tomato yield by 5% compared to 2 mm/day on bare ridges. The bigger roots were concentrated and widely distributed at the shallow soil depth (0–20 cm) of the ridges with high irrigation amounts, while the small and thin roots were in deeper soil layers (30–45 cm). This study provides scientific knowledge on the application of predetermined irrigation conditions that can be (i) integrated into irrigation scheduling and (ii) adopted for regions facing water scarcity and limited or no in situ meteorological data, to improve water use efficiency for vegetable cultivation.