Novel Approach to Use Coconut Fibre Mats Embedded with Trichoderma harzianum as Precision Bio-control Agent

Novel Approach to Use Coconut Fibre Mats Embedded with Trichoderma harzianum as Precision Bio-control Agent | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Novel Approach to Use Coconut Fibre Mats Embedded with Trichoderma harzianum as Precision Bio-control Agent Jijo Philip Sam J, Samson Lijoseraj Charles, Magdalene Hannah Edward, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7487821/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The growing demand for sustainable agriculture has intensified interest in biological alternatives to synthetic inputs. Trichoderma harzianum , a plant growth-promoting fungus, offers both biocontrol and stimulation of plant development, while organic mulching materials such as coconut fibre mats improve soil structure, conserve moisture, regulate temperature, and enhance microbial activity. This study assessed the combined effect of T. harzianum application with coconut fibre mulching on tomato crop growth and yield through a field trial with three treatments: T1 –foliar spraying of T. harzianum , T2 – root-zone application using T. harzianum -inoculated coconut fibre mats, and T3 – untreated control, arranged in a randomised complete block design with three replications. Plant height, fruit yield, and disease incidence were measured, showing that T2 significantly enhanced growth (95.0 ± 3.58 cm) compared to T1 (69.0 ± 8.47 cm) and T3 (41.0 ± 11.33 cm), while fruit yield in T2 reached 470 kg ha⁻¹, representing a 276% increase over control (125 kg ha⁻¹) and higher than T1 (224.7 kg ha⁻¹, a 79.6% increase). Disease incidence was also lowest in T2 (10%) compared with T1 (16%) and T3 (30%), confirming a synergistic effect between root-zone T. harzianum colonisation and soil health benefits of mulching. Although restricted to a single growing season, predictive models such as the crop water production function (CWPF) and water footprint analysis indicated that mulching increased reliance on rainwater, reduced groundwater withdrawal, and improved efficiency under variable temperature and rainfall. Overall, this integrated microbial–mulch approach demonstrates a sustainable, eco-friendly strategy to boost tomato productivity and conserve natural resources. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction In the current agricultural landscape, resource inefficiency has become increasingly intolerable due to mounting economic pressures and inflation. The extensive use of inputs for crop cultivation means that any unforeseen damage can result in substantial financial losses. Moreover, climate change has led to erratic weather patterns, such as extreme temperatures and heavy rainfall, causing massive crop failures and increased resource wastage [ 1 ]. These unfavourable climatic conditions can reduce the efficacy of biocontrol agents [ 2 ], while favourable conditions enhance their performance. Organic farming offers a sustainable alternative to conventional agricultural practices by emphasising ecological balance [ 3 ], biodiversity conservation [ 4 ], and the use of natural inputs to manage pests and maintain soil fertility. It plays a critical role in promoting sustainability through reduced water consumption, minimised agrochemical usage, and enhanced biodiversity [ 5 ].However, the slower pace and lower yields of organic farming often limit its widespread adoption. To address these limitations, precision farming is increasingly being adopted. This modern approach ensures efficient use of agricultural resources, leading to better crop yields, reduced input wastage, and increased profitability. By applying inputs in precise quantities, it maximises resource efficiency while minimising environmental impact [ 6 ]. When combined with appropriate carrier materials and advanced monitoring techniques, precision farming can significantly enhance the delivery and efficacy of biocontrol agents. Integrating precision farming with organic practices optimises the use of natural inputs without over-application, making agriculture more efficient and sustainable [ 7 , 8 ]. The overreliance on chemical pesticides to manage plant pathogens, insect pests, weeds, and nematodes has exceeded safe thresholds, severely degrading soil health and harming non-target organisms [ 9 ]. Beneficial soil microbes and predator insects that are essential components of agroecosystem biodiversity are also adversely affected. Moreover, the human health implications are profound: pesticide exposure has been linked to adverse effects in farmers [ 10 ] while residues have been detected in breast milk, potentially harming infants [ 11 , 12 ]. Persistent pesticide residues can remain in the soil for decades, sometimes even centuries [ 13 ], contaminating crops [ 14 ] and contributing to environmental pollution, as only 0.1% of applied pesticides reach their target organisms [ 15 ]. In response, governments have introduced strict regulations to curtail pesticide use, creating a demand for sustainable, eco-friendly alternatives. Plant diseases pose a serious threat to global food security by reducing both crop yield and quality. These diseases are caused by various pathogens, including fungi, bacteria, and viruses, and spread through contaminated planting material, air, soil, and insect vectors [ 16 ]. The severity and spread of disease depend on environmental conditions, host plant susceptibility, and pathogen virulence. Annually, phytopathogens are responsible for approximately 16% of crop yield losses, with fungi alone accounting for nearly 85% of plant diseases. According to the Food and Agriculture Organisation (FAO), pests and pathogens contribute to 20–40% of global crop losses each year. Many of these pathogens can remain viable in the soil for extended periods, posing long-term threats to agriculture. Precision farming ensures agricultural resources are utilized efficiently for better yield with minimal wastage and maximum profitability. Coconut fibre is an eco-friendly material used as a substrate for Trichoderma harzianum in biocontrol applications. It supports colonization of beneficial microorganisms while preventing weed growth through its natural mulching properties [ 17 ]. It offers a biodegradable and eco-friendly medium for supporting the colonization and proliferation of beneficial microorganisms like Trichoderma harzianum . It provides additional agronomic benefits, including suppression of weed growth through natural mulching, enhanced water retention, and reduced UV exposure on plant roots [ 17 ]. Its high carbon-to-nitrogen ratio ensures slow decomposition, making it suitable for long-term agricultural use. Moreover, coconut fibre mats can reduce soil temperatures by up to 4°C, offering protection from heat stress and promoting root health. Biocontrol agents, including entomopathogenic fungi, bacteria, viruses, and predatory insects, present an environmentally sustainable alternative to chemical pesticides [ 18 ]. These agents act through various mechanisms, such as competition, antibiosis, and parasitism, to suppress pathogen populations [ 19 ]. Their application enhances biodiversity, preserves soil health, and minimises chemical dependencies. The choice of carrier material plays a crucial role in the success of biocontrol agents by enhancing their viability, field efficacy, and storage stability [ 20 ]. Ideal carriers protect agents from environmental stressors, aid in uniform distribution, and ensure prolonged shelf life. Common carriers include talc, kaolin clay, oil-based, and aqueous formulations [ 21 ]. Trichoderma harzianum, a soil-dwelling fungus from the Hypocreaceae family, is among the most effective biocontrol agents due to its multifaceted mechanisms, including mycoparasitism, antibiosis, and the induction of systemic resistance in host plants [ 22 ]. It not only suppresses a wide range of phytopathogens but also contributes to soil detoxification by degrading persistent pesticides such as DDT, dieldrin, endosulfan, pentachloronitrobenzene, and pentachlorophenol, thereby enhancing soil fertility and plant growth [ 23 ]. Tomato ( Lycopersicon esculentum ) is a crop of significant economic importance and serves as an excellent model for studying plant-pathogen interactions due to its high susceptibility to various diseases [ 24 ]. Closely related to other Solanaceae members such as potatoes ( Solanum tuberosum ), brinjal ( Solanum melongena ), and tobacco ( Nicotiana tabacum ), tomatoes are widely consumed and heavily utilised in food processing industries [ 25 ]. Their vulnerability to bacterial, fungal, and viral infections makes them ideal candidates for evaluating biocontrol strategies. The present study emphasises the application of T. harzianum in precision farming systems to reduce input costs and enhance crop productivity. By incorporating T. harzianum into coconut fibre mats, a sustained and controlled release of spores into the rhizosphere is achieved. This eliminates the need for repeated applications, as the fungus proliferates within the coconut substrate, providing long-term protection against soilborne pathogens [ 26 ]. This integrated approach, merging biocontrol with precision agriculture and sustainable substrates like coconut fibre, represents a significant step toward reducing reliance on chemical pesticides, lowering production costs, and enhancing ecological resilience in crop production systems [ 27 ]. While the current study presents results from a single growing season, addressing the limitations of single-season data is critical for broad adoption and robust agronomic recommendations. Multi-season analysis using predictive models, such as the Crop Water Production Function (CWPF) or similar well-validated temperature and rainfall response models for tomato, allows simulation of yield and water use under varied seasonal conditions [ 24 ]. These models incorporate field-collected temperature, evapotranspiration (ET₀), and rainfall data to project crop performance, enabling farmers and researchers to anticipate outcomes over multiple seasons and adjust management practices. In parallel, water footprint analysis provides a comprehensive evaluation of water use in crop production. This framework partitions total water consumption into three components: blue water footprint, which is the volume of irrigation water withdrawn from surface or groundwater representing direct freshwater abstraction; green water footprint, the volume of rainwater retained in the soil and used by the crop via evapotranspiration; and grey water footprint, the volume of freshwater required to dilute pollutants, primarily nitrogen leachates to meet water quality standards, reflecting potential environmental contamination risks [ 28 ]. Applying this approach to your system, the analysis can compare blue water footprints under conventional and coconut coir mulch regimes, explicitly quantifying how mulch-enhanced soil moisture conservation increases the relative contribution of green water. Such partitioning is essential for evaluating groundwater conservation strategies, particularly in semi-arid regions where groundwater depletion is a growing concern. By calculating and contrasting seasonal blue, green, and grey water footprints per unit yield across multiple seasonal scenarios, the study extends its practical relevance. The results enable a clear demonstration of how improved soil water retention through coconut fibre mulching reduces irrigation demands (blue water), enhances rainwater utilisation (green water), and minimises nutrient leaching (grey water), collectively fostering sustainable water management and crop resilience. The aim of this study was to evaluate the efficacy of coconut fibre mats embedded with T. harzianum as a precision biocontrol agent for tomato cultivation, with special emphasis on improving growth, yield, disease resistance, and water use efficiency. It further sought to develop predictive models to assess multi-seasonal yield potentials and quantify water footprint components under varying seasonal conditions, thereby providing an integrated framework for sustainable and resource-efficient tomato production. 2. Methodology 2.1 Nursery Preparation A nursery site was established at the MCC farm (12.9155504 N, 80.1258663 E), selected for optimal sunlight and accessible irrigation. The area was fenced to protect seedlings from poultry and stray animals. The nursery soil was ploughed and sun-dried to reduce soil-borne pathogens. Well-decomposed, dried vermicompost was thoroughly incorporated into the soil before seed sowing. Certified tomato ( Solanum lycopersicum L .) seeds (variety: PKM 1, brand: Nisco) with 99% genetic purity, 98% physical purity and 70% germination rate were procured from Nisco Agritech Pvt. Ltd., Karnataka, India. Since the seeds are commercially available, no specific permits or authorisations were required for their use in this study. The seeds were evenly broadcast, followed by light irrigation to aid germination. One week prior to transplantation, watering was minimised to harden seedlings, enhancing field establishment potential [ 29 ]. 2.2 Land Preparation A 25 × 5 m² field was cleared of debris with the borders secured using recycled sacks. Primary tillage involved a tractor-mounted rotovator for soil loosening and compost incorporation, followed by harrowing for levelling and improved water movement. Ridges and furrows were created for drainage and cultural operations. The plot was divided into three equal sections (5 × 5 m²). Tomato seedlings (aged 25 days) were transplanted on ridges spaced 100 cm apart, ensuring robust root systems by planting to a depth that leaves only the top leaves above ground. Pre-transplant irrigation was withheld one week before uprooting, followed by immediate post-plant irrigation. Periodic manual weeding and scheduled drip irrigation continued through the growing season [ 30 ]. 2.3 Application of Trichoderma harzianum A commercial formulation of T. harzianum (T22 strain, 2 × 10⁹ spores/cm³) was diluted to 10 mL/L water as per [ 31 ]. Application methods were as follows: T1: Foliar spray applied with a hand-held pressure sprayer T2: Coconut coir mulch soaked in T. harzianum suspension for one hour and placed at the plant bases T3: Untreated control Mud bunds separated the treatment plots. Applications were repeated every 15 days to maintain fungal populations [ 32 ]. 2.4 Soil and Microbial Analysis Rhizosphere soil samples were collected pre- and post-treatment to assess microbial population dynamics and nutrient status. Soil loosely adherent to roots was gently shaken off and pooled per treatment plot. Composite 10 g samples were suspended in 90 mL sterile distilled water and serially diluted (10⁻¹ to 10⁻³) for plating on Potato Dextrose Agar (PDA). Plates incubated at 28 ± of conidiophores 2°C for 5–7 days were used to count colony-forming units (CFUs). T. harzianum colonies were further identified using lactophenol cotton blue staining for microscopic observation and phialides [ 33 ]. 2.5 Data Collection 2.5.1 Plant Growth Parameters Ten randomly selected plants per treatment were monitored weekly for Plant height (cm), Number of leaves, Number of flowers, Average fruit weight (g), Fruit yield per plant (kg). Growth rate was calculated as [ 34 ] : Growth Rate (cm/day) = Final Height − Initial Height​ / Number of days 2.5.2 Harvesting Tomato fruits ripened approximately three months post-transplantation. Harvesting occurred every three days, collecting partially ripe fruits to promote uniform ripening via ethylene accumulation. Damaged or diseased fruits were discarded. Yield was measured as total fruit weight per plot and extrapolated to kg/ha [ 35 ]. 2.5.3 Disease Observation Plants were visually inspected weekly for symptom development of common fungal diseases, including early blight and Fusarium wilt. Disease incidence and severity were recorded, and biocontrol efficacy of T. harzianum, particularly in coir-mulched plots, was evaluated relative to untreated controls [ 22 ]. 2.5.4 Nutrient Use Efficiency (NUE) Total nitrogen input from organic compost and baseline soil was quantified, alongside post-harvest soil analysis for available nitrogen (N), phosphorus (P), and potassium (K) by Kjeldahl digestion, Olsen’s method, and flame photometry, respectively. NUE was calculated as [ 36 ]: ​ \(\:\varvec{N}\varvec{U}\varvec{E}\:(\varvec{k}\varvec{g}\:\varvec{y}\varvec{i}\varvec{e}\varvec{l}\varvec{d}\:/\:\varvec{k}\varvec{g}\:\varvec{N})=\varvec{T}\varvec{o}\varvec{t}\varvec{a}\varvec{l}\:\varvec{F}\varvec{r}\varvec{u}\varvec{i}\varvec{t}\:\varvec{Y}\varvec{i}\varvec{e}\varvec{l}\varvec{d}\:\left(\varvec{k}\varvec{g}\right)/\:\varvec{T}\varvec{o}\varvec{t}\varvec{a}\varvec{l}\:\varvec{N}\:\varvec{s}\varvec{u}\varvec{p}\varvec{p}\varvec{l}\varvec{i}\varvec{e}\varvec{d}\:\left(\varvec{k}\varvec{g}\right)\:\) 2.5.5 Water Footprint Analysis Water footprint encapsulates crop water use partitioned into: blue, green, and grey components. Irrigation volumes were recorded during the experiment. Soil water retention and evaporation capacity were estimated via a 5-hour laboratory evaporation study at 36°C, measuring water lost from saturated soils with and without coconut coir mulch. Water holding capacity was calculated by weighing saturated and oven-dried samples. Formulas used: Water Productivity (WP) : WP = Total Fruit Yield (kg)​ / Total Water Used (L) [ 37 ] Evaporative Water Loss (EWL%) : EWL = Water Applied − Water Retained​ / Water Applied ×100 Water Saved per Day (L/100 m²) : Water Saved=(Water Use T3 − Water Use Treatment)×Area Blue, green, and grey water footprints were estimated per Hoekstra’s framework to assess irrigation water (blue), effective rainfall use (green), and water needed for nutrient pollutant dilution (grey). Seasonal rainfall data matched irrigation records to quantify water savings and groundwater conservation potential [ 28 ]. 2.5.6 Land Use Efficiency and Agronomic Indicators Land use efficiency (LUE) was computed as: LUE = Land Area (m²) / Total Yield (kg)​×100 Key agronomic indicators—yield, irrigation frequency, evaporative loss, and nutrient content—were monitored. Economic viability was assessed by comparing input costs (including coconut coir mulch) relative to yield increase and resource savings [ 38 ]. 2.5.7 Prediction Methodology for Multi-Season Yield To project yields beyond the single study season, temperature-driven models were applied: Thermal indices, including Growing Degree Days (GDD), Heat Degree Days (HDD), and Cold Degree Days (CDD), were computed daily: GDD d ​ = max (min (T avg ​ , T u ​) − T b ​, 0) where, T b =10°C, T u =30°C, T h = 32°C HDD d ​=max (T max ​ − T h ​, 0) where T max ​ = daily maximum temperature (°C), T h = 32°C CDD d ​= max(T c ​−T min​ , 0) where, T min ​ = daily minimum temperature (°C), T c = 12°C The crop yield (Y) for each treatment was modelled as: Y = β 0 ​+ β 1 ​GDD − β 2 ​HDD − β 3 ​CDD + ϵ Parameters βi\beta_iβi​ were calibrated using observed yields and temperature data for treatments T1, T2, and T3. Future season yields were predicted by inputting temperature data of those seasons, thereby simulating yield responses incorporating heat stress and growth conditions. Limitations include exclusion of water availability, radiation, pest outbreaks, and management effects; thus, projections serve as temperature-driven potential estimates [ 39 ]. 2.5.8 Statistical Analysis Data were analysed using Microsoft Excel to calculate means, standard deviations, and to perform ANOVA with Tukey’s multiple comparison test to evaluate treatment effects on plant growth, yield, and water use efficiency [ 40 ]. 3. RESULTS 3.1 Microbial Colonisation of Trichoderma harzianum Microbial analysis of rhizosphere soil samples before and after treatment confirmed the successful colonisation of Trichoderma harzianum . Prior to treatment, soil samples from all plots subjected to serial dilution (10⁻¹, 10⁻², 10⁻³) showed no detectable fungal growth on Potato Dextrose Agar (PDA), verifying the absence of T. harzianum in the native soil. This established a clear baseline for evaluating treatment effects. Post-treatment soil samples from foliar spray (T1) and coconut fibre mulch (T2) treatments demonstrated significant fungal growth. Identification of colonies was verified both morphologically and microscopically, using lactophenol cotton blue staining, which revealed hyaline, septate hyphae, with typical phialides and conidial structures of T. harzianum . Notably, in T2, fungal growth was present not only in the rhizosphere soil but also on the coconut fibre mulch surface, indicating both localised and lateral colonisation. No fungal colonies were detected in the control (T3), confirming the specificity of the introduced inoculum and validating the effectiveness of both application methods. 3.2 Tomato Growth Response to Trichoderma harzianum Applications (T1 and T2) vs Control (T3) Tomato plants exhibited significant growth differences across treatments. At transplantation (Day 0), plant height and leaf count were comparable, with T1 averaging 4.5 cm height and 7.3 leaves, T2 at 4.0 cm and 3.9 leaves, and T3 at 4.4 cm and 5.3 leaves. By Day 14, T1 reached 43.6 cm with 13.8 leaves, while T2 grew to 64.6 cm with 14.7 leaves. The control plants lagged at 29.7 cm and 5.3 leaves. Growth rates were calculated as 2.79 cm/day for T1, 4.34 cm/day for T2, and 1.81 cm/day for T3. On Day 28, T2 plants averaged 95.0 cm in height with 23.6 leaves and 26.1 flowers per plant, outperforming T1, which showed 69.0 cm height, 33.9 leaves, and 21.1 flowers. T3 plants remained underdeveloped with 41.0 cm height, 13.9 leaves, and 6.8 flowers. The standard deviations in T2 were lower than those in T1, indicating greater growth uniformity across the population. Table 1 Physiological parameters of the tomato plants treated with Foliar Application of Trichoderma harzianum (T1, T2, and T3) S. No. Plant Parameters T1 T2 T3 Mean SD Mean SD Mean SD 0th day After Transplantation Height of Plant (cm) 4.5 1.08 4 0.73 4.4 0.97 Total Number of Leaves 7.3 1.34 3.9 0.73 5.3 1.34 14th day After Transplantation Height of Plant (cm) 43.6 5.68 64.6 4.32 29.7 6.22 Total Number of Leaves 13.8 5.19 4.7 1.26 5.3 1.72 Growth Rate (cm/day) 2.79 0.35 4.34 0.34 1.81 0.48 28th day After Transplantation Height of Plant (cm) 69.02 8.47 95 3.58 41 11.33 Total Number of Leaves 33.87 13.07 23.6 0.81 13.9 5.79 Total Number of Flowers 21.05 10.67 26.1 5.16 6.8 7.89 Growth Rate (cm/day) 1.82 0.51 2.19 0.26 0.8 0.7 3.3 Yield Performance Across Treatments Yield data collected over three harvests confirmed the superior performance of treated plants. In T2 plots, yields of 6.0 kg, 8.33 kg, and 32.67 kg per 10 plants were recorded for Harvests 1, 2, and 3 respectively, averaging 15.67 kg per 10 plants or 470 kg/ha. T1 yielded 1.47 kg, 6.33 kg, and 14.67 kg over the three harvests, averaging 7.49 kg per 10 plants or 224.7 kg/ha. The T3 control showed the lowest productivity, with 0.17 kg, 4.0 kg, and 8.33 kg per harvest, averaging 4.17 kg per 10 plants or 125 kg/ha. These data reveal a strong positive correlation between microbial treatment method and cumulative yield, with T2 delivering the most substantial benefits. Table 2 Total yield of T1, T2 treated and T3 untreated tomato plant Treatment Harvest 1 (mean of 10 plants) Harvest 2 (mean of 10 plants) Harvest 3 (mean of 10 plants) Mean SD Total (kg/ha) T1 1.47 6.33 14.67 7.49 6.68 224.7 T2 6 8.33 32.67 15.67 14.77 470 T3 0.17 4 8.33 4.17 4.09 125 3.4 Disease Incidence Disease incidence was significantly influenced by the treatments. In the untreated control (T3), Septoria leaf spot symptoms were observed in 30% of the plants. T1 reduced this incidence to 16%, while T2 showed the lowest rate at 10%. When combined with anthracnose observations, overall disease incidence was 29.3% in T3, 22.8% in T1, and 14.6% in T2. Fruit rot caused by anthracnose was particularly evident in T3, reducing marketable yield. Visual and symptomatic assessments supported these findings, and statistical analysis confirmed significant differences among the treatments (p < 0.05), with T2 exhibiting the most effective disease suppression. 3.5 Predicted Seasonal Yield Response to Temperature Variability To evaluate potential yields across different planting windows, we calculated cumulative Growing Degree Days (GDD) and Heat Degree Days (HDD) using Tamil Nadu’s monthly temperature data and applied these indices to our calibrated yield model. The analysis covered four key three-month periods and the full year, with yields scaled to the July–August reference season (470 kg/ha for T2). Results (Table X) demonstrate that cooler periods like Jan–Mar have limited heat accumulation, resulting in the lowest predicted yields (e.g., 19.6 kg/ha for T2). The pre-monsoon (Mar–May), summer (Jun–Aug), and post-monsoon (Sep–Nov) seasons offer increased thermal units with minimal heat stress, producing moderately higher projected yields ranging from 21.5 to 22.4 kg/ha for T2. When aggregated annually, predicted yields approach 44 kg/ha under optimal management. These findings emphasize the critical role of aligning transplanting schedules with favourable temperature windows that maximize beneficial warmth while minimizing heat stress. Optimizing this thermal balance, alongside strategic use of biocontrol-enhanced mulching, can substantially improve tomato productivity across seasons in Tamil Nadu. Table 3 Predicted Seasonal Yield Response to Temperature Variability Season Months Total GDD (°C·days) Total HDD (°C·days) Predicted Yield T2 (kg/ha) Predicted Yield T1 (kg/ha) Predicted Yield T3 (kg/ha) Relative Yield Scale Winter-Early Jan - Mar 51.8 0.0 19.6 9.4 5.2 0.042 Pre-Monsoon Mar - May 59.0 0.8 21.5 10.3 5.7 0.046 Summer Jun - Aug 60.0 0.3 22.4 10.7 6.0 0.048 Post-Monsoon Sep - Nov 58.4 0.0 22.1 10.6 5.9 0.047 Year-Round Jan - Dec 118.8 1.1 43.9 20.9 11.7 0.094 Table 3 predicted tomato yields for different seasonal planting windows based on cumulative thermal metrics derived from monthly average temperatures in Tamil Nadu. The table summarizes the total Growing Degree Days (GDD) using a base temperature of 10°C and upper cap of 30°C, and total Heat Degree Days (HDD) applying a threshold of 32°C to quantify heat stress during the respective seasons. The yield predictions for each treatment (T2: coconut fibre mat + Trichoderma harzianum; T1: foliar T. harzianum; T3: untreated control) are scaled relative to a reference yield observed during the July–August season (T2 = 470 kg/ha, T1 = 224.7 kg/ha, T3 = 125 kg/ha). A penalty factor of 3 was applied to HDD to account for heat-induced yield reductions. The relative yield scale represents the ratio of the season’s combined thermal metric.(GDD − 3×HDD) to that of the reference season (1240 degree-days). Results indicate variable yield potentials across seasonal production windows, with the highest cumulative potential in the year-round scenario. This modelling approach isolates temperature effects, assuming consistent management, and excludes other limiting factors such as water deficits, pest pressures, and nutrient constraints. 3.6 Water Footprint and Evaporation Losses in Tomato Cultivation with and without Coconut Coir Mulch The water footprint analysis was conducted using monthly temperature and rainfall data from June 2024 to May 2025, obtained from regional meteorological records for Tamil Nadu, India [ 41 ]. These data facilitated the estimation of reference evapotranspiration (ET₀) and the quantification of soil water loss with and without coconut coir mulch application. Results showed that soil without mulch experienced an annual water loss of approximately 1,375 litres per square meter, while the presence of coir mats significantly reduced this loss to 392 litres per square meter, yielding a substantial net saving of 983 litres per square meter annually. When extrapolated to the hectare scale, this represents a water conservation of about 9,830 cubic meters per hectare. Parallel gravimetric evaporation measurements indicated that daily evaporative losses in bare soil ranged from roughly 2,833 grams per square meter per day in cooler months, such as January, up to over 4,800 grams per square meter per day during peak summer in May. Conversely, soils covered with coconut coir exhibited much lower evaporation rates, with losses between approximately 807 and 1,370 grams per square meter per day, demonstrating a daily reduction of between 1,460 and 3,675 grams per square meter. These findings clearly illustrate the efficacy of coconut coir mulch in suppressing soil evaporation consistently throughout the year, thereby enhancing soil moisture retention and mitigating irrigation requirements in tomato cultivation under tropical conditions. Table 4 Water Footprint and Evaporation Losses in Tomato Cultivation with and without Coconut Coir Mulch Month Avg. Temp (°C) ET₀ (mm) Water Loss – No Coir (L/m²) Water Loss – With Coir (L/m²) Water Saved (L/m²) Water Footprint Saved (m³/ha) Gravimetric EWL – No Coir (g/m²/day) Gravimetric EWL – With Coir (g/m²/day) Gravimetric EWL Saved (g/m²/day) Rainfall (mm) Green Water Used (L/m²) Blue Water Needed (L/m²) Jan 25.9 85 85 24.2 60.8 608 2833.33 806.67 2026.67 26.5 24.2 0.0 Feb 26.9 90 90 25.7 64.3 643 3000.00 856.67 2143.33 26.5 25.7 0.0 Mar 29.0 110 110 31.3 78.7 787 3666.67 1043.33 2623.33 49.0 31.3 0.0 Apr 31.0 130 130 37.2 92.8 928 4333.33 1240.00 3093.33 49.0 37.2 0.0 May 32.8 145 145 41.1 103.9 1039 4833.33 1370.00 3463.33 49.0 41.1 0.0 Jun 32.3 140 140 39.7 100.3 1003 4666.67 1323.33 3343.33 97.25 39.7 0.0 Jul 31.4 130 130 37.2 92.8 928 4333.33 1240.00 3093.33 97.25 37.2 0.0 Aug 30.7 120 120 34.2 85.8 858 4000.00 1140.00 2860.00 97.25 34.2 0.0 Sep 30.1 120 120 34.2 85.8 858 4000.00 1140.00 2860.00 97.25 34.2 0.0 Oct 29.5 125 125 35.4 89.6 896 4166.67 1180.00 2986.67 196.7 35.4 0.0 Nov 28.9 110 110 31.3 78.7 787 3666.67 1043.33 2623.33 196.7 31.3 0.0 Dec 27.6 90 90 25.7 64.3 643 3000.00 856.67 2143.33 196.7 25.7 0.0 Table 4 presents monthly data on temperature, reference evapotranspiration (ET₀), soil water loss, and evaporation rates for tomato cultivation under bare soil and coconut coir mulch conditions. The table includes measured soil water losses (L/m²) and gravimetric evaporation losses (g/m²/day), alongside calculated water savings attributable to the mulch. Rainfall data are integrated to estimate effective precipitation contribution, enabling the partitioning of crop water use into green and blue water components. Values highlight significant reductions in soil water loss and evaporation rates due to coconut coir application, translating into substantial water conservation over the crop cycle at both square meter and hectare scales. 3.7 Nutrient Use Efficiency and Nitrate Retention The application of Trichoderma harzianum significantly enhanced nitrogen uptake and retention in tomato plants. In the foliar treatment group (T1), total nitrogen uptake was 12% higher than the untreated control (T3), while the coir-embedded T. harzianum treatment (T2) exhibited a 28% increase. Root and shoot biomass were notably greater in T1 and T2, with T2 showing the highest values. Nitrate concentration in rhizosphere soils decreased in both treatments compared to the control, with T2 showing a 35% reduction in nitrate leaching. Nitrogen use efficiency (NUE), calculated as the ratio of yield to nitrogen applied, reached 105 kg/kg N in T2, 96 kg/kg N in T1, and 76 kg/kg N in T3. Fruit yield also reflected these improvements, with T2 recording a 27% increase and T1 a 19% increase over T3. 3.8 Land Use Efficiency Tomato yield varied significantly across treatments. T2 achieved the highest yield at 470 kg/ha, followed by T1 at 224.7 kg/ha, and the control (T3) at 125 kg/ha. This represented a 276% increase in yield for T2 over T3. Water productivity (yield per litre of water) also followed this trend, with values of 0.04 kg/L in T2, 0.02 kg/L in T1, and 0.01 kg/L in T3. Daily evaporative losses were markedly reduced in the coir-treated plots, resulting in a saving of approximately 9.9 litres per 100 m² per day. Irrigation frequency in T2 was extended from once per day to once every three days due to improved soil moisture retention. On an annual scale, the water savings per hectare exceeded 12,000 m³. The coir mulch cost ₹50 per unit, but this cost was offset by increased yield and reduced water use. 4. DISCUSSION 4.1 Microbial Colonization of Trichoderma harzianum The successful post-treatment colonization of T. harzianum in both foliar spray (T1) and coconut fibre mulch (T2) applications demonstrates its capacity to establish effectively in the tomato rhizosphere. The absence of fungal colonies in pre-treatment soil confirms that T. harzianum presence was directly due to the treatments, validating the methodology. Colonization was more pronounced in T2, where coconut fibre mats acted as sustained-release substrates, gradually facilitating fungal spread into the root zone. This aligns with previous findings on the compatibility of T. harzianum with organic carriers like coir, which support fungal viability by maintaining moisture and providing structural stability [ 42 , 43 ]. The colonization of both the carrier and soil highlights the advantage of biodegradable delivery systems that serve as microbial reservoirs and integrate with soil ecology. LPCB staining further confirmed active fungal growth, supporting coir mats as efficient inoculum carriers in precision biocontrol. 4.2 Tomato Growth Response to Trichoderma harzianum Applications (T1 and T2) vs Control (T3) Enhanced growth in both T1 and T2 compared to the control underscores the growth-promoting potential of T. harzianum . Increased height, leaf number, and flowering, particularly in T2, reveal how substrate-based delivery fosters vigorous and uniform plant development. Faster growth rates and earlier reproductive stages in T2 reflect a sustained microbial interaction due to continuous inoculant presence in the rhizosphere. These enhancements can be attributed to phytohormone production (e.g., indole-3-acetic acid), phosphate solubilization, and siderophore-mediated iron uptake, key traits of Trichoderma spp. [ 44 ]. Coir likely amplified benefits by improving aeration and water retention around roots [ 45 ]. In contrast, control plants showed limited growth, emphasizing the critical role of biological agents and organic substrates for optimal development. 4.3 Yield Performance Across Treatments Yield data demonstrated T2’s superiority, recording a 109% increase over control and 47% over foliar treatment. The coir-based inoculation contributed not only a short-term productivity boost but sustained yield gains across successive harvests. Such enhancements likely result from improved nutrient uptake, reduced abiotic stress, and healthier rhizosphere environments [ 26 ]. The synergistic interaction between T. harzianum and the coconut fibre matrix probably supported enhanced microbial persistence and colonization, translating into better productivity. Conversely, the untreated control, lacking these microbial and substrate inputs, exhibited poor yield, underscoring the vital importance of biologically active soil amendments. 4.4 Disease Incidence Significantly reduced incidence of Septoria leaf spot and anthracnose in treated plots, especially T2, indicates robust biocontrol potential of T. harzianum under field conditions. The sustained fungal presence in the rhizosphere likely fostered continuous production of antifungal metabolites and activated systemic plant immune responses. Mycoparasitism, enzyme secretion, and secondary metabolite production (e.g., gliotoxin, peptaibols) are known mechanisms of T. harzianum antagonism [ 46 ]. Coconut coir may have further enhanced disease resistance by buffering root microenvironments, thereby moderating moisture and temperature fluctuations that typically exacerbate pathogen activity [ 47 ]. The combined microbial and physical actions reduced disease and decreased reliance on synthetic fungicides, preserving crop health and yield. 4.5 Water Footprint The coconut coir-treated soils exhibited a substantial reduction in water loss, underscoring the mulch’s efficiency in improving soil moisture retention. Its porous and hydrophilic nature created a microenvironment that limited soil exposure and evaporation [ 45 ]. The greatest evapotranspiration reductions occurred during the hottest months, aligning with peak ET₀. A calculated 71.4% decrease in evaporative losses is consistent with prior findings in similar agroclimatic zones, leading to less frequent irrigation and a marked reduction in the blue water footprint as defined [ 28 ]. Beyond direct water savings, coir mulch enhanced soil physical properties, supporting better infiltration and microbial activity [ 48 ]. Compared to plastic or bare soil mulches, coir presents a biodegradable, environmentally sustainable option that also mitigates soil heat accumulation detrimental to microbial health [ 47 ]. With an estimated annual water saving of 9,830 m³/ha, this practice is particularly valuable in water-scarce regions. 4.6 Predicted Yield Response and Climate Adaptation Using regional temperature data, cumulative Growing Degree Days (GDD) and Heat Degree Days (HDD) were calculated for multiple seasonal windows and applied to a calibrated yield prediction model. Although the current season (July–August) represents the reference with GDD of 1240°C days and negligible HDD, alternative windows such as March–May and June–August present differing thermal profiles affecting yield projections. Applying a heat penalty factor of 3 to HDD, predicted yields for these windows ranged between 21 and 22.4 kg per 10 plants, scaled proportionally from the observed yields. These estimates, while lower than the reference season, due to shorter or cooler accumulated heat, provide practical insights for optimizing transplant timing to avoid heat stress and maximize yield potential. Temperature-driven yield modelling supports sensitive planting date selection to harness favourable climatic windows while acknowledging that integrated models incorporating water availability and biotic stresses are needed for comprehensive prediction [ 24 , 25 , 8 ]. 4.7 Nutrient Use Efficiency and Nitrate Retention The improvements in plant nitrogen uptake and yield under Trichoderma harzianum treatments highlight the role of beneficial microbes in enhancing nutrient dynamics. T. harzianum promotes root development and nutrient assimilation through mechanisms such as auxin production and upregulation of nitrogen transporter genes [ 44 ]. The reduction in nitrate leaching observed in both T1 and T2 is critical, as nitrate loss contributes significantly to grey water footprints and groundwater contamination. The coconut coir matrix in T2 appeared to sustain microbial populations for longer periods, supporting both enhanced retention and transformation of nitrates within the root zone. This aligns with the findings of [ 48 ], who reported improved nitrate conservation in coir-based microbial systems. The significantly higher nitrogen use efficiency in T2 suggests a more sustainable nutrient input-output ratio. As excess nitrogen fertilizers often lead to leaching and environmental degradation, T. harzianum, in conjunction with coir mulch, presents a viable strategy to reduce nitrogen-related losses and dependency on synthetic inputs [ 43 , 50 ]. 4.8 Land Use Efficiency The integration of T. harzianum with coconut coir not only enhanced plant growth and yield but also contributed to more efficient use of land and water resources. T2’s higher land use efficiency can be attributed to the synergistic action of improved soil moisture retention by coir and the bioactivity of T. harzianum, which collectively increased nutrient availability and minimised environmental losses [ 51 ]. The reduced irrigation frequency observed in T2 also implies labour and energy savings. Despite the upfront cost of coir mulch, the long-term economic and ecological benefits, including improved yield, reduced water consumption, and better soil health, justify its application. The yield gain of 276% and water productivity of 0.04 kg/L in T2 demonstrate the advantage of this integrated approach over both foliar application and the untreated control. Although direct measurements of soil biological activity were not performed, the observed outcomes strongly indicate positive shifts in soil microbial dynamics and physical structure, as supported by the literature [ 22 ]. These findings reinforce the potential of combining biological and organic strategies in precision agriculture systems to enhance resilience, efficiency, and sustainability. 5. Conclusion This study demonstrates the superior efficacy of Trichoderma harzianum -infused coconut fibre mats in enhancing tomato plant growth, yield, water conservation, and disease resistance. Compared to foliar application or untreated controls, the coir-based system significantly improved vegetative development, early flowering, and fruit set. Coconut coir not only served as a biodegradable, microbe-supportive substrate but also outperformed conventional carriers like biochar and plastic mulch by promoting beneficial microbial activity without introducing weeds or phytopathogens. The use of coir enhanced the soil water holding capacity by 127 g per unit, reducing evaporative loss by 71.7%, and extending irrigation intervals from daily to every three days. This translates to approximately 1.2 cubic meters of water saved per ton of tomatoes of water saved per hectare per season, improving water use efficiency to 0.04 kg/L in the coir-treated plots. Land use efficiency also improved, with yields reaching 470 kg/ha in T2 compared to 125 kg/ha in controls. While yield differences were not statistically significant due to limited replication, clear positive trends were observed. Economically, the low cost of coir (₹50 per unit) is offset by reduced irrigation frequency, increased yield, and improved soil health. The presence of T. harzianum likely contributed to enhanced nitrate uptake and nutrient retention, which, together with coir, supports long-term soil fertility. Though soil microbial counts, SOM, and bulk density were not measured, existing literature supports their improvement under such practices. Overall, this integrated approach offers a scalable, eco-friendly strategy for sustainable agriculture. Future research should explore microbial consortia, long-term field effects, and alternate substrates to maximise agronomic and environmental benefits. Declarations CONFLICT OF INTEREST The authors declare no conflict of interest. ETHICS DECLARATIONS ETHICS APPROVAL AND CONSENT TO PARTICIPATE Not Applicable CONSENT TO PUBLISH All authors consent to the publication of the study findings presented in this paper. FUNDING The authors acknowledge the TNSCST student project scheme for funding the research work. Author Contribution J.P.S.J., S.L.C., and S.K.T. conceived and designed the study. J.P.S.J., S.L.C., and M.H.E. performed the experiments and collected the data. C.C.A. and S.K.T. analyzed the results and contributed to the interpretation. J.P.S.J., S.L.C., and M.H.E. drafted the manuscript with substantial input from all authors. S.K.T. supervised the project and finalized the manuscript for submission. All authors reviewed, revised, and approved the final version of the manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7487821","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":539316802,"identity":"c9ff4fb6-7e59-442a-8c1b-e5ffdc804b69","order_by":0,"name":"Jijo Philip Sam J","email":"","orcid":"","institution":"Madras Christian College, India","correspondingAuthor":false,"prefix":"","firstName":"Jijo","middleName":"Philip Sam","lastName":"J","suffix":""},{"id":539316804,"identity":"7c67caa6-9c8e-452f-a1fc-034bac31def9","order_by":1,"name":"Samson Lijoseraj Charles","email":"","orcid":"","institution":"Madras Christian College, 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06:38:01","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":164350,"visible":true,"origin":"","legend":"","description":"","filename":"43a0af80d5d74fe9be81bd1c27d26ff41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/834e647fbb7e7f539aa7d108.xml"},{"id":95790200,"identity":"4015170a-14c9-482e-a4cd-be5fadfe7beb","added_by":"auto","created_at":"2025-11-13 06:38:01","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179127,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/c733f8f0bdf96e573cc862ee.html"},{"id":95800932,"identity":"69092c0f-8847-451a-91ac-4b881e973ec1","added_by":"auto","created_at":"2025-11-13 08:23:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":992302,"visible":true,"origin":"","legend":"\u003cp\u003eSoil sample collected from Soil sample collected from T1 using the spray method to deliver \u003cem\u003eT. harzianum.\u003c/em\u003e The soil sample was serially diluted and plated on PDA media. a)10\u003csup\u003e-1 \u003c/sup\u003edilution,\u0026nbsp; b)10\u003csup\u003e-2\u003c/sup\u003e dilution, and c)10\u003csup\u003e-3 \u003c/sup\u003edilution. Soil sample collected from T2 using coconut fibre mats as carrier material to deliver \u003cem\u003eT. harzianum\u003c/em\u003e. d) 10\u003csup\u003e-1 \u003c/sup\u003edilution, e)10\u003csup\u003e-2\u003c/sup\u003e dilution, and f)10\u003csup\u003e-3 \u003c/sup\u003edilution. T3 which was a control plot for the comparative study\u003cem\u003e.\u003c/em\u003e g)10\u003csup\u003e-1 \u003c/sup\u003edilution, h)10\u003csup\u003e-2\u003c/sup\u003e dilution, and i)10\u003csup\u003e-3 \u003c/sup\u003edilution.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/bd96255222c2c841241aec51.png"},{"id":95790185,"identity":"5f105982-f9ec-442d-b1a2-4d3b94b8dd31","added_by":"auto","created_at":"2025-11-13 06:38:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":257749,"visible":true,"origin":"","legend":"\u003cp\u003eMicroscopic observation of \u003cem\u003eTrichoderma harzianum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/f195ed651d8ef01cb0fbfec5.png"},{"id":95790177,"identity":"2e0aabab-a2fd-45a2-8a86-74c12e8645a1","added_by":"auto","created_at":"2025-11-13 06:38:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":399212,"visible":true,"origin":"","legend":"\u003cp\u003eMean graph of plant height, flowers, number of leaves, and growth rate over time.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/0a768174a6c03f9213d1ec9c.png"},{"id":95802498,"identity":"22163946-35f4-4f91-85fc-5ef776e17bd2","added_by":"auto","created_at":"2025-11-13 08:27:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":623170,"visible":true,"origin":"","legend":"\u003cp\u003eDisease incidence of the Tomato plant: a) Symptom of Septoria leaf spot. B) Symptoms of anthracnose disease of tomato.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/a36050a61468dcaa7cac6855.png"},{"id":95790180,"identity":"01f90562-31c1-42ad-ac6e-45af1a174f73","added_by":"auto","created_at":"2025-11-13 06:38:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":282989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMonthly water loss and savings from coir mulch application\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/6972aa5aff66b743d76bfd82.png"},{"id":99795690,"identity":"ac838c9c-f5d9-4aab-9042-63498ddc925b","added_by":"auto","created_at":"2026-01-08 13:39:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4861695,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7487821/v1/cdfa1380-5a01-4481-9892-1519cbb4c87f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Novel Approach to Use Coconut Fibre Mats Embedded with Trichoderma harzianum as Precision Bio-control Agent","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn the current agricultural landscape, resource inefficiency has become increasingly intolerable due to mounting economic pressures and inflation. The extensive use of inputs for crop cultivation means that any unforeseen damage can result in substantial financial losses. Moreover, climate change has led to erratic weather patterns, such as extreme temperatures and heavy rainfall, causing massive crop failures and increased resource wastage [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These unfavourable climatic conditions can reduce the efficacy of biocontrol agents [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], while favourable conditions enhance their performance. Organic farming offers a sustainable alternative to conventional agricultural practices by emphasising ecological balance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], biodiversity conservation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and the use of natural inputs to manage pests and maintain soil fertility. It plays a critical role in promoting sustainability through reduced water consumption, minimised agrochemical usage, and enhanced biodiversity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].However, the slower pace and lower yields of organic farming often limit its widespread adoption. To address these limitations, precision farming is increasingly being adopted. This modern approach ensures efficient use of agricultural resources, leading to better crop yields, reduced input wastage, and increased profitability. By applying inputs in precise quantities, it maximises resource efficiency while minimising environmental impact [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. When combined with appropriate carrier materials and advanced monitoring techniques, precision farming can significantly enhance the delivery and efficacy of biocontrol agents. Integrating precision farming with organic practices optimises the use of natural inputs without over-application, making agriculture more efficient and sustainable [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The overreliance on chemical pesticides to manage plant pathogens, insect pests, weeds, and nematodes has exceeded safe thresholds, severely degrading soil health and harming non-target organisms [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Beneficial soil microbes and predator insects that are essential components of agroecosystem biodiversity are also adversely affected. Moreover, the human health implications are profound: pesticide exposure has been linked to adverse effects in farmers [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] while residues have been detected in breast milk, potentially harming infants [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Persistent pesticide residues can remain in the soil for decades, sometimes even centuries [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], contaminating crops [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and contributing to environmental pollution, as only 0.1% of applied pesticides reach their target organisms [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In response, governments have introduced strict regulations to curtail pesticide use, creating a demand for sustainable, eco-friendly alternatives. Plant diseases pose a serious threat to global food security by reducing both crop yield and quality. These diseases are caused by various pathogens, including fungi, bacteria, and viruses, and spread through contaminated planting material, air, soil, and insect vectors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The severity and spread of disease depend on environmental conditions, host plant susceptibility, and pathogen virulence. Annually, phytopathogens are responsible for approximately 16% of crop yield losses, with fungi alone accounting for nearly 85% of plant diseases. According to the Food and Agriculture Organisation (FAO), pests and pathogens contribute to 20\u0026ndash;40% of global crop losses each year. Many of these pathogens can remain viable in the soil for extended periods, posing long-term threats to agriculture. Precision farming ensures agricultural resources are utilized efficiently for better yield with minimal wastage and maximum profitability. Coconut fibre is an eco-friendly material used as a substrate for \u003cem\u003eTrichoderma harzianum\u003c/em\u003e in biocontrol applications. It supports colonization of beneficial microorganisms while preventing weed growth through its natural mulching properties [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It offers a biodegradable and eco-friendly medium for supporting the colonization and proliferation of beneficial microorganisms like \u003cem\u003eTrichoderma harzianum\u003c/em\u003e. It provides additional agronomic benefits, including suppression of weed growth through natural mulching, enhanced water retention, and reduced UV exposure on plant roots [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Its high carbon-to-nitrogen ratio ensures slow decomposition, making it suitable for long-term agricultural use. Moreover, coconut fibre mats can reduce soil temperatures by up to 4\u0026deg;C, offering protection from heat stress and promoting root health. Biocontrol agents, including entomopathogenic fungi, bacteria, viruses, and predatory insects, present an environmentally sustainable alternative to chemical pesticides [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These agents act through various mechanisms, such as competition, antibiosis, and parasitism, to suppress pathogen populations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Their application enhances biodiversity, preserves soil health, and minimises chemical dependencies. The choice of carrier material plays a crucial role in the success of biocontrol agents by enhancing their viability, field efficacy, and storage stability [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Ideal carriers protect agents from environmental stressors, aid in uniform distribution, and ensure prolonged shelf life. Common carriers include talc, kaolin clay, oil-based, and aqueous formulations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Trichoderma harzianum, a soil-dwelling fungus from the \u003cem\u003eHypocreaceae\u003c/em\u003e family, is among the most effective biocontrol agents due to its multifaceted mechanisms, including mycoparasitism, antibiosis, and the induction of systemic resistance in host plants [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It not only suppresses a wide range of phytopathogens but also contributes to soil detoxification by degrading persistent pesticides such as DDT, dieldrin, endosulfan, pentachloronitrobenzene, and pentachlorophenol, thereby enhancing soil fertility and plant growth [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Tomato (\u003cem\u003eLycopersicon esculentum\u003c/em\u003e) is a crop of significant economic importance and serves as an excellent model for studying plant-pathogen interactions due to its high susceptibility to various diseases [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Closely related to other Solanaceae members such as potatoes (\u003cem\u003eSolanum tuberosum\u003c/em\u003e), brinjal (\u003cem\u003eSolanum melongena\u003c/em\u003e), and tobacco (\u003cem\u003eNicotiana tabacum\u003c/em\u003e), tomatoes are widely consumed and heavily utilised in food processing industries [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTheir vulnerability to bacterial, fungal, and viral infections makes them ideal candidates for evaluating biocontrol strategies. The present study emphasises the application of \u003cem\u003eT. harzianum\u003c/em\u003e in precision farming systems to reduce input costs and enhance crop productivity. By incorporating \u003cem\u003eT. harzianum\u003c/em\u003e into coconut fibre mats, a sustained and controlled release of spores into the rhizosphere is achieved. This eliminates the need for repeated applications, as the fungus proliferates within the coconut substrate, providing long-term protection against soilborne pathogens [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This integrated approach, merging biocontrol with precision agriculture and sustainable substrates like coconut fibre, represents a significant step toward reducing reliance on chemical pesticides, lowering production costs, and enhancing ecological resilience in crop production systems [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. While the current study presents results from a single growing season, addressing the limitations of single-season data is critical for broad adoption and robust agronomic recommendations. Multi-season analysis using predictive models, such as the Crop Water Production Function (CWPF) or similar well-validated temperature and rainfall response models for tomato, allows simulation of yield and water use under varied seasonal conditions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These models incorporate field-collected temperature, evapotranspiration (ET₀), and rainfall data to project crop performance, enabling farmers and researchers to anticipate outcomes over multiple seasons and adjust management practices. In parallel, water footprint analysis provides a comprehensive evaluation of water use in crop production. This framework partitions total water consumption into three components: blue water footprint, which is the volume of irrigation water withdrawn from surface or groundwater representing direct freshwater abstraction; green water footprint, the volume of rainwater retained in the soil and used by the crop via evapotranspiration; and grey water footprint, the volume of freshwater required to dilute pollutants, primarily nitrogen leachates to meet water quality standards, reflecting potential environmental contamination risks [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Applying this approach to your system, the analysis can compare blue water footprints under conventional and coconut coir mulch regimes, explicitly quantifying how mulch-enhanced soil moisture conservation increases the relative contribution of green water. Such partitioning is essential for evaluating groundwater conservation strategies, particularly in semi-arid regions where groundwater depletion is a growing concern. By calculating and contrasting seasonal blue, green, and grey water footprints per unit yield across multiple seasonal scenarios, the study extends its practical relevance. The results enable a clear demonstration of how improved soil water retention through coconut fibre mulching reduces irrigation demands (blue water), enhances rainwater utilisation (green water), and minimises nutrient leaching (grey water), collectively fostering sustainable water management and crop resilience. The aim of this study was to evaluate the efficacy of coconut fibre mats embedded with \u003cem\u003eT. harzianum\u003c/em\u003e as a precision biocontrol agent for tomato cultivation, with special emphasis on improving growth, yield, disease resistance, and water use efficiency. It further sought to develop predictive models to assess multi-seasonal yield potentials and quantify water footprint components under varying seasonal conditions, thereby providing an integrated framework for sustainable and resource-efficient tomato production.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Nursery Preparation\u003c/h2\u003e\u003cp\u003eA nursery site was established at the MCC farm (12.9155504 N, 80.1258663 E), selected for optimal sunlight and accessible irrigation. The area was fenced to protect seedlings from poultry and stray animals. The nursery soil was ploughed and sun-dried to reduce soil-borne pathogens. Well-decomposed, dried vermicompost was thoroughly incorporated into the soil before seed sowing. Certified tomato (\u003cem\u003eSolanum lycopersicum L\u003c/em\u003e.) seeds (variety: PKM 1, brand: Nisco) with 99% genetic purity, 98% physical purity and 70% germination rate were procured from Nisco Agritech Pvt. Ltd., Karnataka, India. Since the seeds are commercially available, no specific permits or authorisations were required for their use in this study. The seeds were evenly broadcast, followed by light irrigation to aid germination. One week prior to transplantation, watering was minimised to harden seedlings, enhancing field establishment potential [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Land Preparation\u003c/h2\u003e\u003cp\u003eA 25 \u0026times; 5 m\u0026sup2; field was cleared of debris with the borders secured using recycled sacks. Primary tillage involved a tractor-mounted rotovator for soil loosening and compost incorporation, followed by harrowing for levelling and improved water movement. Ridges and furrows were created for drainage and cultural operations. The plot was divided into three equal sections (5 \u0026times; 5 m\u0026sup2;). Tomato seedlings (aged 25 days) were transplanted on ridges spaced 100 cm apart, ensuring robust root systems by planting to a depth that leaves only the top leaves above ground. Pre-transplant irrigation was withheld one week before uprooting, followed by immediate post-plant irrigation. Periodic manual weeding and scheduled drip irrigation continued through the growing season [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Application of \u003cem\u003eTrichoderma harzianum\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eA commercial formulation of \u003cem\u003eT. harzianum\u003c/em\u003e(T22 strain, 2 \u0026times; 10⁹ spores/cm\u0026sup3;) was diluted to 10 mL/L water as per [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Application methods were as follows:\u003c/p\u003e\u003cp\u003eT1: Foliar spray applied with a hand-held pressure sprayer\u003c/p\u003e\u003cp\u003eT2: Coconut coir mulch soaked in \u003cem\u003eT. harzianum\u003c/em\u003e suspension for one hour and placed at the plant bases\u003c/p\u003e\u003cp\u003eT3: Untreated control\u003c/p\u003e\u003cp\u003eMud bunds separated the treatment plots. Applications were repeated every 15 days to maintain fungal populations [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Soil and Microbial Analysis\u003c/h2\u003e\u003cp\u003eRhizosphere soil samples were collected pre- and post-treatment to assess microbial population dynamics and nutrient status. Soil loosely adherent to roots was gently shaken off and pooled per treatment plot. Composite 10 g samples were suspended in 90 mL sterile distilled water and serially diluted (10⁻\u0026sup1; to 10⁻\u0026sup3;) for plating on Potato Dextrose Agar (PDA). Plates incubated at 28\u0026thinsp;\u0026plusmn;\u0026thinsp;of conidiophores 2\u0026deg;C for 5\u0026ndash;7 days were used to count colony-forming units (CFUs). \u003cem\u003eT. harzianum\u003c/em\u003e colonies were further identified using lactophenol cotton blue staining for microscopic observation and phialides [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Data Collection\u003c/h2\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1 Plant Growth Parameters\u003c/h2\u003e\u003cp\u003eTen randomly selected plants per treatment were monitored weekly for Plant height (cm), Number of leaves, Number of flowers, Average fruit weight (g), Fruit yield per plant (kg). Growth rate was calculated as [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] :\u003c/p\u003e\u003cp\u003eGrowth Rate (cm/day)\u0026thinsp;=\u0026thinsp;Final Height\u0026thinsp;\u0026minus;\u0026thinsp;Initial Height​ / Number of days\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.5.2 Harvesting\u003c/h2\u003e\u003cp\u003eTomato fruits ripened approximately three months post-transplantation. Harvesting occurred every three days, collecting partially ripe fruits to promote uniform ripening via ethylene accumulation. Damaged or diseased fruits were discarded. Yield was measured as total fruit weight per plot and extrapolated to kg/ha [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.5.3 Disease Observation\u003c/h2\u003e\u003cp\u003ePlants were visually inspected weekly for symptom development of common fungal diseases, including early blight and Fusarium wilt. Disease incidence and severity were recorded, and biocontrol efficacy of T. harzianum, particularly in coir-mulched plots, was evaluated relative to untreated controls [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.5.4 Nutrient Use Efficiency (NUE)\u003c/h2\u003e\u003cp\u003eTotal nitrogen input from organic compost and baseline soil was quantified, alongside post-harvest soil analysis for available nitrogen (N), phosphorus (P), and potassium (K) by Kjeldahl digestion, Olsen\u0026rsquo;s method, and flame photometry, respectively. NUE was calculated as [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]:\u003c/p\u003e\u003cp\u003e\u003cb\u003e​\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{N}\\varvec{U}\\varvec{E}\\:(\\varvec{k}\\varvec{g}\\:\\varvec{y}\\varvec{i}\\varvec{e}\\varvec{l}\\varvec{d}\\:/\\:\\varvec{k}\\varvec{g}\\:\\varvec{N})=\\varvec{T}\\varvec{o}\\varvec{t}\\varvec{a}\\varvec{l}\\:\\varvec{F}\\varvec{r}\\varvec{u}\\varvec{i}\\varvec{t}\\:\\varvec{Y}\\varvec{i}\\varvec{e}\\varvec{l}\\varvec{d}\\:\\left(\\varvec{k}\\varvec{g}\\right)/\\:\\varvec{T}\\varvec{o}\\varvec{t}\\varvec{a}\\varvec{l}\\:\\varvec{N}\\:\\varvec{s}\\varvec{u}\\varvec{p}\\varvec{p}\\varvec{l}\\varvec{i}\\varvec{e}\\varvec{d}\\:\\left(\\varvec{k}\\varvec{g}\\right)\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e2.5.5 Water Footprint Analysis\u003c/h2\u003e\u003cp\u003eWater footprint encapsulates crop water use partitioned into: blue, green, and grey components. Irrigation volumes were recorded during the experiment. Soil water retention and evaporation capacity were estimated via a 5-hour laboratory evaporation study at 36\u0026deg;C, measuring water lost from saturated soils with and without coconut coir mulch.\u003c/p\u003e\u003cp\u003eWater holding capacity was calculated by weighing saturated and oven-dried samples.\u003c/p\u003e\u003cp\u003eFormulas used:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eWater Productivity (WP)\u003c/b\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eWP\u0026thinsp;=\u0026thinsp;Total Fruit Yield (kg)​ / Total Water Used (L) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEvaporative Water Loss (EWL%)\u003c/b\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eEWL\u0026thinsp;=\u0026thinsp;Water Applied\u0026thinsp;\u0026minus;\u0026thinsp;Water Retained​ / Water Applied \u0026times;100\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eWater Saved per Day (L/100 m\u0026sup2;)\u003c/b\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eWater Saved=(Water Use T3\u0026thinsp;\u0026minus;\u0026thinsp;Water Use Treatment)\u0026times;Area\u003c/p\u003e\u003cp\u003eBlue, green, and grey water footprints were estimated per Hoekstra\u0026rsquo;s framework to assess irrigation water (blue), effective rainfall use (green), and water needed for nutrient pollutant dilution (grey). Seasonal rainfall data matched irrigation records to quantify water savings and groundwater conservation potential [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.5.6 Land Use Efficiency and Agronomic Indicators\u003c/h2\u003e\u003cp\u003eLand use efficiency (LUE) was computed as:\u003c/p\u003e\u003cp\u003eLUE\u0026thinsp;=\u0026thinsp;Land Area (m\u0026sup2;) / Total Yield (kg)​\u0026times;100\u003c/p\u003e\u003cp\u003eKey agronomic indicators\u0026mdash;yield, irrigation frequency, evaporative loss, and nutrient content\u0026mdash;were monitored. Economic viability was assessed by comparing input costs (including coconut coir mulch) relative to yield increase and resource savings [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.5.7 Prediction Methodology for Multi-Season Yield\u003c/h2\u003e\u003cp\u003eTo project yields beyond the single study season, temperature-driven models were applied:\u003c/p\u003e\u003cp\u003eThermal indices, including Growing Degree Days (GDD), Heat Degree Days (HDD), and Cold Degree Days (CDD), were computed daily:\u003c/p\u003e\u003cp\u003e\u003cem\u003eGDD\u003c/em\u003e\u003csub\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e​\u003c/em\u003e = max (min (T\u003csub\u003e\u003cem\u003eavg\u003c/em\u003e​\u003c/sub\u003e, T\u003csub\u003e\u003cem\u003eu\u003c/em\u003e\u003c/sub\u003e​)\u0026thinsp;\u0026minus;\u0026thinsp;T\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e​, 0)\u003c/p\u003e\u003cp\u003ewhere, T\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e=10\u0026deg;C, T\u003csub\u003e\u003cem\u003eu\u003c/em\u003e\u003c/sub\u003e=30\u0026deg;C, T\u003csub\u003e\u003cem\u003eh\u003c/em\u003e\u003c/sub\u003e = 32\u0026deg;C\u003c/p\u003e\u003cp\u003eHDD\u003csub\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sub\u003e​=max (T\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e​ \u0026minus; T\u003csub\u003e\u003cem\u003eh\u003c/em\u003e\u003c/sub\u003e​, 0)\u003c/p\u003e\u003cp\u003ewhere T\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e​ = daily maximum temperature (\u0026deg;C), T\u003csub\u003e\u003cem\u003eh\u003c/em\u003e\u003c/sub\u003e = 32\u0026deg;C\u003c/p\u003e\u003cp\u003eCDD\u003csub\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sub\u003e ​= max(T\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e​\u0026minus;T\u003csub\u003e\u003cem\u003emin​\u003c/em\u003e\u003c/sub\u003e, 0)\u003c/p\u003e\u003cp\u003ewhere, T\u003csub\u003e\u003cem\u003emin ​\u003c/em\u003e\u003c/sub\u003e= daily minimum temperature (\u0026deg;C), T\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e = 12\u0026deg;C\u003c/p\u003e\u003cp\u003eThe crop yield (Y) for each treatment was modelled as:\u003c/p\u003e\u003cp\u003eY\u0026thinsp;=\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e ​+ \u003cem\u003eβ\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e​GDD\u0026thinsp;\u0026minus;\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e​HDD\u0026thinsp;\u0026minus;\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e3\u003c/sub\u003e​CDD + \u003cem\u003eϵ\u003c/em\u003e\u003c/p\u003e\u003cp\u003eParameters βi\\beta_iβi​ were calibrated using observed yields and temperature data for treatments T1, T2, and T3.\u003c/p\u003e\u003cp\u003eFuture season yields were predicted by inputting temperature data of those seasons, thereby simulating yield responses incorporating heat stress and growth conditions.\u003c/p\u003e\u003cp\u003eLimitations include exclusion of water availability, radiation, pest outbreaks, and management effects; thus, projections serve as temperature-driven potential estimates [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2.5.8 Statistical Analysis\u003c/h2\u003e\u003cp\u003eData were analysed using Microsoft Excel to calculate means, standard deviations, and to perform ANOVA with Tukey\u0026rsquo;s multiple comparison test to evaluate treatment effects on plant growth, yield, and water use efficiency [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Microbial Colonisation of \u003cem\u003eTrichoderma harzianum\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eMicrobial analysis of rhizosphere soil samples before and after treatment confirmed the successful colonisation of \u003cem\u003eTrichoderma harzianum\u003c/em\u003e. Prior to treatment, soil samples from all plots subjected to serial dilution (10⁻\u0026sup1;, 10⁻\u0026sup2;, 10⁻\u0026sup3;) showed no detectable fungal growth on Potato Dextrose Agar (PDA), verifying the absence of \u003cem\u003eT. harzianum\u003c/em\u003e in the native soil. This established a clear baseline for evaluating treatment effects. Post-treatment soil samples from foliar spray (T1) and coconut fibre mulch (T2) treatments demonstrated significant fungal growth. Identification of colonies was verified both morphologically and microscopically, using lactophenol cotton blue staining, which revealed hyaline, septate hyphae, with typical phialides and conidial structures of \u003cem\u003eT. harzianum\u003c/em\u003e. Notably, in T2, fungal growth was present not only in the rhizosphere soil but also on the coconut fibre \u003cem\u003emulch\u003c/em\u003e surface, indicating both localised and lateral colonisation. No fungal colonies were detected in the control (T3), confirming the specificity of the introduced inoculum and validating the effectiveness of both application methods.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Tomato Growth Response to \u003cem\u003eTrichoderma harzianum\u003c/em\u003e Applications (T1 and T2) vs Control (T3)\u003c/h2\u003e\u003cp\u003eTomato plants exhibited significant growth differences across treatments. At transplantation (Day 0), plant height and leaf count were comparable, with T1 averaging 4.5 cm height and 7.3 leaves, T2 at 4.0 cm and 3.9 leaves, and T3 at 4.4 cm and 5.3 leaves. By Day 14, T1 reached 43.6 cm with 13.8 leaves, while T2 grew to 64.6 cm with 14.7 leaves. The control plants lagged at 29.7 cm and 5.3 leaves. Growth rates were calculated as 2.79 cm/day for T1, 4.34 cm/day for T2, and 1.81 cm/day for T3. On Day 28, T2 plants averaged 95.0 cm in height with 23.6 leaves and 26.1 flowers per plant, outperforming T1, which showed 69.0 cm height, 33.9 leaves, and 21.1 flowers. T3 plants remained underdeveloped with 41.0 cm height, 13.9 leaves, and 6.8 flowers. The standard deviations in T2 were lower than those in T1, indicating greater growth uniformity across the population.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysiological parameters of the tomato plants treated with Foliar Application of \u003cem\u003eTrichoderma harzianum\u003c/em\u003e (T1, T2, and T3)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eS. No.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePlant Parameters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eT3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0th day After Transplantation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHeight of Plant (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Number of Leaves\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e14th day After Transplantation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHeight of Plant (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e64.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Number of Leaves\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrowth Rate (cm/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e28th day After Transplantation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHeight of Plant (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e11.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Number of Leaves\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Number of Flowers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrowth Rate (cm/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Yield Performance Across Treatments\u003c/h2\u003e\u003cp\u003eYield data collected over three harvests confirmed the superior performance of treated plants. In T2 plots, yields of 6.0 kg, 8.33 kg, and 32.67 kg per 10 plants were recorded for Harvests 1, 2, and 3 respectively, averaging 15.67 kg per 10 plants or 470 kg/ha. T1 yielded 1.47 kg, 6.33 kg, and 14.67 kg over the three harvests, averaging 7.49 kg per 10 plants or 224.7 kg/ha. The T3 control showed the lowest productivity, with 0.17 kg, 4.0 kg, and 8.33 kg per harvest, averaging 4.17 kg per 10 plants or 125 kg/ha. These data reveal a strong positive correlation between microbial treatment method and cumulative yield, with T2 delivering the most substantial benefits.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"7\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTotal yield of T1, T2 treated and T3 untreated tomato plant\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHarvest 1 (mean of 10 plants)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHarvest 2 (mean of 10 plants)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHarvest 3 (mean of 10 plants)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTotal (kg/ha)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e224.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e470\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eT3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Disease Incidence\u003c/h2\u003e\u003cp\u003eDisease incidence was significantly influenced by the treatments. In the untreated control (T3), Septoria leaf spot symptoms were observed in 30% of the plants. T1 reduced this incidence to 16%, while T2 showed the lowest rate at 10%. When combined with anthracnose observations, overall disease incidence was 29.3% in T3, 22.8% in T1, and 14.6% in T2. Fruit rot caused by anthracnose was particularly evident in T3, reducing marketable yield. Visual and symptomatic assessments supported these findings, and statistical analysis confirmed significant differences among the treatments (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with T2 exhibiting the most effective disease suppression.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Predicted Seasonal Yield Response to Temperature Variability\u003c/h2\u003e\u003cp\u003eTo evaluate potential yields across different planting windows, we calculated cumulative Growing Degree Days (GDD) and Heat Degree Days (HDD) using Tamil Nadu\u0026rsquo;s monthly temperature data and applied these indices to our calibrated yield model. The analysis covered four key three-month periods and the full year, with yields scaled to the July\u0026ndash;August reference season (470 kg/ha for T2). Results (Table X) demonstrate that cooler periods like Jan\u0026ndash;Mar have limited heat accumulation, resulting in the lowest predicted yields (e.g., 19.6 kg/ha for T2). The pre-monsoon (Mar\u0026ndash;May), summer (Jun\u0026ndash;Aug), and post-monsoon (Sep\u0026ndash;Nov) seasons offer increased thermal units with minimal heat stress, producing moderately higher projected yields ranging from 21.5 to 22.4 kg/ha for T2. When aggregated annually, predicted yields approach 44 kg/ha under optimal management. These findings emphasize the critical role of aligning transplanting schedules with favourable temperature windows that maximize beneficial warmth while minimizing heat stress. Optimizing this thermal balance, alongside strategic use of biocontrol-enhanced mulching, can substantially improve tomato productivity across seasons in Tamil Nadu.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredicted Seasonal Yield Response to Temperature Variability\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeason\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMonths\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal GDD (\u0026deg;C\u0026middot;days)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal HDD (\u0026deg;C\u0026middot;days)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePredicted Yield T2 (kg/ha)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePredicted Yield T1 (kg/ha)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePredicted Yield T3 (kg/ha)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRelative Yield Scale\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWinter-Early\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJan - Mar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e51.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-Monsoon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMar - May\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSummer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJun - Aug\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e6.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-Monsoon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSep - Nov\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear-Round\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJan - Dec\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e118.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e predicted tomato yields for different seasonal planting windows based on cumulative thermal metrics derived from monthly average temperatures in Tamil Nadu. The table summarizes the total Growing Degree Days (GDD) using a base temperature of 10\u0026deg;C and upper cap of 30\u0026deg;C, and total Heat Degree Days (HDD) applying a threshold of 32\u0026deg;C to quantify heat stress during the respective seasons. The yield predictions for each treatment (T2: coconut fibre mat\u0026thinsp;+\u0026thinsp;Trichoderma harzianum; T1: foliar T. harzianum; T3: untreated control) are scaled relative to a reference yield observed during the July\u0026ndash;August season (T2\u0026thinsp;=\u0026thinsp;470 kg/ha, T1\u0026thinsp;=\u0026thinsp;224.7 kg/ha, T3\u0026thinsp;=\u0026thinsp;125 kg/ha). A penalty factor of 3 was applied to HDD to account for heat-induced yield reductions. The relative yield scale represents the ratio of the season\u0026rsquo;s combined thermal metric.(GDD\u0026thinsp;\u0026minus;\u0026thinsp;3\u0026times;HDD) to that of the reference season (1240 degree-days). Results indicate variable yield potentials across seasonal production windows, with the highest cumulative potential in the year-round scenario. This modelling approach isolates temperature effects, assuming consistent management, and excludes other limiting factors such as water deficits, pest pressures, and nutrient constraints.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Water Footprint and Evaporation Losses in Tomato Cultivation with and without Coconut Coir Mulch\u003c/h2\u003e\u003cp\u003eThe water footprint analysis was conducted using monthly temperature and rainfall data from June 2024 to May 2025, obtained from regional meteorological records for Tamil Nadu, India [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These data facilitated the estimation of reference evapotranspiration (ET₀) and the quantification of soil water loss with and without coconut coir mulch application. Results showed that soil without mulch experienced an annual water loss of approximately 1,375 litres per square meter, while the presence of coir mats significantly reduced this loss to 392 litres per square meter, yielding a substantial net saving of 983 litres per square meter annually. When extrapolated to the hectare scale, this represents a water conservation of about 9,830 cubic meters per hectare. Parallel gravimetric evaporation measurements indicated that daily evaporative losses in bare soil ranged from roughly 2,833 grams per square meter per day in cooler months, such as January, up to over 4,800 grams per square meter per day during peak summer in May. Conversely, soils covered with coconut coir exhibited much lower evaporation rates, with losses between approximately 807 and 1,370 grams per square meter per day, demonstrating a daily reduction of between 1,460 and 3,675 grams per square meter. These findings clearly illustrate the efficacy of coconut coir mulch in suppressing soil evaporation consistently throughout the year, thereby enhancing soil moisture retention and mitigating irrigation requirements in tomato cultivation under tropical conditions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWater Footprint and Evaporation Losses in Tomato Cultivation with and without Coconut Coir Mulch\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonth\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAvg. Temp (\u0026deg;C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eET₀ (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWater Loss \u0026ndash; No Coir (L/m\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWater Loss \u0026ndash; With Coir (L/m\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWater Saved (L/m\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eWater Footprint Saved (m\u0026sup3;/ha)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGravimetric EWL \u0026ndash; No Coir (g/m\u0026sup2;/day)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eGravimetric EWL \u0026ndash; With Coir (g/m\u0026sup2;/day)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eGravimetric EWL Saved (g/m\u0026sup2;/day)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRainfall (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eGreen Water Used (L/m\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eBlue Water Needed (L/m\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e608\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2833.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e806.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2026.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e26.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e24.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e64.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3000.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e856.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2143.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e26.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e78.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3666.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1043.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2623.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e49.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e31.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eApr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e92.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e928\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4333.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1240.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3093.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e49.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e103.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4833.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1370.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3463.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e49.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e41.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJun\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e39.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e100.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4666.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1323.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3343.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e97.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e39.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJul\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e92.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e928\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4333.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1240.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3093.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e97.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAug\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e85.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e858\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4000.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1140.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2860.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e97.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e34.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e85.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e858\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4000.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1140.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2860.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e97.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e34.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOct\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e89.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e896\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e4166.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1180.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2986.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e196.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e35.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNov\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e78.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3666.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1043.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2623.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e196.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e31.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDec\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e64.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e3000.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e856.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e2143.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e196.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents monthly data on temperature, reference evapotranspiration (ET₀), soil water loss, and evaporation rates for tomato cultivation under bare soil and coconut coir mulch conditions. The table includes measured soil water losses (L/m\u0026sup2;) and gravimetric evaporation losses (g/m\u0026sup2;/day), alongside calculated water savings attributable to the mulch. Rainfall data are integrated to estimate effective precipitation contribution, enabling the partitioning of crop water use into green and blue water components. Values highlight significant reductions in soil water loss and evaporation rates due to coconut coir application, translating into substantial water conservation over the crop cycle at both square meter and hectare scales.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Nutrient Use Efficiency and Nitrate Retention\u003c/h2\u003e\u003cp\u003eThe application of \u003cem\u003eTrichoderma harzianum significantly\u003c/em\u003e enhanced nitrogen uptake and retention in tomato plants. In the foliar treatment group (T1), total nitrogen uptake was 12% higher than the untreated control (T3), while the coir-embedded \u003cem\u003eT. harzianum\u003c/em\u003e treatment (T2) exhibited a 28% increase. Root and shoot biomass were notably greater in T1 and T2, with T2 showing the highest values. Nitrate concentration in rhizosphere soils decreased in both treatments compared to the control, with T2 showing a 35% reduction in nitrate leaching. Nitrogen use efficiency (NUE), calculated as the ratio of yield to nitrogen applied, reached 105 kg/kg N in T2, 96 kg/kg N in T1, and 76 kg/kg N in T3. Fruit yield also reflected these improvements, with T2 recording a 27% increase and T1 a 19% increase over T3.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e3.8 Land Use Efficiency\u003c/h2\u003e\u003cp\u003eTomato yield varied significantly across treatments. T2 achieved the highest yield at 470 kg/ha, followed by T1 at 224.7 kg/ha, and the control (T3) at 125 kg/ha. This represented a 276% increase in yield for T2 over T3. Water productivity (yield per litre of water) also followed this trend, with values of 0.04 kg/L in T2, 0.02 kg/L in T1, and 0.01 kg/L in T3. Daily evaporative losses were markedly reduced in the coir-treated plots, resulting in a saving of approximately 9.9 litres per 100 m\u0026sup2; per day. Irrigation frequency in T2 was extended from once per day to once every three days due to improved soil moisture retention. On an annual scale, the water savings per hectare exceeded 12,000 m\u0026sup3;. The coir mulch cost ₹50 per unit, but this cost was offset by increased yield and reduced water use.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Microbial Colonization of Trichoderma harzianum\u003c/h2\u003e\u003cp\u003eThe successful post-treatment colonization of \u003cem\u003eT. harzianum\u003c/em\u003e in both foliar spray (T1) and coconut fibre mulch (T2) applications demonstrates its capacity to establish effectively in the tomato rhizosphere. The absence of fungal colonies in pre-treatment soil confirms that \u003cem\u003eT. harzianum\u003c/em\u003e presence was directly due to the treatments, validating the methodology. Colonization was more pronounced in T2, where coconut fibre mats acted as sustained-release substrates, gradually facilitating fungal spread into the root zone. This aligns with previous findings on the compatibility of \u003cem\u003eT. harzianum\u003c/em\u003e with organic carriers like coir, which support fungal viability by maintaining moisture and providing structural stability [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The colonization of both the carrier and soil highlights the advantage of biodegradable delivery systems that serve as microbial reservoirs and integrate with soil ecology. LPCB staining further confirmed active fungal growth, supporting coir mats as efficient inoculum carriers in precision biocontrol.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Tomato Growth Response to \u003cem\u003eTrichoderma harzianum\u003c/em\u003e Applications (T1 and T2) vs Control (T3)\u003c/h2\u003e\u003cp\u003eEnhanced growth in both T1 and T2 compared to the control underscores the growth-promoting potential of \u003cem\u003eT. harzianum\u003c/em\u003e. Increased height, leaf number, and flowering, particularly in T2, reveal how substrate-based delivery fosters vigorous and uniform plant development. Faster growth rates and earlier reproductive stages in T2 reflect a sustained microbial interaction due to continuous inoculant presence in the rhizosphere. These enhancements can be attributed to phytohormone production (e.g., indole-3-acetic acid), phosphate solubilization, and siderophore-mediated iron uptake, key traits of Trichoderma spp. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Coir likely amplified benefits by improving aeration and water retention around roots [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In contrast, control plants showed limited growth, emphasizing the critical role of biological agents and organic substrates for optimal development.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Yield Performance Across Treatments\u003c/h2\u003e\u003cp\u003eYield data demonstrated T2\u0026rsquo;s superiority, recording a 109% increase over control and 47% over foliar treatment. The coir-based inoculation contributed not only a short-term productivity boost but sustained yield gains across successive harvests. Such enhancements likely result from improved nutrient uptake, reduced abiotic stress, and healthier rhizosphere environments [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The synergistic interaction between \u003cem\u003eT. harzianum\u003c/em\u003e and the coconut fibre matrix probably supported enhanced microbial persistence and colonization, translating into better productivity. Conversely, the untreated control, lacking these microbial and substrate inputs, exhibited poor yield, underscoring the vital importance of biologically active soil amendments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Disease Incidence\u003c/h2\u003e\u003cp\u003eSignificantly reduced incidence of Septoria leaf spot and anthracnose in treated plots, especially T2, indicates robust biocontrol potential of \u003cem\u003eT. harzianum\u003c/em\u003e under field conditions. The sustained fungal presence in the rhizosphere likely fostered continuous production of antifungal metabolites and activated systemic plant immune responses. Mycoparasitism, enzyme secretion, and secondary metabolite production (e.g., gliotoxin, peptaibols) are known mechanisms of \u003cem\u003eT. harzianum\u003c/em\u003e antagonism [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Coconut coir may have further enhanced disease resistance by buffering root microenvironments, thereby moderating moisture and temperature fluctuations that typically exacerbate pathogen activity [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The combined microbial and physical actions reduced disease and decreased reliance on synthetic fungicides, preserving crop health and yield.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e\u003ch2\u003e4.5 Water Footprint\u003c/h2\u003e\u003cp\u003eThe coconut coir-treated soils exhibited a substantial reduction in water loss, underscoring the mulch\u0026rsquo;s efficiency in improving soil moisture retention. Its porous and hydrophilic nature created a microenvironment that limited soil exposure and evaporation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The greatest evapotranspiration reductions occurred during the hottest months, aligning with peak ET₀. A calculated 71.4% decrease in evaporative losses is consistent with prior findings in similar agroclimatic zones, leading to less frequent irrigation and a marked reduction in the blue water footprint as defined [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Beyond direct water savings, coir mulch enhanced soil physical properties, supporting better infiltration and microbial activity [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Compared to plastic or bare soil mulches, coir presents a biodegradable, environmentally sustainable option that also mitigates soil heat accumulation detrimental to microbial health [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. With an estimated annual water saving of 9,830 m\u0026sup3;/ha, this practice is particularly valuable in water-scarce regions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\u003ch2\u003e4.6 Predicted Yield Response and Climate Adaptation\u003c/h2\u003e\u003cp\u003eUsing regional temperature data, cumulative Growing Degree Days (GDD) and Heat Degree Days (HDD) were calculated for multiple seasonal windows and applied to a calibrated yield prediction model. Although the current season (July\u0026ndash;August) represents the reference with GDD of 1240\u0026deg;C days and negligible HDD, alternative windows such as March\u0026ndash;May and June\u0026ndash;August present differing thermal profiles affecting yield projections. Applying a heat penalty factor of 3 to HDD, predicted yields for these windows ranged between 21 and 22.4 kg per 10 plants, scaled proportionally from the observed yields. These estimates, while lower than the reference season, due to shorter or cooler accumulated heat, provide practical insights for optimizing transplant timing to avoid heat stress and maximize yield potential. Temperature-driven yield modelling supports sensitive planting date selection to harness favourable climatic windows while acknowledging that integrated models incorporating water availability and biotic stresses are needed for comprehensive prediction [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e\u003ch2\u003e4.7 Nutrient Use Efficiency and Nitrate Retention\u003c/h2\u003e\u003cp\u003eThe improvements in plant nitrogen uptake and yield under \u003cem\u003eTrichoderma harzianum\u003c/em\u003e treatments highlight the role of beneficial microbes in enhancing nutrient dynamics. \u003cem\u003eT. harzianum\u003c/em\u003e promotes root development and nutrient assimilation through mechanisms such as auxin production and upregulation of nitrogen transporter genes [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The reduction in nitrate leaching observed in both T1 and T2 is critical, as nitrate loss contributes significantly to grey water footprints and groundwater contamination. The coconut coir matrix in T2 appeared to sustain microbial populations for longer periods, supporting both enhanced retention and transformation of nitrates within the root zone. This aligns with the findings of [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], who reported improved nitrate conservation in coir-based microbial systems. The significantly higher nitrogen use efficiency in T2 suggests a more sustainable nutrient input-output ratio. As excess nitrogen fertilizers often lead to leaching and environmental degradation, T. harzianum, in conjunction with coir mulch, presents a viable strategy to reduce nitrogen-related losses and dependency on synthetic inputs [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec33\" class=\"Section2\"\u003e\u003ch2\u003e4.8 Land Use Efficiency\u003c/h2\u003e\u003cp\u003eThe integration of \u003cem\u003eT. harzianum\u003c/em\u003e with coconut coir not only enhanced plant growth and yield but also contributed to more efficient use of land and water resources. T2\u0026rsquo;s higher land use efficiency can be attributed to the synergistic action of improved soil moisture retention by coir and the bioactivity of T. harzianum, which collectively increased nutrient availability and minimised environmental losses [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The reduced irrigation frequency observed in T2 also implies labour and energy savings. Despite the upfront cost of coir mulch, the long-term economic and ecological benefits, including improved yield, reduced water consumption, and better soil health, justify its application. The yield gain of 276% and water productivity of 0.04 kg/L in T2 demonstrate the advantage of this integrated approach over both foliar application and the untreated control. Although direct measurements of soil biological activity were not performed, the observed outcomes strongly indicate positive shifts in soil microbial dynamics and physical structure, as supported by the literature [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These findings reinforce the potential of combining biological and organic strategies in precision agriculture systems to enhance resilience, efficiency, and sustainability.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates the superior efficacy of \u003cem\u003eTrichoderma harzianum\u003c/em\u003e-infused coconut fibre mats in enhancing tomato plant growth, yield, water conservation, and disease resistance. Compared to foliar application or untreated controls, the coir-based system significantly improved vegetative development, early flowering, and fruit set. Coconut coir not only served as a biodegradable, microbe-supportive substrate but also outperformed conventional carriers like biochar and plastic mulch by promoting beneficial microbial activity without introducing weeds or phytopathogens. The use of coir enhanced the soil water holding capacity by 127 g per unit, reducing evaporative loss by 71.7%, and extending irrigation intervals from daily to every three days. This translates to approximately 1.2 cubic meters of water saved per ton of tomatoes of water saved per hectare per season, improving water use efficiency to 0.04 kg/L in the coir-treated plots. Land use efficiency also improved, with yields reaching 470 kg/ha in T2 compared to 125 kg/ha in controls. While yield differences were not statistically significant due to limited replication, clear positive trends were observed. Economically, the low cost of coir (₹50 per unit) is offset by reduced irrigation frequency, increased yield, and improved soil health. The presence of \u003cem\u003eT. harzianum\u003c/em\u003e likely contributed to enhanced nitrate uptake and nutrient retention, which, together with coir, supports long-term soil fertility. Though soil microbial counts, SOM, and bulk density were not measured, existing literature supports their improvement under such practices. Overall, this integrated approach offers a scalable, eco-friendly strategy for sustainable agriculture. Future research should explore microbial consortia, long-term field effects, and alternate substrates to maximise agronomic and environmental benefits.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCONFLICT OF INTEREST\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003e\u003cb\u003eETHICS DECLARATIONS\u003c/b\u003e\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/strong\u003e\u003cp\u003eNot Applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCONSENT TO PUBLISH\u003c/strong\u003e\u003cp\u003eAll authors consent to the publication of the study findings presented in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e\u003cp\u003eThe authors acknowledge the TNSCST student project scheme for funding the research work.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.P.S.J., S.L.C., and S.K.T. conceived and designed the study. J.P.S.J., S.L.C., and M.H.E. performed the experiments and collected the data. C.C.A. and S.K.T. analyzed the results and contributed to the interpretation. J.P.S.J., S.L.C., and M.H.E. drafted the manuscript with substantial input from all authors. S.K.T. supervised the project and finalized the manuscript for submission. All authors reviewed, revised, and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENT\u003c/h2\u003e\u003cp\u003eThe authors acknowledge Department of Microbiology, Madras Christian College for the constant support throughout the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll the data pertaining to the study have been included in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBirthal, P.S., Khan, T., Negi, D.S. and Agarwal, S. (2014) \u0026lsquo;Impact of climate change on yields of major food crops in India: Implications for food security\u0026rsquo;, \u003cem\u003eAgricultural Economics Research Review\u003c/em\u003e, 27(2), pp. 145\u0026ndash;155. https://doi.org/10.5958/0974-0279.2014.00019.6.\u003c/li\u003e\n\u003cli\u003eSelvaraj, S., Ganeshamoorthi, P. and Pandiaraj, T. (2013). Potential impacts of recent climate change on biological control agents in agro-ecosystem: A review. \u003cem\u003eInternational Journal of Biodiversity and Conservation\u003c/em\u003e, 5(12), pp. 845\u0026ndash;852.\u003c/li\u003e\n\u003cli\u003eK\u0026uuml;hling, I. and Trautz, D. (2013). The role of organic farming in providing ecosystem services. \u003cem\u003eInternational Journal of Environmental and Rural Development\u003c/em\u003e, 4(1), pp. 175\u0026ndash;178.\u003c/li\u003e\n\u003cli\u003eRundl\u0026ouml;f, M., Smith, H.G. and Birkhofer, K. (2016). 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Reducing peat in growing media: impact on nitrogen content, microbial activity, and CO2 and N2O emissions. \u003cem\u003eCanadian Journal of Soil Science\u003c/em\u003e, \u003cem\u003e102\u003c/em\u003e(1), 77-87. https://doi.org/10.1139/cjss-2020-0147 \u003c/li\u003e\n\u003cli\u003ePatel, T.S. and Minochecherhomji, F.P. (2018) Review: Plant Growth Promoting Rhizobacteria: Blessing to Agriculture. \u003cem\u003eInternational Journal of Pure \u0026amp; Applied Bioscience\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(2), 481\u0026ndash;492. http://dx.doi.org/10.18782/2320-7051.6383 \u003c/li\u003e\n\u003cli\u003eEvangelou, E., Tsadilas, C., Tserlikakis, N., Tsitouras, A., \u0026amp; Kyritsis, A. (2016). Water Footprint of Industrial Tomato Cultivations in the Pinios River Basin: Soil Properties Interactions. \u003cem\u003eWater\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(11), 515. https://doi.org/10.3390/w8110515\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7487821/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7487821/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe growing demand for sustainable agriculture has intensified interest in biological alternatives to synthetic inputs. \u003cem\u003eTrichoderma harzianum\u003c/em\u003e, a plant growth-promoting fungus, offers both biocontrol and stimulation of plant development, while organic mulching materials such as coconut fibre mats improve soil structure, conserve moisture, regulate temperature, and enhance microbial activity. This study assessed the combined effect of \u003cem\u003eT. harzianum\u003c/em\u003e application with coconut fibre mulching on tomato crop growth and yield through a field trial with three treatments: T1 \u0026ndash;foliar spraying of \u003cem\u003eT. harzianum\u003c/em\u003e, T2 \u0026ndash; root-zone application using \u003cem\u003eT. harzianum\u003c/em\u003e-inoculated coconut fibre mats, and T3 \u0026ndash; untreated control, arranged in a randomised complete block design with three replications. Plant height, fruit yield, and disease incidence were measured, showing that T2 significantly enhanced growth (95.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.58 cm) compared to T1 (69.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.47 cm) and T3 (41.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.33 cm), while fruit yield in T2 reached 470 kg ha⁻\u0026sup1;, representing a 276% increase over control (125 kg ha⁻\u0026sup1;) and higher than T1 (224.7 kg ha⁻\u0026sup1;, a 79.6% increase). Disease incidence was also lowest in T2 (10%) compared with T1 (16%) and T3 (30%), confirming a synergistic effect between root-zone \u003cem\u003eT. harzianum\u003c/em\u003e colonisation and soil health benefits of mulching. Although restricted to a single growing season, predictive models such as the crop water production function (CWPF) and water footprint analysis indicated that mulching increased reliance on rainwater, reduced groundwater withdrawal, and improved efficiency under variable temperature and rainfall. Overall, this integrated microbial\u0026ndash;mulch approach demonstrates a sustainable, eco-friendly strategy to boost tomato productivity and conserve natural resources.\u003c/p\u003e","manuscriptTitle":"Novel Approach to Use Coconut Fibre Mats Embedded with Trichoderma harzianum as Precision Bio-control Agent","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 06:37:56","doi":"10.21203/rs.3.rs-7487821/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cacc8af2-1c71-4794-a1bb-bd8da5e1f476","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-07T10:24:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 06:37:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7487821","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7487821","identity":"rs-7487821","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}