Assessment of physical compatibility of newer pesticide–adjuvant combinations for UAVs based spraying

Introduction

Paddy (Oryza sativa L.) is cultivated globally being one of the most important cereal crops worldwide. It is cultivated in more than 100 countries on every continent, except, for Antarctica, although 91 per cent of the world's rice is grown and consumed in Asia. USDA's global rice production in 2025-26 is projects lower supplies, smaller consumption, reduced trade and higher ending stocks. World 2025-26 consumption is lowered 0.8 million tons to 541.0 million, mostly on smaller consumption estimates for several African countries. Global 2025-26 trade is decreased 1.3 million tons to 62.0 million, largely on a slower-thanexpected pace of exports from India. Paddy acreage increased by 0.6% to 45 lakh hectares from 44.73 lakh hectares. Rice production was projected at 1406.48 lakh tonnes. Uttar Pradesh remained the largest producer, followed by Telangana and Punjab, with significant contributions from West Bengal, Madhya Pradesh, Andhra Pradesh, Odisha, and Chattisgarh (Anonymous, 2026) [1] . Rice cultivation is highly affected by major insect pests and diseases such as stem borer, leaf folder, brown planthopper, Bacterial leaf blight, rice blast, sheath blight, sheath rot and grain discoloration, which considerably reduce yield and grain quality (Savary et al., 2019) [15] . Effective management of these problems mainly depends on timely pesticide application (Prasad and Eizenga, 2008) [10] . Traditionally, pesticides are applied using knapsack sprayers, power sprayers and tractor-mounted sprayers. However, conventional spraying has challeges are like uneven spray coverage, poor canopy penetration, excessive pesticide wastage, spray drift, and high labour requirements (Lan and Chen, 2018) [8] . In rice ecosystems, spraying becomes more difficult during later crop stages because dense canopy and flooded field conditions obstruct the penetration of spray droplets into lower plant regions where diseases like sheath blight usually initiate.

In addition, manual spraying exposes workers directly to hazardous chemicals and increases environmental contamination through runoff and drift (Zhang et al., 2011) [20] . These limitations created the need for advanced and precision-based spraying technologies such as Unmanned Aerial Vehicles (UAVs) for efficient crop protection in rice. Unmanned Aerial Vehicles (UAVs) are commonly called agricultural drones emerged as an important precision agriculture technology for pesticide application to the farmers doorstep. UAVs can operate autonomously or through remote control and offer several advantages over conventional spraying methods including rapid spraying, uniform droplet distribution, reduced labour dependency, low water requirement, timely application and improved safety to applicators (Chen et al., 2020) [3] . Drone spraying also improves canopy penetration through rotor-induced downwash airflow, enabling better deposition of droplets on lower portions of rice plants. Studies reported that UAV spraying improves spray efficiency, reduces pesticide losses, and enhances pest and disease control even under difficult field conditions (Wang et al., 2019; Hu et al., 2024) [19, 7]. Recognizing the potential benefits of drone technology in agriculture, the Govt of India has actively promoted the adoption of agricultural drones through initiatives such as the Sub-Mission on Agricultural Mechanization (SMAM), and the Namo Drone Didi Scheme to encourage precision farming and modern crop management practices. Furthermore, Professor Jayashankar Telangana Agricultural University has developed Standard Operating Procedures (SOPs) for UAV-based pesticide application in major field crops including rice (Varma et al., 2022) [18] . Adjuvants are supplementary substances added to pesticide spray solutions to improve spray performance and pesticide efficiency (Bao et al., 2022) [2] . They include surfactants, spreaders, stickers, compatibility agents, anti-foaming agents and drift-control compounds. In UAV spraying systems, adjuvants play a major role in reducing surface tension, improving droplet spreading wettability, minimizing evaporation, reducing spray drift, and increasing deposition on rice leaves. Several studies demonstrated that tank-mix adjuvants significantly improve spray characteristics and biological efficacy of pesticides applied through drones (Ma et al., 2022) [9] . Research findings indicated that the addition of suitable adjuvants enhanced canopy coverage, droplet retention and pesticide utilization efficiency while reducing pesticide usage by nearly 20 per cent. Different adjuvants such as organosilicon surfactants, lecithin-based compounds, mineral oils, and plant essential oils were found effective in improving spray deposition and pest control efficiency in rice and other crops under UAV spraying conditions (He et al., 2021) [6] . Tank-mixing of insecticides and fungicides is increasingly practiced by farmers to reduce spraying frequency, labour costs and operational expenses while improving insect-pest and disease management efficiency. However, improper mixing of pesticides at high concentrations may lead to incompatibility problems such as sedimentation, foaming, flocculation, precipitation, nozzle blockage, uneven spray distribution, reduced control efficacy and phytotoxicity (Rajasekar and Mallapur, 2017) [12] . Therefore, evaluating the physical compatibility of pesticides with adjuvants under UAV spray concentrations is essential before field application.

The present experiment focuses on studying the compatibility of newer fungicides and insecticides with adjuvants such as Silwet Gold, SPREAD-X 180 and Stikker Plus under drone spraying concentration in rice. Since, very limited information is available under Indian conditions regarding pesticide-adjuvant combinations applied through UAVs systems, this investigation represents a pioneering and systematic effort toward the development of efficient, sustainable and precision-driven UAVs based pesticide application strategies for enhanced rice crop protection.

Materials and Methods

The physical compatibility of eight individual pesticides comprising of each four insecticides, fungicides and three adjuvants as presented in Table 1 along with their sixty-four (64) possible combinations, were evaluated under laboratory conditions through a jar compatibility test (14). The compatibility studies were carried out using pesticide concentrations recommended for drone (UAVs) sprayer. The pesticides and adjuvants selected for the investigation were chosen based on their broad-spectrum effectiveness, economic feasibility and commercial availability in the market.

The pesticides and adjuvants

The four insecticides studied are Isocycloseram

Preparation of drone spray concentrations

Drone spray concentrations were calculated by maintaining the recommended active ingredient dose per hectare while adjusting the pesticide concentration according to the lower spray volume used in UAVs spraying. A spray volume of 40 L ha⁻¹ was adopted for drone application (18). The recommended pesticide dose per hectare was recalculated to obtain the required concentration per litre of spray solution while ensuring the total active ingredient applied per hectare remained equivalent to the conventional recommended dose. All pesticide combinations were tested along with adjuvants at their respective drone spray concentrations. Silwet Gold was used at 0.33 mL L⁻¹, whereas SPREAD-X 180 and Stikker Plus were used at 0.5 mL L⁻¹ of water for evaluating their compatibility with pesticide mixtures under UAV spraying conditions.

Procedure for jar compatibility test

Water collected from the open well at the experimental site was used for preparation of all pesticide mixtures. A measured quantity of water was taken in a one-litre glass jar into which one insecticide and one fungicide were added at their respective drone spray doses. The pesticides were mixed according to the WALES mixing sequence suggested by (Suganthy et al., 2010) [16] wherein wet table powders (WP) and water dispersible granules (WDG) were added first, followed by suspension concentrates (SC) and flowables, and finally emulsifiable concentrates (EC) and soluble concentrates (SL). After addition of the pesticides, the adjuvants will be added, the volume was made up to one litre with water and the mixture was shaken thoroughly to ensure uniform mixing. From the prepared spray mixture, 100 mL of solution was transferred into a 100 mL calibrated knobbed measuring cylinder and kept undisturbed under laboratory conditions for 60 min. Observations on physical compatibility parameters such as foaming, sedimentation was recorded after 30 and 60 min of observation period. The compatibility of pesticide mixtures was assessed based on the absence or presence of these physical abnormalities.

pH measurement

The pH of individual insecticides, fungicides, adjuvants, and their combinations at drone spraying concentrations was measured using a digital p H meter. The recorded p H values were classified into different categories, such as acidic, neutral and alkaline according to the classification proposed.

Results and Discussion

The pesticides and adjuvants

The results of the present investigation on the physical compatibility of insecticide-fungicide combinations with adjuvants under UAV spraying conditions revealed that most of the tested combinations were physically stable and suitable for drone application in rice. In the jar compatibility test, the majority of the pesticide mixtures without adjuvants showed no visible foaming or sedimentation, indicating good compatibility under drone spraying concentration. Among the sixteen combinations tested, combinations involving Isocycloseram 18.1% SC + (Mefentrifluconazole 200 + Fluxapyroxad 200 g/l SC) and Novaluron + Emamectin benzoate + (Mefentrifluconazole 200 + Fluxapyroxad 200 g/l SC) recorded the slight sedimentation, whereas Spinetoram 11.7% SC combinations showed minor foaming and sedimentation (Table 2).The present findings were in agreement with the results reported by Raju et al., 2018 reported that chlorantraniliprole exhibited physical compatibility with the fungicides tricyclazole, hexaconazole and propiconazole, as no signs of sedimentation or foaming were observed in the tested mixtures at Taiwan sprayer application concentration. A few pesticide mixtures produced foaming under concentrated drone spray volumes, while most combinations remained physically stable (Ragiman et al., 2023) [11] . Similarly, (Georgia, 2019) [4] reported that the combinations of chlorantraniliprole with azoxystrobin and hexaconazole were both physically and chemically compatible. Further, (Goud et al., 2010) [5] stated that propiconazole when combined with insecticides such as indoxacarb and novaluron showed no foaming, while sedimentation values of 1.8 ml and nil, respectively, were recorded, which were within the permissible ISI limit of 2 ml per 100 ml. The addition of adjuvants influenced the compatibility behaviour of the spray mixtures. Among the adjuvants tested, Silwet Gold produced comparatively higher foaming, especially in combinations involving Mefentrifluconazole 200 + Fluxapyroxad 200 g/l SC, where foaming reached up to 5 ml. Spread-X 180 also caused moderate foaming and slight sedimentation in some combinations, while Stikker Plus exhibited comparatively better physical stability with very low foaming and sedimentation. However, severe precipitation or separation was not observed in any treatment. The increased foaming observed with Silwet Gold might be due to its surfactant properties under concentrated UAV spray conditions (Table 2 andFig

pH Measurement

The pH studies revealed that the individual pesticides, adjuvants and their combinations remained within neutral to slightly alkaline range. The p H of individual chemicals varied from 7. 16 showed slightly alkaline nature. Spread-X 180 exhibited comparatively higher p H due to its alkaline nature, while Silwet Gold and Stikker Plus maintained relatively stable p H conditions. Importantly, none of the combinations showed extreme acidic or highly alkaline conditions, which indicates that favourable conditions for pesticide stability and bioefficacy Table 2. Similar findings were reported by (Ragiman et al., 2023) [11] who stated that certain pesticide mixtures at drone spraying concentration showed increased foaming due to higher chemical concentration in lowvolume applications. P H analysis of pesticide formulations and their combinations used in rice crop protection revealed that most treatments maintained a nearly neutral reaction, whereas cartap hydrochloride 50% SP exhibited comparatively higher acidity along with slight pH variations in a few pesticide combinations (Supriya et al., 2024) [17] . The absence of extreme p H conditions also corresponded with minimal sedimentation observed during jar compatibility testing, suggesting good chemical stability of the spray mixtures applied through drones. The present findings are also in agreement with (Rajasekar and Mallapur, 2017) [12] who reported that physical compatibility of pesticide mixtures is closely associated with maintaining favourable p H conditions. Overall, the results demonstrated that most insecticidefungicide combinations tested in the present study were physically and chemically compatible under UAV spraying conditions. The compatible mixtures exhibited good stability with negligible foaming and sedimentation and maintained favourable p H levels suitable for drone-based low-volume spraying. The study further indicated that proper selection of adjuvants is essential to improve spray uniformity and compatibility under UAV applications. These findings support the safe and effective use of compatible pesticide mixtures for precision crop protection in rice cultivation.

Conclusion

The study concluded that most insecticide-fungicide combinations tested under UAV spraying were physically and chemically compatible. Jar tests showed negligible foaming and sedimentation, indicating suitability for lowvolume drone spraying tank mixing of pesticide with adjuvants. The p H of pesticides, adjuvants, and mixtures remained neutral to slightly alkaline, supporting stability. Among adjuvants, Stikker Plus showed better compatibility, while Silwet Gold produced relatively higher foaming. Overall, selected combinations were safely and effectively used through UAVs for precise and sustainable insect pest and disease management in rice.

Future Scope

The findings of the present investigation and earlier studies clearly demonstrated that the incorporation of suitable tankmix adjuvants in UAV-based pesticide application systems can considerably enhance spray retention, wetting, spreading behaviour, and deposition efficiency on plant surfaces, thereby improving pesticide utilization efficiency even at reduced pesticide dosages. The improved physicochemical characteristics achieved through adjuvant incorporation indicated the possibility of maintaining effective pest and disease management while reducing the quantity of pesticide applied, which is highly important for sustainable agriculture and environmental safety. Future research should therefore focus on evaluating the extent of pesticide dosage reduction possible under different UAV spraying conditions without compromising biological efficacy. Detailed investigations on optimized adjuvantpesticide combinations, spray volume, droplet spectrum, nozzle type, and flight parameters are essential to achieve maximum target coverage with minimum chemical input. In addition, large-scale field studies under diverse agroclimatic conditions are necessary to assess spray deposition, drift reduction, phytotoxicity, residue dynamics and economic feasibility associated with reduced-dose UAV spraying. The adoption of efficient adjuvant-assisted lowdose pesticide application strategies can significantly reduce chemical wastage, production costs, labour dependency and environmental contamination while promoting precision, sustainability and eco-friendly crop protection practices.

Acknowledgement

The authors are highly thankful to Professor Jayashankar Telangana Agricultural University and the Agricultural Research Institute, Rice Research Unit for providing the necessary infrastructural facilities, technical support, and financial assistance for conducting this research work.

Disclaimer (Artificial intelligence)

Author(s) hereby declares that NO generative AI technologies such as Large Language Models (ChatGPT, COPILOT, etc.) and text-to-image generators have been used during the writing or editing of this manuscript.

Competing Interests

The authors declare that they have no competing interests.

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