Next Article in Journal
Soil Amendments, Physicochemical Properties, and Metal Accumulation in Soils and Vegetables of Volcanic and Non-Volcanic Regions in Ecuador
Next Article in Special Issue
Integrating Stride Attention and Cross-Modality Fusion for UAV-Based Detection of Drought, Pest, and Disease Stress in Croplands
Previous Article in Journal
The Projected Effects of Climate Change on the Potential Distribution of Planococcus minor Based on Ensemble Species Distribution Models
Previous Article in Special Issue
A Reinforcement Learning-Driven UAV-Based Smart Agriculture System for Extreme Weather Prediction
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 15
Issue 5
10.3390/agronomy15051164
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Review of Active Plant Frost Protection Equipment and Technologies: Current Status, Challenges, and Future Prospects

by
Tianhong Liu
1,2,†,
Songchao Zhang
1,2,*,†,
Tao Sun
1,2,
Cong Ma
3 and
Xinyu Xue
1,2,*
1
Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China
2
Sino-USA Pesticide Application Technology Cooperative Laboratory, Nanjing 210014, China
3
Ningxia Academy of Agricultural and Forestry Sciences, Institute of Agricultural Economics and Information Technology, Yinchuan 750002, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(5), 1164; https://doi.org/10.3390/agronomy15051164
Submission received: 11 April 2025 / Revised: 6 May 2025 / Accepted: 7 May 2025 / Published: 10 May 2025
(This article belongs to the Special Issue New Trends in Agricultural UAV Application—2nd Edition)
Browse Figures
Versions Notes

Abstract

:
Frost poses a significant threat to agricultural production, leading to reduced crop yields and deterioration in quality. This review systematically provides an overview of the types and causes of plant frost, and delves into the principles, research progress, and application status of three key active frost protection (FP) technologies: air disturbance, sprinkler irrigation, and heating. It also scrutinizes the challenges faced by current FP equipment, such as high costs, complex maintenance, and noise pollution. Air disturbance technology utilizes fans to mix upper and lower air layers, increasing the canopy temperature, with research focusing on fan optimization and unmanned aerial vehicle (UAV) application. Sprinkler irrigation technology releases latent heat through water freezing, with research centering on water saving and automation. Heating technology directly supplies heat, with attention on heat source optimization and mobile heating strategies. Finally, this review outlines the development trends of plant FP equipment and technologies, highlighting the promising application prospects of agricultural UAVs in FP, which can have multi-purpose use and effectively reduce costs.

1. Introduction

Frost damage poses a persistent and economically significant threat to agricultural production in various regions worldwide, particularly those experiencing seasonal temperature fluctuations in temperate zones during critical spring and autumn periods, as well as causing occasional damage in subtropical areas or at higher altitudes [1,2,3,4]. This vulnerability is especially pronounced during critical crop developmental phases, such as bud break, flowering, and early fruit development, where even brief exposure to sub-zero temperatures can result in irreversible cellular damage and tissue necrosis, leading to substantial yield reductions and quality degradation across a wide range of crops [5,6,7]. The increasing frequency and intensity of extreme weather events, including unseasonal frosts, partly attributable to climate change, heighten the risk of frost damage and underscore the growing need for effective frost protection (FP) strategies [8,9,10,11].
A spectrum of FP methods exist, broadly classifiable as passive or active. Passive methods, such as careful site selection, choosing frost-tolerant cultivars, and appropriate soil management practices (e.g., maintaining moist, compact soil), can offer a foundational degree of protection by minimizing risk or moderating temperature drops [12]. However, the efficacy of passive strategies alone is often limited, especially during severe radiative frosts or unpredictable advective freeze events, necessitating the implementation of active interventions [13]. Beyond passive approaches, several active or alternative FP techniques have been explored. These include the application of anti-transpirants to reduce evaporative cooling [14,15], the use of insulating foams or protective covers (like row covers or tunnels) to trap heat [16], and the application of biostimulants or cryoprotectants intended to enhance the plant’s intrinsic tolerance to freezing stress. While these alternative methods have specific applications, this review focuses specifically on the three most widely adopted and researched active, equipment-based FP technologies for field and orchard scale protection: air disturbance, sprinkler irrigation, and heating. This focus is justified by their significant commercial implementation, the distinct physical principles they employ, and the substantial body of research dedicated to optimizing their associated equipment and operational strategies. Air disturbance utilizes fans or helicopters to disrupt temperature inversions by mixing warmer upper-layer air with colder near-ground air [17,18,19,20]; sprinkler irrigation leverages the release of latent heat as water freezes on plant surfaces, maintaining tissue temperatures near 0 °C [21,22]; and heating involves the direct supply of thermal energy using various heat sources [23,24].
A mounting imperative exists for research endeavors to concentrate on enhancing the efficiency, cost-effectiveness, and environmental sustainability of prevailing FP equipment; such efforts should aspire to minimize energy and water consumption, whilst concomitantly reducing noise and air pollution [25,26]. Moreover, the incorporation of innovative technologies, such as unmanned aerial vehicles (UAVs) and advanced sensor networks, presents a number of advantageous prospects for the formulation of FP strategies that are more precise, adaptive, and data-driven, enabling targeted interventions and minimizing resource waste [27,28,29,30]. Finally, it is vital to understand the synergistic effects of combining different FP methods and developing integrated approaches tailored to specific crop types, micro-climates, and economic constraints in order to enhance the resilience of agricultural systems to frost damage. The complexities of different types of frost events also require different strategies, and more work needs to be carried out to optimize systems for each. This review aims to address these knowledge gaps by providing a comprehensive overview of advances in plant FP equipment, analyzing the principles, research progress, and application status of air disturbance, sprinkler irrigation, and heating technologies, and highlighting the challenges and opportunities for future research and development, with a particular emphasis on the potential of UAVs to revolutionize FP practices (Figure 1).

2. Causes of Frost Formation

Frost refers to white crystals formed when the temperature of the ground or objects on the ground drops to 0 °C or slightly below 0 °C, causing water vapor in the air to condense, as shown in Figure 2. The formation of frost is a dynamic process influenced by various environmental factors, including air temperature, humidity, wind speed, and geographical conditions. It is most common between late autumn and early spring, with susceptibility varying significantly based on latitude, elevation, proximity to large water bodies (which moderate the temperature), and local topography [31]. On clear, calm nights with radiative cooling, the temperature can drop below 0 °C, leading to frost formation [32]. The formation of frost occurs mainly due to the radiative cooling process among the soil, plants, and the atmosphere [33]. During the day, under short-wave radiation, the canopy between plants and the atmosphere undergoes intense photosynthesis and transpiration [34]. Conversely, at night, long-wave radiation precipitates a substantial decline in near-ground temperature, resulting in a temperature inversion, whereby the temperature below the canopy is approximately 3 °C lower than that above the canopy. Due to the low near-ground temperature—which is often exacerbated at higher elevations due to generally lower temperatures, and potentially in valleys or depressions, where cold air pools due to nocturnal air drainage forming ‘frost pockets’—and if sufficient water vapor is present in the air (humidity is high enough), such that the surface temperature drops to or below the frost point (the temperature at which air becomes saturated with respect to ice), this water vapor will desublimate (condense directly from gas to solid) onto surfaces, particularly those with poor thermal conductivity, forming white frost crystals. If there is insufficient moisture in the air, visible white frost will not form even when temperatures drop below 0 °C, but damaging ‘black frost’ conditions may still occur [35]. If there are clouds in the night sky, frost formation will be delayed or even prevented as clouds weaken the long-wave radiation emitted from the soil and vegetation near the ground. Additionally, wind speed significantly impacts frost formation. A gentle breeze promotes frost formation by moving water vapor over a cold surface, while high winds hinder frost formation by rapidly moving air and mixing upper and lower air layers. Generally, frost does not form easily when the wind speed reaches level three or above. Therefore, frost usually forms when there are clear, gentle breezes or during windless nights in the cold season.

3. Air Disturbance Technology for Plant FP

3.1. Principle of Air Disturbance Technology for Frost Protection

Air disturbance technology utilizes the inversion phenomenon during frost nights, employing FP fans to force warmer upper-layer air into the crop canopy, thereby elevating the canopy air temperature above the critical frost damage temperature threshold (shown in Figure 3). This technology contributes to environmental pollution mitigation, facilitates the mechanization and automated control of FP equipment, and offers enhanced operational efficiency under strong inversion conditions. However, under weak inversion conditions during frost nights, the technology encounters challenges, including diminished FP efficacy and constrained operational capacity. The primary equipment employed for the prevention of frost includes elevated FP fans, suction and discharge fans, and helicopters. This technology is currently the most widely used mechanical FP method on a global scale.

3.2. Research Status of Frost Prevention Fans

Antonio C. Ribeiro et al. [19] tested the effect of wind turbines on FP in apple orchards under different micro-climatic conditions over 11 frost nights in 1999 and 2000. They found that wind turbines were more effective under strong inversion, with significant temperature increases and flower damage reduction. In 1999, flower frost damage was reduced by 60%, and it was reduced by 37% in 2000. This study provided important empirical data for the application of wind turbines in FP, improving crop yield and quality.
Mark C. Battany et al. [17] studied the effectiveness of upward-suction and discharge fans (shown in Figure 4) in vineyard FP over 12 spring frost nights in 2010 and 2011, assessing their effectiveness against those of traditional fans. The study found that traditional fans were more effective in strong inversions, particularly at the height of the grapevines (about 1.1 m). In strong inversions, upward-suction fans exhibited limited effectiveness, and there was a possibility that they could reduce temperatures in weak inversions.
Kensuke Kimura et al. [36] investigated the thermal effect of oscillating anti-freezing fans in tea fields, observing that fan operation was more effective under conditions of strong inversion. They revealed the dynamic influence of fan operation on tea leaf thermal balance through time–space analysis, demonstrating that fan operation significantly improved tea leaf thermal balance and reduced the risk of frost damage.
Vincent W.J. Heusinkveld et al. [18] evaluated the relationship between wind turbine performance and main physical processes during frost events via field experiments (shown in Figure 5) and numerical simulations. The results indicated that the temperature response was highly dependent on radial distance and height from the turbines, with the turbines achieving a temperature increase within a height of 1 m, covering 3–5 hectares. Furthermore, a slower turbine rotation time (3–6 min) led to a significant increase in the affected area, while the temperature increase remained relatively constant. The optimal temperature increase was found to occur when the turbine horizontal tilt angle was between 8 and 16 degrees, aiding in the optimization of wind turbine design and operation for effective fruit tree FP.
Judith Boekee et al. [20] investigated the role of fans in FP, with a particular focus on orchards. The study revealed that fans play a dual role in FP, functioning by two distinct mechanisms. Firstly, they facilitate the mixing of warm air from the upper layer into the canopy layer, thereby regulating the temperature of leaves. Secondly, they enhance wind speed, thereby eroding the leaf boundary layer and promoting heat exchange between the leaves and the air. However, the leaf temperature lags behind the air temperature due to stronger leaf radiation cooling, and the petals and branches have different heat capacities, leading to different temperature changes. The study indicates that fan operation exerts a substantial influence on FP; nevertheless, the prediction of frost damage must take into account discrepancies in plant and air temperature.
In China, some scholars have also developed FP machines. Hu et al. [37] designed and tested a high-altitude fan FP system for tea gardens, demonstrating the efficacy of a 3 kW system in covering an area of 1000 m2. At temperatures as low as −4 °C, the system increased the temperature of the tea tree canopy by 4 °C, thus preventing frost damage. Successively, they studied the effect of anti-freezing machines in tea gardens over different time scales, obtained the optimal activation and shutdown times, optimized the fan impellers for anti-freezing, and conducted field trials to study the airflow disturbance and temperature changes of anti-freezing fans in tea gardens [38,39,40,41]. In 2023, they designed and tested a noise-reduction structure for the arc-shaped blade of the FP fan [42].
Yin Xianzhi et al. [43] assessed the FP effect of large-scale orchard FP machines based on comparative test data during a severe cooling process from 19 to 21 October 2013. The study revealed that a high-altitude FP machine, with a power output of 120 kW, an elevation of 8.5 m, and wind blades measuring 6 m in diameter, effectively disturbed and mixed upper and lower air layers. This disturbance resulted in the elimination of inversion within the protected area, a significant increase in near-ground temperature, and effective FP formation. The effective protection range of each FP machine was found to be 20–100 m horizontally, and its effective protection area was determined to be 1.73–3.07 hectares.

3.3. Research Status of Using UAVs for Frost Prevention

The principle of UAV FP involves the generation of strong downward air currents via its rotors. Computational fluid dynamics (CFD) simulations, employing methods like Reynolds-averaged Navier–Stokes (RANS) with turbulence models or the Lattice Boltzmann Method (LBM) [44,45], reveal that this downwash initially forms spiral vortices directly below the rotors. As depicted in analyses like Figure 6, these structures evolve, particularly during forward flight, into inclined horseshoe vortices whose angle increases with flight velocity. The purpose of this engineered airflow is to disturb the stable, stratified air typical of radiation frost nights, mixing warmer air from above the inversion layer with colder air near the ground, thereby breaking the inversion and preventing frost formation, as shown in Figure 7.
CFD studies quantify this downwash, showing that the maximum velocities can reach 13–15 m/s and the vorticity can reach over 500 s−1 near the rotors, depending on the rotor speed and flight conditions. However, this high intensity is concentrated, typically within 1–1.5 m below the UAV, and the Z-directional (downward) velocity and its coverage area attenuate with increasing distance from the rotor. The penetration depth is critical for FP; simulations indicate that while higher rotor speeds increase initial downwash intensity, very high forward-flight speeds can excessively tilt the vortices, hindering the airflow’s penetration to the canopy base or ground level. Therefore, optimizing operational parameters like flight height and velocity is crucial to maximize the effective mixing volume where frost protection is needed [44].
This method offers potentially wide coverage, significant effectiveness, and high flexibility. However, it faces challenges such as operational costs, complexity, and sensitivity to flight conditions. While UAVs show good prospects for large-scale orchard FP, cost-effectiveness and operational factors require comprehensive consideration. With the rapid development of China’s agricultural UAV industry, increasingly low-cost, easy-to-operate, intelligent UAVs hold promise for wider adoption in plant FP applications.
Hu et al. [46] conducted a trial of FP in tea gardens using a UAV in 2012. They tested the influence of the helicopter on the distribution of the near-ground airflow at different hovering heights, and conducted a trial to assess the FP effects in tea gardens (Figure 8) with different combinations of flight heights, speeds, and time intervals. The experimental results showed that within a hovering height range of 5 to 10 m, the UAV had the greatest disturbance effect on the airflow below the ground surface outside the rotor of the UAV, but the disturbance effect weakened as the hovering height increased. The best FP effect was achieved under the combination of a flight height of 5 m, a flight speed of 6 m/s, and a flight time interval of 30 min, resulting in a 3.83 °C temperature increase in the tea tree canopy layer. This study underscores the potential of extending the application of agriculture UAVs to plant FP, particularly in hilly regions.
In addition, Hu et al. [30] also investigated the optimal flight parameters of UAVs for FP in tea plantations in 2015. Through field experiments, they analyzed the effects of flight altitude, speed, and interval on the disturbance of airflow and temperature increase around the tea tree canopy layer. It was found that when the flight speed was constant, the wind speed around the tea tree canopy layer decreased with an increase in flight altitude. A multivariate linear relationship was identified between temperature increase and flight parameters, with the order of influence of flight parameters on FP being flight interval, followed by flight altitude, followed by flight speed. The optimal flight parameter combination was determined to be a flight altitude of 4.0 m, a flight speed of 6.0 m/s, and a flight interval of 20 min, with the air temperature around the tea tree canopy layer increasing by 1.6 °C.
Qiao et al. [29] utilized a CFD simulation and field tests to verify the FP reliability of the DJI T40 agricultural UAV (Shenzhen, China) in peach orchards (Figure 9). The results showed that when the UAV hovered 6 m above the ground with a rotor speed of 1000 rpm, the temperatures at different height levels eventually stabilized, with this process being completed within 20 s. The field tests also revealed that when the peach trees reached the critical frost temperature during the flowering period, the intervention of the UAV could significantly increase the temperature in the near-ground surface layer, with an increase range of 2.5 °C to 3 °C, providing a reliable method to alleviate frost damage.
Numerous studies have investigated the efficacy of various air disturbance methods for plant frost protection (FP), encompassing conventional downward-blowing wind machines, upward-suction fans, oscillating fans, specialized high-altitude fans, and, increasingly, unmanned aerial vehicles (UAVs). Research provides valuable insights into the performance of these systems under different conditions. However, the reported effectiveness varies significantly depending on the specific technology employed, operational parameters (such as fan speed, rotation time, tilt angle, UAV flight height, speed, and interval), prevailing meteorological conditions (especially inversion strength and wind drift), the type of crop being protected, and the geographical location. For instance, effectiveness is often measured differently, ranging from measuring direct temperature increases (°C) and the protected area (ha or m2) to reductions in flower or tissue damage (%). To better understand and compare the quantitative outcomes and applicability of these diverse air disturbance approaches, a summary of key findings, including the method, measured effectiveness, study location, and plant type, is presented in Table 1.

4. Sprinkler Irrigation for Frost Protection

4.1. Principle of Sprinkler Irrigation for Frost Protection

The principle of FP by sprinkler irrigation involves the projection of a fine water mist to create a barrier against frost. The process entails the spraying of water in fine droplets, which subsequently freezes on the surfaces of plants. This results in the release of latent heat of condensation, thereby increasing the local temperature and reducing the likelihood of frost formation. This method also ensures adequate moisture in the ground and the surrounding area, contributing to enhanced FP. This technique finds extensive application in agricultural settings, particularly in the cultivation of frost-resistant plants, such as fruit trees. However, a significant potential drawback of this method, especially with continuous or excessive application rates, is the accumulation of heavy ice loads on the plants. The weight of this ice can cause physical damage, such as limb breakage, particularly on young or structurally weak trees or plants. Therefore, careful management of application rates and cycling strategies is crucial not only for effective FP and water conservation, but also to minimize the risk of ice-load damage [21]. A schematic diagram of sprinkler irrigation for FP is shown in Figure 10.

4.2. Research Status of Sprinkler Irrigation for Frost Prevention

The investigation into sprinkler FP systems was initiated by foreign scholars in the 1980s. As early as 1980, P. J. C. Hamer [47] found that traditional sprinkler irrigation systems usually supplied water at a fixed rate and were designed for the most severe frost conditions, leading to excessive water consumption in most cases. Therefore, he designed an automatic control system, which automatically adjusted the water supply rate according to the simulated temperature of the fruit tree buds. During the spring frost period, tests showed that the system provided complete FP, while using only half the normal water consumption. In 1986, some research was conducted focusing on the thermal balance of apple tree buds and flowers during FP processes, especially the water consumption required for FP via top sprinkler irrigation. By measuring the temperature changes of apple bud tips during natural and simulated frost periods, and then comparing them with heat transfer theory prediction results, it was found that in the early stage of FP, partial wetting of buds and ice accumulation altered both the bud size and the heat transfer coefficient, thus affecting thermal balance calculation. The final thermal balance equation, therefore, took these factors into consideration, enabling accurate calculation of the water consumption of sprinkler irrigation systems under different environmental conditions.
J. Barfield et al. [48] proposed a formula accounting for humidity in order to predict the rate of irrigation by means of spraying. It is important to note that neglecting humidity can result in significant shortcomings in the design of irrigation systems. By calculating the energy loss of wet leaves in order to maintain the leaf temperature at 0 °C under conditions of low temperature, experimental results demonstrated that neglecting humidity could lead to erroneous system design, with an error of up to 28%. Mark Rieger [49] conducted a series of experiments on the efficacy of micro-sprinkler irrigation systems, both in relation to their position beneath and above the tree canopy. The study revealed that the micro-sprinkler irrigation system positioned above the tree canopy could effectively maintain the temperature of peach blossom buds above the lethal point during the spring frost period. This system demonstrated a 50% to 87% reduction in water and energy consumption when compared to the traditional overhead sprinkler irrigation system. In a study conducted by A. B. Koc et al. [50], an automatic circulating sprinkler irrigation system was employed for the purpose of FP for apple buds. The results obtained from this study indicated that the average water consumption was reduced by approximately 72% in three frost events when compared with traditional continuous sprinkler irrigation. Ali Asghar Ghaemi et al. [22] used an automatic sprinkler irrigation system based on tree and air humidity detection by thermistors, and the irrigation water consumption rate was determined using Frostpro software [51] per energy balance. The experimental results revealed that the peach blossom temperature was 2.5 °C higher than in the control group, and the peach blossom mortality rate was 29.5% lower after a 54.3% reduction in water consumption. ISSA et al. [52] developed a simplified model to simulate the solidification process of water film on a single fruit surface. They determined the irrigation frequency to ensure that the fruit surface was always surrounded by water film, thereby preventing the fruit temperature from dropping below 0 °C. Faith Olszewski et al. [53] conducted a study on the utilization of automatic cyclic sprinkler irrigation systems in the context of spring FP. Conventional FP typically involves the continuous operation of an irrigation pump throughout the night until the temperature exceeds the critical level for plant cultivation. The research team conducted a three-year monitoring study and conducted a comparative analysis of the effects of cyclic and traditional spring frost irrigation on cranberry bud damage, crop yield, and water consumption. The results obtained from this study indicated that the implementation of cyclic irrigation methods resulted in a significant reduction in seasonal water consumption, ranging from 33% to 80%, with a water-saving range of 113 to 198 mm. Furthermore, the study revealed that the yield of cranberry buds was notably higher as a result of the cyclic irrigation method compared to the traditional spring FP method.
In 1980, the Ningxia Academy of Agricultural and Forestry Sciences conducted a study on the effect of irrigation for FP in apple orchards [54]. The experiment found that conducting ground irrigation before the onset of frost or before the full-bloom period could significantly increase the air temperature and humidity, thereby reducing the damage caused by frost to apple flower clusters. After irrigation, the soil moisture increased and evaporation was intense, which helped to buffer the cooling process of frost. It was evident that the implementation of irrigation resulted in a reduction in soil temperature. However, the protective effect that this practice provides against frost is noteworthy. In a study by Hu et al. [55], an effective method for preventing frost damage to tea plants was proposed. This involved continuous spraying of water at a rate of 2–4 mm/h during frost nights. The sprinkler system was programmed to cease operation after sunrise, at which time point the temperature of the tea tree canopy layer increased by 2.2 °C within one hour. In contrast, the temperature in the non-irrigated area rose by 4.8 °C, which was hypothesized to cause frost damage to the tea plants. Pan et al. [56] investigated the dynamic changes in water and ice storage in tea trees under sprinkler irrigation for FP and their influencing factors. The study found that under non-freezing conditions, the water and ice storage in tea trees went through three stages: accumulation, dynamic equilibrium, and drying, while under freezing conditions, the ice storage went through four stages: accumulation, retention, melting, loss, and drying. The study further revealed that the water and ice storage capacity of the micro-sprinkler system was 1.2 and 2.0 times that of the rocker-arm sprinkler under equivalent irrigation pressure conditions, respectively. The duration of sprinkler irrigation exhibited no significant impact on the maximum water storage; however, the maximum ice storage demonstrated a substantial increase with an increase in the duration of sprinkler irrigation. This study provides a foundational basis for the optimization of sprinkler irrigation parameters, the enhancement of FP efficacy, and the realization of precise sprinkler irrigation.
Sprinkler irrigation systems include conventional continuous systems, automated cycled or pulsed applications, under- and over-tree micro-sprinklers, and systems employing sophisticated control logic based on temperature, humidity, or energy balance models. However, the reported effectiveness varies considerably depending on the specific system design, control strategy, application rate, prevailing environmental conditions such as humidity and wind, crops being protected, and study location. Effectiveness is quantified through diverse metrics, including direct temperature maintenance (°C), reduction in tissue damage (%), seasonal water savings (mm or %), and impacts on crop yield. To facilitate a clearer understanding and comparison of the quantitative outcomes and applicability of these diverse sprinkler irrigation techniques, a summary of key findings, including the method, measured effectiveness, study location, and plant type, is presented in Table 2.

5. Anti-Frost Heating System

5.1. Principle of Anti-Frost Heating

Anti-frost heating employs heating devices (e.g., electric heating wires, glass) to maintain the surface temperature above the frost point during frost periods, thereby preventing frost formation. Early anti-frost heating primarily relied on combustion furnaces, which were distributed uniformly within orchards to protect fruit trees from radiant frost, as shown in Figure 11. However, these furnaces frequently burned incompletely, resulting in substantial smoke emissions and subsequent deterioration in orchard air quality. Furthermore, the necessity for a substantial number of furnaces to achieve effective FP can result in increased costs.

5.2. Research Status of Anti-Frost Heating Technology

Ercan Atam et al. [23] proposed a horticultural FP system that integrates hybrid green energy, combining renewable and non-renewable energy sources with active heaters. A schematic diagram of this system is shown in Figure 12. The researchers developed a multi-objective robust optimization method to enhance the system design, encompassing the distribution of active heaters and the layout of thermal energy networks in extensive orchards. The studies demonstrated that this method reduced the total pipeline length by 24.13% and enhanced the heating efficacy by 54.29% in comparison with heuristic-based methods.
Wu et al. [24] designed and optimized an intelligent orchard FP machine (schematic diagram shown in Figure 13) for mountainous areas, integrating an FP fan with a heating system. The heating system utilized electric heating wires to warm air, which was drawn into a heating chamber by the fan and rapidly heated. The heated air was then expelled through rotating nozzles to create an FP zone. The air temperature could be adjusted by selecting electric heating wires of different lengths and diameters. Experimental evidence demonstrated that the optimized machine was capable of covering a 10 m radius in orchards and adapting dynamically to environmental changes, even at wind speeds of up to 2 m/s. Additionally, this design integrated multiple FP machines powered by solar panels, which worked collaboratively, improving the overall efficiency, enhancing economic benefits, and reducing energy consumption.
Hua et al. [57] conducted thermal transfer modeling for an FP heating system in apple orchards. They developed a 3D computational fluid dynamics model to predict the temperature distribution of two air heaters in the orchard under different wind conditions and fixed heating layouts. The results showed that positioning heaters in the windward direction offered greater protection to the tree canopy volume compared to the downwind direction. Furthermore, they also simulated the mobile heating situation and compared it with three fixed heating situations. The simulation demonstrated that mobile heating increased the percentage of protected tree canopies by 1180.0% compared to heaters placed at one end of the tree row, and by 141.5% compared to fixed heating at the middle and other end of the tree row. Consequently, the utilization of mobile heating strategies was recommended for enhanced orchard FP. They also developed a dynamic heating path planning method based on an accurate heating strategy. Using multiple heaters for precise heating, they improved the A-Star path planning algorithm, combined with linear programming and conflict search methods to generate optimal paths. Compared with the traditional fixed heating and mobile heating strategies, the accurate heating strategy significantly reduced the number of heaters by 96.8% and 85.9%, with the improved algorithm showing advantages in path cost and computation time reduction [58]. Figure 14 shows the mobile heating system used for the experiments in the orchard.
While early methods, like combustion furnaces, have known drawbacks, significant research has advanced cleaner, more efficient, and automated heating approaches. These include hybrid green energy systems with optimized heater distribution, intelligent self-heating electric machines, fixed forced-air heaters with different layouts, and mobile heating strategies involving path-planned UGVs for precision application. However, the reported effectiveness varies considerably depending on the specific system design (e.g., fixed vs. mobile, energy source), control strategy (e.g., optimized layout, path planning), operational parameters, prevailing environmental conditions (like wind), crop being protected, and study setting (field vs. simulation). Effectiveness is quantified through diverse metrics, including enhanced heating efficacy (%), protected radius (m) or Volume Percentage of Protected Canopy (VPPC) (%), reductions in infrastructure or heater numbers (%), and improvements in operational costs or computational time. To facilitate a clearer understanding and comparison of the quantitative outcomes and applicability of these diverse heating techniques, a summary of key findings, including the method, measured or simulated effectiveness, study setting, and plant type, is presented in Table 3.

6. Crop Frost Protection Options

Although the occurrence of extreme weather conditions around the globe has become more frequent in recent years, crop FP is still needed and continues to be used during crop production. By summarizing and outlining the characteristics of the different FP techniques and equipment mentioned above, we can obtain the advantages and shortcomings of each FP method, in order to guide the appropriate selection of FP methods and approaches in agricultural production.
Despite their high initial construction costs, wind turbine systems demonstrate low operating costs, a long lifespan, and multiple uses, making them particularly beneficial for large orchards characterized by strong inversion layers. Helicopter systems provide extensive coverage and do not necessitate fixed facilities, but they incur relative high single-operation costs, and are thus suitable only for sudden and extreme frost emergencies. Sprinkler systems require a relatively high initial investment, but offer the advantage of continuous operation with minimal water and electricity requirements; this makes them suitable for small- and medium-sized farms with sufficient water resources and the ability to prevent soil saturation. Heating systems have low initial costs, but high energy consumption due to their reliance on fuel and natural gas, resulting in rapid heat loss. These systems are therefore only recommended for local, short-term heating in agricultural facilities. In summary, wind turbine systems should be prioritized for long-term protection of orchards and large fields. It is recognized that the agricultural industry has the capacity to combine cover and small heating systems. In addition, sprinkler and UAV systems can serve as complementary solutions for resource-adaptive areas and emergencies, respectively. Technological adaptation and cost recovery can significantly improve the economic performance of FP measures, thereby reducing agricultural disaster losses.

7. Discussion

Air disturbance technology, sprinkler irrigation technology, heating systems, and the other methods summarized above have each been applied for frost protection in crop production. With regard to hot and cold air disturbance in wind fields, there have been fewer applications of UAVs in previous research, mainly due to the fact that earlier agricultural UAVs were expensive, difficult to operate, and less intelligent, resulting in a higher cost of a single FP application.
Agricultural UAVs have developed very rapidly in China. With different airborne mission equipment, UAVs can execute aerial spraying [59,60], remote sensing [61,62,63], supplementary pollination [64,65], aerial seeding [66], etc. With the advancement of technologies such as real-time kinematic high-precision positioning, automatic navigation, flight control, and active obstacle avoidance, the safety and accuracy of UAVs have been highly improved [67,68]. Due to their ability to efficiently perturb the inversion layer and quickly respond to sudden frost events, UAVs are expected to become a core FP tool for large-scale orchards and facility agriculture. As China’s agricultural UAV industry chain matures gradually, the cost of the equipment will continue to decline, driving its popularity in small- and medium-sized farms. In addition, the integration of 5G network and IoT technology will support the linkage of UAVs and ground sensors to build an ‘air–ground integrated’ intelligent FP network. This involves ground sensors monitoring conditions, while UAVs act as both intervention tools (generating downwash) and mobile communication hubs. For instance, early work demonstrated a system where a UAV carrying a mobile communication node flew over sparse Wireless Sensor Network (WSN) clusters deployed in vineyards for real-time frost monitoring. The UAV collected sensor data and relayed them via GPRS/SMS to a base station, overcoming communication limitations across fragmented parcels [69]. This type of integrated network architecture enables timely, spatially aware frost alerts and potentially automated activation of FP measures based on real-time ground data, paving the way for all-weather, fully automatic protection.
Therefore, it is believed that the use of agricultural UAVs for crop FP in China and the promotion of Chinese-made agricultural UAVs are very promising. In terms of the FP effectiveness of UAVs, some researchers [29,30,46] have carried out relevant studies, proving that it is feasible for agricultural UAVs to carry out FP operations, which, in previous scientific studies, were just limited by the technical level of UAVs at the time. In terms of the technological development level of agricultural UAV technology, UAVs could realize autonomous takeoff and landing, achieve centimeter-level flight route accuracy, and imitate ground flight and autonomous obstacle avoidance with the assistance of a dedicated UAV flight control system that is fully capable of ensuring the safety of super-visual flight and simple operation [70,71,72]. Taking the development of agricultural UAVs in China as a representative example, Shenzhen DJI Innovation Technology Co., Ltd. (Shenzhen, China) [https://ag.dji.com/] and Guangzhou XAG Technology Co., Ltd. (Guangzhou, China) [https://www.xag.cn/] have produced the latest large-load T100 and P150pro agricultural UAVs, with a maximum flight speed of 13.8 m/s, a flight altitude of 30 m, an endurance of 40 min, and a rated load of 75 kg. The cost comparison between conventional frost protection methods and UAV frost protection is summarized in Table 4.
The authors believe that agricultural UAVs have significant potential in the field of FP in crop production, but further research is still needed in several areas to achieve better results in this domain. Firstly, in order to effectively disrupt the atmospheric inversion layer, studies on the flight parameters and rotor disturbance airflow of agricultural UAVs are necessary. These studies can be conducted using computational fluid dynamics (CFD) simulations or smoke test methods. Secondly, considering various crops, like tea plantations, apple orchards and pear orchards, etc., the effects of different canopy structures and densities, leaf shapes and sizes, pore distributions, and other parameters on the obstruction, rebound, and transmission of perturbed airflow need to be clarified to elucidate the efficiency of hot and cold air exchange achieved by agricultural UAVs in FP operations for different crops. Finally, the warming effect should be evaluated, taking into account anti-frost flight parameters, operating time, operating costs, energy (battery energy) input, and other factors. The goal is to optimize the operation parameters of agricultural UAVs, taking into account crop characteristics and the timing of frost events, to develop an effective anti-frost operation mode, which would facilitate the broader application of agricultural UAVs in FP.

Author Contributions

Conceptualization, T.L. and S.Z.; methodology, S.Z. and C.M.; software, T.L. and S.Z.; validation, T.L., S.Z., T.S. and C.M.; formal analysis, T.L. and S.Z.; investigation, S.Z. and C.M.; resources, S.Z. and X.X.; data curation, S.Z. and X.X.; writing—original draft preparation, T.L. and S.Z.; writing—review and editing, S.Z. and X.X.; visualization, S.Z.; supervision, X.X.; project administration, S.Z.; funding acquisition, X.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key R&D Programme of Ningxia Hui Autonomous Region (grant no. 2024BBF01013), the China Agriculture Research System of MOF and MARA (grant no. CARS-12), and the Agricultural Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences, Crop Protection Machinery Team (grant no. CAAS-ASTIP-CPMT).

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Fuller, M.P.; Wisniewski, M. The use of infrared thermal imaging in the study of ice nucleation and freezing of plants. J. Therm. Biol. 1998, 23, 81–89. [Google Scholar] [CrossRef]
  2. Vitasse, Y.; Lenz, A.; Körner, C. The interaction between freezing tolerance and phenology in temperate deciduous trees. Front. Plant Sci. 2014, 5, 541. [Google Scholar] [CrossRef]
  3. Repo, T.; Hänninen, H.; Kellomäki, S. The effects of long—Term elevation of air temperature and CO on the frost hardiness of Scots pine. Plant Cell Environ. 1996, 19, 209–216. [Google Scholar] [CrossRef]
  4. Skahill, B.; Berenguer, B.; Stoll, M. A Spatial Risk Analysis of Springtime Daily Minimum Surface Air Temperature Values for Vineyard Site Selection: Applications to Pinot Noir Grapevines Throughout the Willamette Valley American Viticultural Area. Agronomy 2024, 14, 1566. [Google Scholar] [CrossRef]
  5. Arora, R.; Rowland, L.J.; Tanino, K. Induction and Release of Bud Dormancy in Woody Perennials: A Science Comes of Age. Hortscience 2003, 38, 911–921. [Google Scholar] [CrossRef]
  6. Kalberer, S.R.; Wisniewski, M.; Arora, R.; Rowland, L.J. Deacclimation and Reacclimation of Cold-Hardy Plants: Current Understanding and Emerging Concepts. Plant Sci. 2006, 171, 3–16. [Google Scholar] [CrossRef]
  7. Graczyk, D.; Szwed, M. Changes in the Occurrence of Late Spring Frost in Poland. Agronomy 2020, 10, 1835. [Google Scholar] [CrossRef]
  8. Thomashow, M.F. Plant Cold Acclimation: Freezing Tolerance Genes and Regulatory Mechanisms. Annu. Rev. Plant Physiol. Plant Mol. Biol. 1999, 50, 571–599. [Google Scholar] [CrossRef]
  9. Augspurger, C.K. Reconstructing patterns of temperature, phenology, and frost damage over 124 years: Spring damage risk is increasing. Ecology 2013, 94, 41–50. [Google Scholar] [CrossRef]
  10. Gu, L.; Hanson, P.J.; Post, W.M.; Kaiser, P.D.; Yang, B.; Nemani, R.; Pallardy, S.; Meyers, T. The 2007 Eastern US spring freeze: Increased cold damage in a warming world? Bioscience 2008, 58, 253–262. [Google Scholar] [CrossRef]
  11. Inouye, D.W. The ecological and evolutionary significance of frost in the context of climate change. Ecol. Lett. 2000, 3, 517–523. [Google Scholar] [CrossRef]
  12. Ma, Q.; Huang, J.; Hänninen, H.; Berninger, F. Divergent trends in the risk of spring frost damage to trees in Europe with recent warming. Glob. Change Biol. 2019, 25, 351–360. [Google Scholar] [CrossRef]
  13. Xiang, J.; Hare, M.C.; Vickers, L.H.; Kettlewell, P.S. A Comparative Study on Rapeseed Sprayed with Film Antitranspirant Under Two Contrasting Rates of Soil Water Depletion. Agronomy 2024, 14, 2944. [Google Scholar] [CrossRef]
  14. Faralli, M.; Weerasinghe, M.; Leung, G.; Marriott, R.; Miles, M.; Kettlewell, P. Wax Extracted from Waste Cauliflower Leaves Shows Potential Antitranspirant Efficacy When Applied to Rapeseed Plants. Agronomy 2022, 12, 455. [Google Scholar] [CrossRef]
  15. Peltonen-sainio, P.; Jauhiainen, L.; Känkänen, H. Finnish Farmers Feel They Have Succeeded in Adopting Cover Crops but Need Down-to-Earth Support from Research. Agronomy 2023, 13, 2326. [Google Scholar] [CrossRef]
  16. Rodrigo, J. Spring frosts in deciduous fruit trees—Morphological damage and flower hardiness. Sci. Hortic. 2000, 85, 155–173. [Google Scholar] [CrossRef]
  17. Battany, M.C. Vineyard frost protection with upward-blowing wind machines. Agric. For. Meteorol. 2012, 157, 39–48. [Google Scholar] [CrossRef]
  18. Heusinkveld, V.W.J.; van Hooft, J.A.; Schilperoort, B.; Baas, P.; Veldhuis, M. Towards a physics-based understanding of fruit frost protection using wind machines. Agric. For. Meteorol. 2020, 282, 107868. [Google Scholar] [CrossRef]
  19. Ribeiro, A.C.; De Melo-Abreu, J.P.; Snyder, R.L. Apple orchard frost protection with wind machine operation. Agric. For. Meteorol. 2006, 141, 71–81. [Google Scholar] [CrossRef]
  20. Boekee, J.; Dai, Y.; Schilperoort, B.; Wiel, B.J.H.; Veldhuis, M. Plant–atmosphere heat exchange during wind machine operation for frost protection. Agric. For. Meteorol. 2023, 330, 109312. [Google Scholar] [CrossRef]
  21. Pan, Q.; Lu, Y.; Hu, H.; Hu, Y. Review and research prospects on sprinkler irrigation frost protection for horticultural crops. Sci. Hortic. 2024, 326, 112775. [Google Scholar] [CrossRef]
  22. Ghaemi, A.A.; Rafie Rafiee, M.; Sepaskhah, A.R. Tree-Temperature Monitoring for Frost Protection of Orchards in Semi-Arid Regions Using Sprinkler Irrigation. Agric. Sci. China 2009, 8, 98–107. [Google Scholar] [CrossRef]
  23. Atam, E.; Abdelmaguid, T.F.; Keskin, M.E.; Kerrigan, E.C. A hybrid green energy-based system with a multi-objective optimization approach for optimal frost prevention in horticulture. J. Clean. Prod. 2021, 329, 129563. [Google Scholar] [CrossRef]
  24. Wu, H.; Wang, S. Design and optimization of intelligent orchard frost prevention machine under low-carbon emission reduction. J. Clean. Prod. 2023, 433, 139808. [Google Scholar] [CrossRef]
  25. Pecl, G.T.; Araújo, M.B.; Bell, J.D.; Blanchard, J.; Bonebrake, T.C.; Chen, C.; Clark, T.D.; Colwell, R.K.; Danielson, F.; Evengård, B.; et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science 2017, 355, eaai9214. [Google Scholar] [CrossRef]
  26. Samaniego, L.; Kumar, R.; Attinger, S. Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res. 2010, 46. [Google Scholar] [CrossRef]
  27. Radoglou-Grammatikis, P.; Sarigiannidis, P.; Lagkas, T.; Moscholios, L. A compilation of UAV applications for precision agriculture. Comput. Netw. 2020, 172, 107148. [Google Scholar] [CrossRef]
  28. Tsouros, D.C.; Bibi, S.; Sarigiannidis, P.G. A review on UAV-based applications for precision agriculture. Information 2019, 10, 349. [Google Scholar] [CrossRef]
  29. Qiao, B.; Wang, L.; Han, H.; Huang, Z.; Lin, Y. Effects of airflow disturbance from a multi-rotor unmanned aerial vehicle on fruit tree frost protection. Biosyst. Eng. 2024, 241, 95–112. [Google Scholar] [CrossRef]
  30. Hu, Y.; Liu, S.; Wu, W.; Wang, J.; Shen, J. Optimal flight parameters of unmanned helicopter for tea plantation frost protection. Int. J. Agric. Biol. Eng. 2015, 8, 50–57. [Google Scholar]
  31. Jones, H.G. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology; Cambridge University Press: Cambridge, UK, 2013; pp. 224–254. [Google Scholar]
  32. Smith, E.; Coolong; Timothy, C.; Pam, K. Commercial Freeze Protection for Fruits and Vegetables, UGA Cooperative Extension Bulletin. 2017. Available online: https://extension.uga.edu/ (accessed on 6 May 2025).
  33. Brown, J.M.; Yu, X.; Holloway, H.M.P.; Dacosta, M.; Bernstein, R.P. Differences in promote response to cold acclimation in Zoysia japonica cultivars with different levels of freeze tolerance. Crop Sci. 2020, 60, 2744–2756. [Google Scholar] [CrossRef]
  34. Green, M. Quantifying Sub-Canopy Water Recycling in a Mixed Hardwood Forest; Agu Fall Meeting Abstracts 2019, H44A-01; American Geophysical Union: Washington, DC, USA, 2019. [Google Scholar]
  35. Song, H.; Hu, Y.; Lu, Y.; Wang, J.; Pan, Q. A Review of Methods and Techniques for Detecting Frost on Plant Surfaces. Agriculture 2021, 11, 1142. [Google Scholar] [CrossRef]
  36. Kimura, K.; Yasutake, D.; Nakazono, K.; Kitano, M. Dynamic distribution of thermal effects of an oscillating frost protective fan in a tea field. Biosyst. Eng. 2017, 164, 98–109. [Google Scholar] [CrossRef]
  37. Hu, Y.; Li, P.; Dai, Q.; Zhang, X.; Kazuhisa, T.; Cui, G. System design and experiment on elevated wind machine for tea frost protection. Trans. Chin. Soc. Agric. Mach. 2007, 97–99, 124. [Google Scholar]
  38. Hu, Y. Mechanism and Control Technology of Late Frost Protection for Tea Plant (Camellia sinensis L.) Through Air Disturbance; Jiangsu University: Zhenjiang, China, 2011. [Google Scholar]
  39. Hu, Y.; Zhu, X.; Zhao, M.; Snyder, R.; Li, P. Operation effects of wind machines for frost protection of tea trees on different time scales. Trans. Chin. Soc. Agric. Mach. 2013, 44, 252–257. [Google Scholar]
  40. Wu, W.; Hu, Y.; Yang, S.; Mao, K.; Zhu, X.; Li, P. Optimal design of wind machine impeller for frost protection based on CFD and its field test on airflow disturbance. Int. J. Agric. Biol. Eng. 2015, 8, 43–49. [Google Scholar]
  41. Huang, Z.; Pan, Z.; Hu, Y.; Wang, X.; Wu, W. Research on 3D wind field and temperature variation based on tea antifrost fan. J. Chin. Agric. Mech. 2016, 37, 75–79. [Google Scholar]
  42. Hu, Y.; Feng, C.; Tang, J.; Xie, Z.; Zhang, Z. Structure design and test on noise reduction for frost protection wind machine of arc-plate blade. Trans. Chin. Soc. Agric. Mach. 2023, 54, 158–168. [Google Scholar]
  43. Yin, X.; Wang, Y.; Ding, R.; Fu, S.; Zhang, F.; Chen, Q. Effective experiment of elevated wind machine for frost protection with long blade in large apple orchards. Trans. Chin. Soc. Agric. Eng. 2014, 30, 25–32. [Google Scholar]
  44. Yang, F.; Xue, X.; Cai, C.; Sun, Z.; Zhou, Q. Numerical Simulation and Analysis on Spray Drift Movement of Multirotor Plant Protection Unmanned Aerial Vehicle. Energies 2018, 11, 2399. [Google Scholar] [CrossRef]
  45. Zhu, Y.; Guo, Q.; Tang, Y.; Zhu, X.; He, Y.; Huang, H.; Luo, S. CFD Simulation and Measurement of the Downwash Airflow of a Quadrotor Plant Protection Uav During Operation. Comput. Electron. Agric. 2022, 201, 107286. [Google Scholar] [CrossRef]
  46. Hu, Y.; Liu, S.; Shen, J. Frost protection experiment in tea fields using an unmanned helicopters. J. Shenyang Agric. Univ. 2013, 44, 692–695. [Google Scholar]
  47. Hamer, P. The heat balance of apple buds and blossoms. Part II. The water requirements for frost protection by overhead sprinkler irrigation. Agric. For. Meteorol. 1986, 37, 159–174. [Google Scholar] [CrossRef]
  48. Barfield, B.J.; Walton, L.R.; Lacey, R.E. Prediction of sprinkler rates for night-time radiation frost protection. Agric. Meteorol. 1981, 24, 1–9. [Google Scholar] [CrossRef]
  49. Rieger, M. Under- and overtree microsprinkler irrigation for frost protection of peaches. Horttechnology 1993, 3, 81–85. [Google Scholar] [CrossRef]
  50. Koc, A.B.; Heinemann, P.H.; Crassweller, R.M.; Morrow, C.T. Automated cycled sprinkler irrigation system for frost protection of apple buds. Appl. Eng. Agric. 2000, 16, 231–240. [Google Scholar] [CrossRef]
  51. Perry, K.B. FROSTPRO, a model of overhead irrigation rates for frost/freeze protection of apple orchards. J. Hortsci. 1986, 21, 1060–1061. [Google Scholar] [CrossRef]
  52. Issa, R.J. Numerical heat transfer model for frost protection of citrus fruits by water from a spraying system. Therm. Sci. 2012, 16, 31–42. [Google Scholar] [CrossRef]
  53. Olszewski, F.; Jeranyama, P.; Kennedy, C.D.; Moranville, C.J.D. Automated cycled sprinkler irrigation for spring frost protection of cranberries. Agric. Water Manag. 2017, 189, 19–26. [Google Scholar] [CrossRef]
  54. Bai, C.; Chen, Q.; Duan, G. Irrigation for frost prevention in apple orchards. Ningxia Agric. Sci. Technol. 1980, 5, 28–31. [Google Scholar]
  55. Hu, Y.; Zhao, C.; Liu, P.; Eric, A.A.; Li, P. Sprinkler irrigation system for tea frost protection and the application effect. Int. J. Agric. Biol. Eng. 2016, 9, 17–23. [Google Scholar]
  56. Pan, Q.; Lu, Y.; Zhang, Z.; Jin, K.; Song, J.; Hu, Y. Variation and influencing factors of water/ice storage within tea plant during frost protection sprinkling. Trans. Chin. Soc. Agric. Mach. 2024, 55, 180–187. [Google Scholar]
  57. Hua, W.; Heinemann, P.; He, L. Heat transfer modeling with fixed and mobile heaters for frost protection in apple orchards. Comput. Electron. Agric. 2024, 227, 109525. [Google Scholar] [CrossRef]
  58. Hua, W.; He, L.; Heinemann, P.; Zhu, M. Precision heating strategy based dynamic heater path planning for frost protection in apple orchards. Biosyst. Eng. 2025, 250, 117–132. [Google Scholar] [CrossRef]
  59. Zhang, S.; Xue, X.; Sun, T.; Gu, W.; Zhang, C.; Peng, B.; Sun, X. Evaluation and comparison of two typical kinds UAAS based on the first industry standard of China. Int. Agric. Eng. J. 2020, 29, 331–340. [Google Scholar]
  60. Xue, X.; Lan, Y.; Sun, Z.; Chang, C.; Hoffmann, W. Develop an unmanned aerial vehicle based automatic aerial spraying system. Comput. Electron. Agric. 2016, 128, 58–66. [Google Scholar] [CrossRef]
  61. Zhang, S.; Xue, X.; Chen, C.; Sun, Z.; Sun, T. Development of a low-cost quadrotor UAV based on ADRC for agricultural remote sensing. Int. J. Agric. Biol. Eng. 2019, 12, 82–87. [Google Scholar] [CrossRef]
  62. Wang, X.; Wang, M.; Wang, S.; Wu, Y. Extraction of vegetation information from visible unmanned aerial vehicle images. Trans. Trans. Chin. Soc. Agric. Mach. Eng. 2015, 31, 152–159. [Google Scholar]
  63. Zhang, S.; Qiu, B.; Xue, X.; Sun, T.; Peng, B. Parameters optimization of crop protection UAS based on the first industry standard of China. Int. J. Agric. Biol. Eng. 2020, 13, 29–35. [Google Scholar] [CrossRef]
  64. Zhang, S.; Cai, C.; Li, J.; Cheng, X.; Sun, T.; Liu, X.; Tian, Y.; Xue, X. The airflow field characteristics of the unmanned agricultural aerial system on oilseed rape (Brassica napus) canopy for supplementary pollination. Agronomy 2021, 11, 2035. [Google Scholar] [CrossRef]
  65. Zhang, J.; Zhang, S.; Li, J.; Cai, C.; Gu, W.; Cheng, X.; Wang, H.; Xue, X. Effects of different pollination methods on oilseed rape (Brassica napus) plant growth traits and rapeseed yields. Plants 2022, 11, 1677. [Google Scholar] [CrossRef]
  66. Song, C.; Zhou, Z.; Jiang, R.; Luo, X.; He, X.; Ming, R. Design and parameter optimization of pneumatic rice sowing device for unmanned aerial vehicle. Trans. Trans. Chin. Soc. Agric. Mach. Eng. 2018, 34, 80–88. [Google Scholar]
  67. Wang, L.; Lan, Y.; Zhang, Y.; Zhang, H.; Tahir, M.; Ou, S.; Liu, X.; Chen, P. Applications and prospects of agricultural unmanned aerial vehicle obstacle avoidance technology in China. Sensors 2019, 19, 642. [Google Scholar] [CrossRef]
  68. Cao, G.; Li, Y.; Nan, F.; Liu, D.; Chen, C.; Zhang, J. Development and analysis of plant protection control system and route planning research. Trans. Chin. Soc. Agric. Mach. Mach. 2020, 8, 1–16. [Google Scholar]
  69. Valente, J.; Sanz, D.; Barrientos, A.; Cerro, J.; Riberio, A.; Rossi, C. An Air-ground Wireless Sensor Network for Crop Monitoring. Sensors 2011, 11, 6088–6108. [Google Scholar] [CrossRef]
  70. Sun, Z.; Gu, W.; Cui, L.; Cai, C.; Chen, C.; Zhou, Q.; Ding, S.; Lan, Y.; Xue, X. Research status and development trends of key technologies for intelligent plant protection equipment. J. Intell. Agric. Mech. 2024, 5, 1–23. [Google Scholar]
  71. Hu, P.; Zhang, R.; Yang, J.; Chen, L. Development status and key technologies of plant protection UAVs in China: A review. Drones 2022, 6, 354. [Google Scholar] [CrossRef]
  72. García-Munguía, A.; Guerra-Ávila, P.L.; Islas-Ojeda, E.; Flores-Sánchez, J.L.; Vázquez-Martínez, O.; García-Munguía, A.M.; GarcíaMunguía, O. A review of drone technology and operation processes in agricultural crop spraying. Drones 2024, 8, 674. [Google Scholar] [CrossRef]
  73. Available online: https://www.orchard-rite.com/ (accessed on 6 May 2025).
  74. Available online: https://www.towandblow.com/ (accessed on 6 May 2025).
  75. Available online: https://www.nelsonirrigation.com/ (accessed on 6 May 2025).
  76. Available online: https://www.rainbird.com/ (accessed on 6 May 2025).
  77. Available online: https://ag.dji.com/ (accessed on 6 May 2025).
  78. Available online: https://www.xag.cn/ (accessed on 6 May 2025).
Agronomy 15 01164 g001
Figure 1. Conditions for the formation of frost on natural radiation surfaces.
Figure 1. Conditions for the formation of frost on natural radiation surfaces.
Agronomy 15 01164 g001
Agronomy 15 01164 g002
Figure 2. Formation principle of frost layer on plant surface.
Figure 2. Formation principle of frost layer on plant surface.
Agronomy 15 01164 g002
Agronomy 15 01164 g003
Figure 3. Diagram of FP fan principle.
Figure 3. Diagram of FP fan principle.
Agronomy 15 01164 g003
Agronomy 15 01164 g004
Figure 4. Upward-suction and discharge-type fan (a) and its schematic diagram (b). 1. Axial fan; 2. frost protection duct; 3. transmission; 4. windbreak; 5. plants; 6. bracket; 7. motor.
Figure 4. Upward-suction and discharge-type fan (a) and its schematic diagram (b). 1. Axial fan; 2. frost protection duct; 3. transmission; 4. windbreak; 5. plants; 6. bracket; 7. motor.
Agronomy 15 01164 g004
Agronomy 15 01164 g005
Figure 5. Frost-proof fan used by Vincent W.J. Heusinkveld.
Figure 5. Frost-proof fan used by Vincent W.J. Heusinkveld.
Agronomy 15 01164 g005
Agronomy 15 01164 g006
Figure 6. CFD simulation of downward airflow for unmanned aerial vehicles. (a) Flight velocity 1 m/s, front view. (b) Flight velocity 1 m/s, side view. (c) Flight velocity 1 m/s, top view. (d) Flight velocity 2 m/s, front view. (e) Flight velocity 2 m/s, side view. (f) Flight velocity 2 m/s, top view.
Figure 6. CFD simulation of downward airflow for unmanned aerial vehicles. (a) Flight velocity 1 m/s, front view. (b) Flight velocity 1 m/s, side view. (c) Flight velocity 1 m/s, top view. (d) Flight velocity 2 m/s, front view. (e) Flight velocity 2 m/s, side view. (f) Flight velocity 2 m/s, top view.
Agronomy 15 01164 g006
Agronomy 15 01164 g007
Figure 7. Schematic diagram of helicopter anti-frosting mechanism. 1. UAV; 2. temperature sensor; 3. tea plants.
Figure 7. Schematic diagram of helicopter anti-frosting mechanism. 1. UAV; 2. temperature sensor; 3. tea plants.
Agronomy 15 01164 g007
Agronomy 15 01164 g008
Figure 8. The agricultural UAV used in the experiment.
Figure 8. The agricultural UAV used in the experiment.
Agronomy 15 01164 g008
Agronomy 15 01164 g009
Figure 9. The agricultural UAV DJI T40 used in peach orchard FP.
Figure 9. The agricultural UAV DJI T40 used in peach orchard FP.
Agronomy 15 01164 g009
Agronomy 15 01164 g010
Figure 10. Schematic diagram of sprinkler irrigation for FP.
Figure 10. Schematic diagram of sprinkler irrigation for FP.
Agronomy 15 01164 g010
Agronomy 15 01164 g011
Figure 11. The combustion furnace used for heating.
Figure 11. The combustion furnace used for heating.
Agronomy 15 01164 g011
Agronomy 15 01164 g012
Figure 12. Schematic diagram of integrated hot air blower-based hybrid green energy anti-frosting system.
Figure 12. Schematic diagram of integrated hot air blower-based hybrid green energy anti-frosting system.
Agronomy 15 01164 g012
Agronomy 15 01164 g013
Figure 13. Schematic diagram of anti-frost machine.
Figure 13. Schematic diagram of anti-frost machine.
Agronomy 15 01164 g013
Agronomy 15 01164 g014
Figure 14. Mobile heating system for orchards based on UGV.
Figure 14. Mobile heating system for orchards based on UGV.
Agronomy 15 01164 g014
Table 1. Comparison of air disturbance frost protection methods and effectiveness.
Table 1. Comparison of air disturbance frost protection methods and effectiveness.
Method/EquipmentKey Effectiveness MeasureLocationPlant TypeReference
Conventional wind machineReduced flower damage by 60% (1999) and 37% (2000); more effective under strong inversion.Apple orchard, PortugalApple[19]
Conventional and upward-suction fansConventional fan showed greater temperature increase, especially at 1.1 m under strong inversion. Upward-suction fan had limited effect, potentially negative under weak inversion.Vineyard, USAGrapevine[17]
Oscillating anti-freezing fansImproved thermal balance of tea leaves; more effective under strong inversion.Tea field, JapanTea[36]
Conventional wind machine (field tests and simulations)Temperature increase at up to 1 m height covered 3–5 hectares; slower rotation (3–6 min) increased affected area; optimal tilt angle between 8° and 16°.Fruit orchard, the NetherlandsFruit trees (pear)[18]
Fans (general principles)Mechanism: mixes air and erodes boundary layer; leaf temperature lags behind air temperature; requires approximately 15 rotations for optimal mixing.Orchard focusGeneral[20]
High-altitude fan3 kw system: covered over 1000 m2; achieved 4 °C temperature increase at negative 4 °C ambient temperature.Tea garden, ChinaTea[37,38,39,40,41,42]
Large-scale orchard FP machine120 kw, 8.5 m height, 6 m blade machine: effective horizontal range of 20–100 m; protected area of 1.73–3.07 hectares per machine.Orchard, ChinaFruit trees[43]
UAV (2012)Best result: achieved 3.83 °C temperature increase (at 5 m height, 6 m/s speed, 30 min interval). Disturbance effect decreased as height increased (5–10 m).Tea garden, ChinaTea[46]
UAV (2015)Optimal result: achieved 1.6 °C temperature increase (at 4.0 m height, 6.0 m/s speed, 20 min interval, with 3.8 °C inversion). Parameter influence order: interval > height > speed.Tea plantation, ChinaTea[30]
UAV (DJI T40 Multi-rotor)Hovering (6 m, 1000 rpm): achieved 2.5 °C to 3.0 °C near-ground temperature increase during critical frost; stabilized temperatures in less than 20 s.Peach orchard, ChinaPeach[29]
Table 2. Comparison of sprinkler irrigation frost protection methods and effectiveness.
Table 2. Comparison of sprinkler irrigation frost protection methods and effectiveness.
Method/EquipmentKey Effectiveness MeasureLocationPlant TypeReference
Automatic control (vs. fixed rate)Provided complete protection using 50% less water than conventional fixed rate.Fruit orchardApple[47]
Heat balance model Including humidity is crucial; ignoring it can lead to up to 28% underestimation of required rate.GeneralGeneral[48]
Micro-sprinkler (over-tree vs. overhead)Over-tree method maintained peach buds above lethal temperature; used 50% to 87% less water and energy compared to traditional overhead method.Peach orchardPeach[49]
Automatic cycling (vs. continuous)Reduced average water consumption by approximately 72% in three frost events compared to continuous sprinkling.Apple orchard, USA (PA)Apple[50]
Automatic system (humidity/temperature-based)Maintained peach blossom temperature 2.5 °C higher than control; reduced blossom mortality by 29.5%, with 54.3% less water.Peach orchard, IranPeach[22]
Simplified water film model Determined required irrigation frequency to maintain water film and prevent temperature dropping below 0 °C.TheoreticalCitrus[52]
Automatic cyclic system (vs. continuous)Reduced seasonal water use by 33% to 80% (113 to 198 mm saved); yield often higher than with traditional continuous frost irrigation.Cranberry bog, USACranberry[53]
Ground irrigation (pre-frost/bloom)Increased air temperature and humidity, reducing frost damage to flower clusters.Apple orchard, China (Ningxia)Apple[54]
Continuous spraying (2–4 mm/h)Maintained tea canopy near 0 °C; post-sunrise temperature rise slowed (+2.2 °C/h vs. +4.8 °C/h in non-irrigated), preventing potential damage.Tea field, ChinaTea[55]
Micro-sprinkler vs. rocker-armMicro-sprinkler led to storage of 1.2 times more water and 2.0 times more ice; sprinkling duration significantly increased maximum ice storage, but not maximum water storage.Tea field, ChinaTea[56]
Table 3. Comparison of heating frost protection methods and effectiveness.
Table 3. Comparison of heating frost protection methods and effectiveness.
Method/EquipmentKey Effectiveness MeasureLocationPlant TypeReference
Hybrid green energy systemOptimized layout reduced pipeline length by 24.13% and improved heating efficacy by 54.29% compared to heuristic design.HorticultureGeneral[23]
Intelligent orchard FP machine Covered 10 m radius effectively, even with 2 m/s wind; dynamic adaptation; potential for solar power integration.Mountainous orchardFruit trees[24]
Fixed air heatersVPPC achieved was 32.2%; positioning heaters upwind was better than downwind. Reducing interaction between heaters improved performance.Apple orchardApple[57]
Mobile air heatersIncreased VPPC by 1180.0% compared to heaters at one end, and 141.5% compared to heaters at middle/other end.Apple orchard Apple[57]
Precision heating strategyNumber of heaters required was 96.8% less than that of traditional fixed type and 85.9% less than that of traditional mobile type.Apple orchardApple[58]
Table 4. Estimated Costs for Different Frost Protection Methods.
Table 4. Estimated Costs for Different Frost Protection Methods.
MethodInitial Investment Annual Operating CostKey Cost DriversManufacturer
Wind machines$3000–$7000+$100–$600+Initial investment: high equipment cost
Operating costs: electricity and maintenance		Orchard-Rite (Yakima, WA, USA)
[73]
Tow and Blow (Hawke’s Bay, NZ, USA)
[74]
Sprinkler irrigation$1500–$5000+$150–$800+Initial investment: highly dependent on water source
Operating costs: mainly pumping energy and potentially water costs		Nelson Irrigation (Walla Walla, WA, USA)
[75]
Rain Bird (Azusa, CA, USA)
[76]
Heaters——$500–$2500+Initial investment: requires many units
Operating costs: primarily fuel, extremely high		 Often involve local integrators rather than single global brands
UAV$1500–$6000+$50–$400+Initial investment: relatively high, but a UAV can achieve multiple functions with a single machine
Operating costs: mainly electricity for charging		DJI (Shenzhen, China)
[77]
XAG (Guangzhou, China)
https://www.xag.cn/ [78]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Liu, T.; Zhang, S.; Sun, T.; Ma, C.; Xue, X. Review of Active Plant Frost Protection Equipment and Technologies: Current Status, Challenges, and Future Prospects. Agronomy 2025, 15, 1164. https://doi.org/10.3390/agronomy15051164

AMA Style

Liu T, Zhang S, Sun T, Ma C, Xue X. Review of Active Plant Frost Protection Equipment and Technologies: Current Status, Challenges, and Future Prospects. Agronomy. 2025; 15(5):1164. https://doi.org/10.3390/agronomy15051164

Chicago/Turabian Style

Liu, Tianhong, Songchao Zhang, Tao Sun, Cong Ma, and Xinyu Xue. 2025. "Review of Active Plant Frost Protection Equipment and Technologies: Current Status, Challenges, and Future Prospects" Agronomy 15, no. 5: 1164. https://doi.org/10.3390/agronomy15051164

APA Style

Liu, T., Zhang, S., Sun, T., Ma, C., & Xue, X. (2025). Review of Active Plant Frost Protection Equipment and Technologies: Current Status, Challenges, and Future Prospects. Agronomy, 15(5), 1164. https://doi.org/10.3390/agronomy15051164

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop