Agricultural Thermal Inspections (ATI) and Multispectral Sensors

Multispectral Camera Sensors

Multispectral Cameras attached on Drones ( UAVs) allow
researchers, analysts and farmers to get an overview that
will facilititate measurement of chlorophyll.

Why Measure Chlorophyll?

Chlorophyll is the green pigment that allows plants to
photosynthesize. This process uses sunlight to convert carbon dioxide and water into basic components for plants. Since nitrogen is a part of chlorophyll, by measuring it, you indirectly measure the amount of nitrogen in the plant. This allows for more efficient programming of fertilizer applications.

Since the UAV system could provide flexible flight performance and high temporal and spatial resolution imagery, the ground-based methods on crop status measurement may be done on UAV system to achieve more accurate results than satellite images. The advantages of the multispectral camera were demonstrated. It could provide some better vegetation indices in the estimation of plant biophysical parameters. Specifically the red-edge bands in multispectral camera could provide more vegetation indices combinations. Therefore, a multispectral camera could be applied in future research on wheat and corn total nitrogen and final yield estimation. Additionally, many researchers used ground based multispectral or hyperspectral imagery to monitor crop disease and water status. By using the Tetracam, the wavelength of each band can be adjusted to the requirements of different indices, these indices derived from ground based research could be measured with the UAV system and achieved for a large area monitoring.


Relationship between Nitrogen content and GNDVI

In the first part of this study, we determined the relationship between wheat foliage nitrogen and the remote sensing results GNDVI. The GNDVI was correlated weakly with the reference wheat foliage nitrogen content measurements (R2 = 0.085). Wheat foliage nitrogen content ranged from 3% to 6%, with a trend for nitrogen content to decrease from May to July, possibly caused by mechanisms of nitrogen distribution and transformation in wheat. In the tillering and stem extension stage, wheat absorbed much nitrogen from soil to produce chlorophyll, and therefore, the two measurements in May were the highest for nitrogen content. From stem extension to the heading stage, the transfer of nitrogen in leaves to grain was initiated, and the foliage nitrogen content rapidly declined. Therefore, we calculated the total weight of foliage nitrogen using a physical dry biomass estimation method to evaluate the relationship between total weight of foliage nitrogen and GNDVI.



An infrared thermal imaging system provides the surface temperature of any object and these data may be used directly or indirectly for many applications. However, this method is suitable for making quality determination of surface temperature than quantitative measurement (Davis and Lettington 1988). This technique has been used in various fields such as medicine, electrical, mechanical, and civil engineering for a long time (Agerskans 1975). The reductions in cost of the equipment and simple operational procedure have created opportunities for the application in several fields of the agricultural and food industries. This technology can be used in all agricultural materials and processes, where heat is generated or lost in space and time (Hellebrand et al. 2002). Small variations (below 1o C) can also be successfully measured with proper equipment and methodology. If the temperature difference is too small, a suitable environment should be created such as increasing or decreasing the temperature of the sample and measuring the rate of cooling or heating (Danno et al. 1980). 


Pre-Harvest Operations

Plant leaves possess a complex heterogeneous internal structure and because of this different parts of the leaf contain different amounts of water per unit area, affecting thermal properties. The important parameters in plant physiology such as transpiration rate, heat capacity per unit area of the leaf, and the water flow velocity can be measured to high temporal and spatial resolution by thermal imaging techniques (Christoph et al. 2002). Identification of diseases in the 4 field nursery before visible symptoms occur, irrigation scheduling based on soil moisture content and plant parameters, detection of fruits and vegetables on the plants to guide mechanical harvesting, and yield forecasting are the potential areas in which thermal imaging methods may be utilized effectively in the agricultural fields.


Field nursery

Local microclimatic changes in the field nursery will cause severe damage to the tender seedlings. Early detection of dampness and disease in a nursery is very important to take early control measures. The microclimatic changes inside the nursery site can be mapped with great spatial accuracy using infrared thermography. In a field nursery, significant positive correlation was found between seedling temperature and degree of damage (Hellebrand et al. 2002). The warmest seedlings had a lower survival rate than the cooler seedlings (Egnell and Orlander 1993). Kim and Lee (2004) developed algorithms to detect the quality of potato transplants using visual and thermal imaging. Potato transplants were grown at three photosynthetic photon flux (PPF) levels of 50, 150, 250 µmol.m2 s-1 and four electrical conductivity levels of 700, 1400, 2100, 2800 µ The leaf temperature was higher (by about 0.5 to 2.0o C) for the transplants grown at PPF of 50 µmol.m2 s-1 than the other two treatments. The authors stated that thermal and visual characteristics of potato transplants can be used to monitor the transplants’ grown at low PPF.


Irrigation scheduling

Infrared thermometry may be used to schedule irrigation based on soil moisture content and plant parameters such as evapo-transpiration, stomatal conductance, and closing of stomata (Jones 1999). Inoue et al. (1990) determined the transpiration and stomatal conductance using infrared thermometry. Temperature of the canopy was taken with the help of a handheld infrared thermal camera in a cotton field. Transpiration rate and stomatal conductance were calculated using canopy temperature and other meteorological data in a model. A porometer was used to measure transpiration and stomatal conductance in the field simultaneously. Crop stress indices calculated by remote infrared thermometry were linearly related with porormeter values and R2 of 0.79 and 0.93 for transpiration and stomatal resistance, respectively. Berliner et al. (1984) determined the crop stress for wheat using infrared thermometry. A thermal camera was installed on a platform located on the top of a pole (3.3 m height) in the field. In addition to canopy temperature, wet and dry bulb temperatures, wind speed, and solar radiation were also recorded simultaneously. Stomatal resistance and water potential had a linear relationship with canopy temperature and the R2 were 0.64 and 0.65, respectively. For the implementation of canopy temperature as a water stress index, no meteorological data other than infrared measurement is required. Landsat thermal bands could be used to study the irrigation status of the field and different stages of growth of crops (Perdikou et al. 2002). Kalma and Jupp (1990) used infrared thermometry data to develop a model for estimating the evaporation from a pasture. All metabolic activities of a plant cause variation in temperature and hence, research on the quantification of changes in temperature on the canopy with respect to various plant parameters would yield valuable information required for precision farming.

Yield forecasting


 thermal picture


Time series data models are the commonly used methods to estimate yield for many crops in almost all parts of the world. But most of the time, high deviation is observed in the actual yield from the forecasted yield. Smith et al. (1985) analyzed the relationship between wheat yield and one-time measurement (daytime) of temperature difference between foliage and ambient air temperature (Tf-Ta). For foliage temperature measurement, they used a thermal camera (3o field of view lens) which received the infrared radiation in the spectral wavelength of 8-14 µm. The camera was held at 1.5 m height in the field and focused on the foliage at 30o . In addition to ambient and foliage temperatures, associated micrometeorological data were collected during the wheat growing stages from jointing to maturity. The experiment was conducted for two crop seasons (1982 and 1983) on a red-brown soil in Australia. Transpiration and the associated aerodynamic characteristics and canopy stomatal resistances to water vapor transport were predicted from the collected temperature 5 data. They determined that the predicted transpiration and CO2 assimilation rates were closely related to yield within each year but not between years. The regression coefficients for Tf-Ta and various yield parameters are shown in Table 2. It was stated that infrared thermometry would be a useful technique for studying yield variations in agronomic experiments.


Farm machinery

Unexpected failure of farm equipment during peak operational season can
result in severe economic losses. All mechanical and electrical equipment can be inspected by a thermal camera for wear and tear. By this method, it is possible to identify the excessive heat produced by components due to friction or any other reason. For instance, hay making equipment, planters, combines, tractors, and other mechanical equipment may be inspected by infrared thermography and proactive steps can be taken to change parts before they fail or 
cause an interruption in production (Hellebrand et al. 2002). Utter (2003) demonstrated the use of infrared thermography to identify the backfiring and oil leakage in agricultural aircraft.
In many developing countries, millions of people are involved in agricultural field
operations. To maximize work efficiency and field safety, ergonomic factors are being considered in the design of farm machinery and work environment. Thermography would be an excellent choice to map the body temperature of workers during field work.

Green Houses

The environmental conditions inside a greenhouse chamber should be maintained carefully because the small plants and seedlings are sensitive to small changes in the microclimate. Thermography is a useful tool to detect temperature anomalies at various locations inside the greenhouse. Ljungberg and Jonsson (2002) conducted an infrared survey to investigate the temperature profile at various locations inside a greenhouse such as surface of the tables used for plant production, radiation tubes, and plants at different stages of growth. The survey was conducted in greenhouses under conditions, production benches without plants and with plants. A thermal camera (wavelength 8-12 µm), mounted on a two wheeled cart was used for the survey. In the greenhouse with plants, the difference between maximum and minimum temperatures on the production benches was 4.3oC, whereas it was 11oC in the greenhouse without plants. The difference was more than 100oC on the radiation pipes in the greenhouse with plants and only 6.5oC in the greenhouse without plants. The authors suggested that thermography can be used as a tool to calibrate heating systems, evaluate its function, and to indicate anomalies in the growth process of plants inside a greenhouse. Infrared thermography may be used as an effective tool in research and evaluation of the growth process of plants at different energy related greenhouse conditions.