Introduction
The oil palm plantation in Malaysia is one amongst the largest producer of crude palm oil in the world. It is constitutes a key pillar of the Malaysian National Economy. The industry is well regulated, comprising government, land schemes and independent smallholdings, as well as those engage in downstream industries such as milling, processing, manufacturing and trading. The export revenues of palm oil are up to more than RM 67.6 billion in 2016. Oil palm was planted in more than 5.74 million hectares (ha) in 2016 and utilising the largest agricultural land area of more than 60% (Khusairi, et.al. 2017).
Despite the rapid growth of the industry, the oil palm remains prone to the threat by a variety of pests such as insects, vertebrates and diseases. With the fact that there are various techniques in in controlling such as cultural, mechanical, biological, genetic and chemical control are became the primary means of solving pest problem in plantation. Often the strategy of controlling at the late stages of pest outbreak are not satisfactory due to impact to human health and environment impact which are not comply with MSPO and RSPO.
Precise and efficient pest early detection and warning are key strategic important in handling and managing pest outbreak in the plantation. Meteorological data for example were used to forecast pest outbreaks based on knowledge of the biology and ecology of the pest. Ibrahim et.al. 2013, demonstrated that the effect of temperature on the development and survival of bagworm species conformed to the insect’s trend to increasing temperature until the optimum was reached.
The used of spatial technology, with comprises and Global Positioning System or GPS benefited agriculture through applications of crop nutrient and pest and disease status monitoring (Ahmadi et.al. 2017). The presence of remote sensing tools offer rapid, harmless and cost-effective means to obtain necessary information on the triggering factor of pest outbreaks such as temperature, relative humidity and their natural enemies.
What is Thermal Remote Sensing System or Thermography?
Thermal remote sensing technology or thermography is a non-destructive technique used to determine thermal properties of any objects of interest. The principle of thermal remote sensing is the invisible radiation patterns of objects converted into visible images and these images are called thermal images. These images can be acquired using portable, handheld or thermal sensors that are coupled with optical systems mounted on an airplane or satellite.
The potential use of thermal remote sensing in agriculture includes nursery and greenhouse monitoring, irrigation scheduling, plant disease detection, estimating fruit yield, evaluating the maturity of fruits and bruise detection in fruits and vegetables.
However, in recent years, the usage of thermal imaging is gaining popularity in pest detection due to the reductions in the cost of the equipment and simple operating procedure.
Concept and advantages of Thermography
Thermal remote sensing or Thermography is one amongst techniques in remote sensing systems. Others are such as Virtual, Optical Microwave, Radar and Synthetic Radar. Thermography however is a non-contact techniques to determine the temperature distribution of any object in a short period of time. It is deal with the acquisition, processing and interpretation of data acquired primary in the thermal portion of the electromagnetic spectrum (Ishimwe et.al. 2014).
The principle of thermal remote sensing is, it collects the thermal infrared regions within the infrared radiation from 8 to 12 um which emitted from the Earth's surface by thermal sensors or cameras into an image (Ishimwe et.al. 2014). The thermal remote sensing, radiations emitted by ground objects are measured for temperature estimation. These measurements give the radiant temperature of a body which depends on two factors; kinetic temperature and emissivity (Prakash. 2000).
Advantages of the thermal cameras are easy to handle and highly accurate temperature measurements are possible (Lloyd. 2013). Further, the thermal imaging, it is possible to obtain temperature mapping of any particular region of interest with fast response times, which is not possible with thermo-couples or other temperature sensors. In addition, the repeat- ability of temperature measurements is high in thermal imaging.
Furthermore, previous models of thermal camera’s required cryogenically cooled sensors to obtain temperature resolution of 0.1°C whereas recent day cameras can operate at room temperature, making these camera users friendly and promoting an increase in the use of thermal imaging in various fields (Ishimwe et.al. 2014; Lillesand & Chipman. 2014).
Detector and Lenses
The principle used by thermal imaging is heat from incoming IR radiation increases temperature and are used to measure temperature changes by ant temperature dependent mechanism such as thermo-electric voltage, resistance or pyro-electric voltage (Rogalski, 2003). The detectors used in thermal cameras may be broadly classified into three categories: classic semi-conductors, novel semi-conductors, and thermal detectors (Holst. 2000).
The lenses for thermal cameras are usually made of silicon (Si) or germanium (Ge) materials. In general, Si is used for MWIR cameras and Ge is used in LWIR cameras. Both materials have good mechanical properties (non-hygroscopic and do not break easily). While making proper design, infrared camera lenses can transmit close to 100% of incident radiation (Holst. 2000).
Thermal Imaging camera
A Thermo-graphic Camera (Infrared camera or Thermal Imaging Camera) is a device that forms an image using infrared radiation that similar to an image forms by a common camera using visible light. Thermal camera is designed to detect radiation emitted from a sample in a specified waveband into an electrical signal which is then processed into an image. Radiation in this part of the electromagnetic spectrum is referred to as infrared, or commonly IR, which is just beyond what the human eye can see (Lloyd. 2013; Prakash. 2000). On the other hand, camera sensors can be built to detect and make use of this type of radiation. A so-called day-and-night camera uses an IR-cut filter during daytime to filter out IR-light so it will not distort the colors of images as perceived by the human eye. When the camera is in night mode, the IR-cut filter is removed.
Since the human eye is unable to see infrared light the camera displays the image in black and white. Near infrared light also requires some kind of light source, either natural, such as moonlight, or man-made, such as street lights or a dedicated IR-lamp. With advancement in electronics and instrumentation technology, there are several thermal camera models available in the market at wide price ranges (Lloyd. 2013).
Case Study 1: Finding Termites with Thermal Imaging
Termites has been a huge problems in housing areas and urban buildings. Owners quite often are unaware of the present of any termite problem in their house. Pest Control Company are usually over-charged due to in ability to identify the location of the source of the problems.
Oil palm plantation especially in an area of peat are attack by subterranean termites. The primary termites capable of killing oil palm was Coptotermes curvignathus (Cheng S., Kirton, L.G. and Gurmit, S., 2008). The occurrences of termite attack in oil palm was reported first in 1927 in Malaya. In immature oil palm, termites attack palms as early as 7 to 8 months after planting and infestations of immature plantings could reach 8-9 per cent with 3-5 per cent killed per year if not quickly treated. In mature oil palm, termites gain entry into the central frond column to feed on spear and new frond bases and then the growing point; the palm is finally killed (Fee C.G., 2017).
When termite invade house and buildings, the normal heat pattern of the walls floors and roof are changes. Thermal imaging camera records changes in heat pattern and indicates the exact location of termite’s infestation. It was noted that termites are “ectothermic”, animal body temperature is determine by taking advantage of external condition and also called as cold-blooded animal whereby heat are not produced by the body. However, Termites are hosts to bacteria, which live in their gut and the bacteria helps to break down and digest cellulose, the main component of wood. The digestion and chemical reaction generates heat.
Figure 1: Termite Queen Figure 2: Termite Queen in Thermal Image
Figure credit to Ken J., and David R., 2002
Figure 1 and 2 are an example of end product of thermal imaging camera for Termite queen. Figure 3 and 4 is an example of how thermal image can be used as a tool to locate termites whereas conventional method fail to locate the infestation of termites.
Figure 3: Thermal imaging are capable to locate termite infestation Figure 4: Conventional investigation are not capable to find evidence of termite infestation
Figure credit to Ken J. and David R., 2002
Case Study 2: Remote Sensing for Monitoring Bagworm Infestation
Bagworm which classified in family Lepidoptera: Psychidea are categorised as leaf eating caterpillars characterised based on their bag, built from pieces of dried plant material i.e. leaves and small twigs (Barlow, 1982). The outbreak are very common in Malaysia with some states experiences a severe attack especially in west coast and having negative effect on economic due to reduction of oil palm yield.
According to Wood et.al. (1973), the yield decline over the next two years is caused by 50% of canopy damages and may up to 43% reduction. Perhaps more precise and early detection of bagworm infestation becomes critical part and may help in providing solution for oil palm plantation.
The census was conducted by MPOB in June 2012, at Teluk Intan Research Center. However, the study was using a spectral reflectance measures from field spectrometer instead of using thermal imaging. The data collection was based of three types of foliar damage and its respective spectral measurement i.e. light, medium and serious damage (Figure 5)
Figure 5: Spectral reflectance characteristics on each level of foliar damage.
Based on the obtained data, plotting of bagworm location infestation are possible to be plotted and displayed in a map mode (Figure 6). It can be translated into on ground action, indeed after minimum activity of on ground census. Decision can be made by planters and manager to use appropriate tools and method of controls the outbreak of bagworm.
Figure 6: Distribution of sampling points over layered in SPOT 5 satelite image of MPOB Research Station, Teluk Intan, Perak. (MPOB TT No 502)
Case Study 3: Thermal Imagery for Animal Detection
The large-scale of deforestation due to opening of new land for oil palm plantation creates crisis between human needs and the idealism of conservationist i.e. preserve the forest. Thus, RSPO and MSPO has a goal of transforming the industry in collaboration with the global supply chain. One amongst the important element in RSPO and MPSO are the High Conservation Value (HCV) and monitoring the wildlife are crucial. Similarly, information on animal pest such as wild boar, unattended cattle given a negative impact on overall plantation management.
The conventional techniques are often fail to give an actual number of animal life in the designated area. Traditional ground-based survey are such as direct counts or records or observation on transect counts, trapping, tagging and sign may give a predicted number of population. The accuracy in using traditional methods comes with high costs in both labour and other limitation. Field expedition often consists of laborious, intensive sampling over long periods of time.
The animal thermal scanner was recently used on a study basis in three experimental research two of which were on ground basis and through airborne. The observation scoring method and on image analysis were developed for quantification of the thermal images in the vegetation component.
Digital high resolution using remote sending has been used in combination with airborne platform perhaps may give a more detail data as well as more competitive costs and credible data. Thermal infrared sensors may give a more precise outcomes. Sensors measure the thermal radiant energy of materials within a scene. Most large animals are having a high radiant temperature in comparison with their current backgrounds. Therefore thermal sensors provide a potential means for counting and studying the distribution of animals at night (Barrett & Curtis 1992).
Thermal imagery has been recognised as a means of detecting animals since the late 1960s (Croon et. al. 1968). The technique has gained increasing recognition with the introduction and advance of new hardware technology, yet the method still remains at an experimental phase; few thermal aerial operational surveys are conducted. Inadequacies such as thermal sensor limitations, equipment availability, high costs and thermal imaging procedures can contribute to a non-viable operation.
Case Study 4: Red Palm Weevil
Rhynchophorus ferrugineus or better known as the red palm weevil (RPW) considered to be the world’s worst pest of palm trees (Abbas, 2010). According to DOA, 2007 the attack of RPW was first detected in Terengganu and had spread to 58 localities in all seven district of the states of Terengganu (DOA, 2011). In 2016 has been found in Perlis, Kedah, Pulau Pinang, Terengganu and Kelantan indicated drastic increase of RPW weevil (DOA, 2016).
The weevil is believed to be introduce by date palm trees which brought in across the border either for the date palm plantation or landscaping purposes without proper quarantine several years back (Wahizatul et. al., 2013). The weevil is a conceal tissue borer that attacks more than 26 palm species worldwide belonging to 16 genera, including coconut, oil palm and sago palm (EPPO, 2007)
Accessing and visual detection of the weevil infestation is difficult and almost impossible thus, an alternative have been evaluated. Soroker, 2013 has deployed a system to detect RPW larvae, the canopy temperature based on aerial thermal images using semi-automated procedures used to map potential infestation of RPW larvae caused water stress, which was reflected by both higher canopy temperature extracted from thermal images and lower stomata conductance compared with healthy trees.
The water stress was detected 25 days after infestation, three weeks before visual symptoms were observed (Figure 7). The thermal system is used in green house to collect thermal images, while Golomb (2015), applied thermal system in the field, the main goal of the study was to examine the ability to detect infected trees using thermal images. By measurements, imaging and analysing of infected and uninfected trees over multi-year experiments in quarantine and commercial orchards, results was (partially showed that the RPW creates water stress and affects canopy temperature. Analysis of the aerial thermal image above date palm plantation successfully detected the infected trees, which was similar to Soroker (2013) results.
Figure 7: Thermal images of palm trees infected and uninfected by RPW.
Figure 8: Thermal system for RPW detection in the Field Figure 9: Thermal system for RPW detection in the Green House
Discussion and Conclusion
The application of thermal remote sensing application was developed and introduced in 1960’s, mainly to monitor thermal bridging in the buildings and overheating processes such as engine and electronic devices and the energy industries. Due to reduction of costs of the equipment and simple application techniques, it creates an opportunities in area of agriculture and currently have been used in precision agricultures (Prakash, 2000).
Thermal imaging was a better alternative tools for many application in agriculture, starting from pre-nursery, nursery, irrigation scheduling (Jones, 1999) yield forecasting (Stajnko et.al., 2004) harvesting, green house, termite attack, farm machinery and post-harvest operations and bruise detection (Varith et. al. 2003). Several utilisations in metrology with pest management may be conducted efficiently.
However, in contrary with earlier statement with the used of thermal imaging in reality not getting much attention by researcher as well as agriculturist due to reasons which led reduce in using. The system was seen as an expensive due to camera price and limits the application only to laboratory settings and high value target analysis. Further weather condition in the field limits the automation of thermal data and often imaging sensor calibration and atmospherics correction are a must. Thermal imaging need to be improved in time and more research need to be conducted.
Infra-red or IR imaging may be an option or perhaps the combination of both thermal and IR application in some cases may be a solution. With the invention of enhanced thermal sensor cameras will bring more interest and challenge in this relatively less explores field. There are a definite need to get to more understanding thermal data by scientific and application. The development should be focuses on fundamental and principle of thermal remote sensing, laboratory measurement and spectral response of natural materials in the thermal infrared region which lead to a more precise and sophisticated sensor technology.
Review on case study reveals that thermal imaging will be appropriate with present in large animal such as wildlife and large insect especially termites. Study by MOPB for monitoring or census on the infestation of bagworm were on infested palm leaves whereby when monitoring was conducted it has already perhaps at the late stages. However a combination of conventional methods such as observation and IR images may be a good practices if plantation staff and personal aware of bag worm present at early stages. IR imaging method may be used to quantify the infestation stages.
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