Thermal cameras and applications: a survey <s> Agriculture and food <s> Abstract The feasibility of using an infrared thermal imaging system to identify the fungal infection in stored wheat was studied. Thermal images of bulk wheat grains infected by Aspergillus glaucus group, Aspergillus niger van Tieghem and Penicillium spp. were obtained using an un-cooled focal planar array type infrared thermal camera after heating grain for 180 s with a plate heater placed 10 mm above the grain and maintained at 90 °C, and then cooling in ambient air for 30 s. In total, twelve temperature features were derived from heated and cooled wheat and four-way and pair-wise classification models were developed by linear and quadratic discriminant analyses (LDA and QDA). Leave-one-out and bootstrapping methods were used to validate the developed classification models. Pair-wise LDA and QDA classification models gave a maximum accuracy of 100% for healthy samples and more than 97% and 96% for infected samples, respectively. Four-way LDA and QDA classification models yielded relatively low classification accuracies for fungus-infected samples due to the non-significant changes in the temperature features between grain samples infected with different species of fungi. <s> BIB001 </s> Thermal cameras and applications: a survey <s> Agriculture and food <s> Thermal imaging is a technique to convert the invisible radiation pattern of an object into visible images for feature extraction and analysis. Infrared thermal imaging was first developed for military purposes but later gained a wide application in various fields such as aerospace, agriculture, civil engineering, medicine, and veterinary. Infrared thermal imaging technology can be applied in all fields where temperature differences could be used to assist in evaluation, diagnosis, or analysis of a process or product. Potential use of thermal imaging in agriculture and food industry includes predicting water stress in crops, planning irrigation scheduling, disease and pathogen detection in plants, predicting fruit yield, evaluating the maturing of fruits, bruise detection in fruits and vegetables, detection of foreign bodies in food material, and temperature distribution during cooking. This paper reviews the application of thermal imaging in agriculture and food industry and elaborates on the potential of thermal imaging in various agricultural practices. The major advantage of infrared thermal imaging is the non-invasive, non-contact, and non-destructive nature of the technique to determine the temperature distribution of any object or process of interest in a short period of time. <s> BIB002
Thermal imaging systems have various applications in the agriculture and food industry. They are suitable in the food industry due to their portability, real-time imaging, and noninvasive and non-contact temperature measurement capability [59] . In food quality measurement, it is important to use a non-destructive method to avoid waste. The two papers BIB002 and [59] reviewed the use of thermal imaging in the agriculture and food industry, including both passive thermography (measuring the temperature of the scene) and active thermography (adding thermal energy to an object, and then measuring the temperature). Passive thermography is mostly used for temperature control in food manufacturing and for monitoring heat processes. Active thermography of food objects can give information about the quality, such as damage and bruises in fruits and vegetables. Bruises can be detected using active thermal imaging, due to different thermodynamic properties in sound and bruised tissue. Thermal imaging has been applied in BIB001 to detect fungal infections in stored wheat. It could discriminate between healthy and infected wheat, but not between different fungal species. In [93], they classified healthy and fungal infected pistachio kernels.