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This study investigated thermal aspect potentials of date palm (Phoenix dactylifera (Linnaeus) (Arecaceae)) infested by red palm weevil (Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae)) in early detection. Palms were forced infested, i.e., fertile females and males were introduced inside the palms to initiate infestation. Effects of three infestation intensities on date palm were examined throughout a 24-day period. Temperature gradients inside infested and healthy palms of the commercial cultivar (Khalas) were determined using data loggers. Adult weevils and loggers were introduced inside holes drilled in palm trunks for measuring temperatures at 15-minute intervals during 24 consecutive days. These 24 days after infestation is the larval stage where most of the damage occurs and the infested palms can still be rescued through remedial control measures. A repeated measures analysis showed that the temperature of infested palms during the two seasons of the study were 33.22 °C and 30.08 °C, while for the healthy palms were 31.83 °C and 27.56 °C. Differences were significant during the first (F=6.14, df=3, P=0.009) and the second (F=3.89, df=3, P=0.038) season. The corresponding ambient atmosphere temperatures were 31.83 °C and 28.03 °C, respectively. This study provides valuable baseline information for developing a real-time sensor fusion system for a nondestructive early detection of insect infestation.

Cadra (Ephestia) cautella (Walker) is a moth that attacks dates from ripening stages while on tree, throughout storage, and until consumption, causing enormous qualitative and quantitative damages, resulting in economic losses. Image-processing algorithms were developed for detecting and differentiating between three Cadra egg categories based on the success of Trichogramma bourarachae (Pintureau and Babaul) parasitization. These categories were parasitized (black and dark red), unparasitized fertile unhatched (yellow), and unparasitized hatched (white) eggs. Color, light intensity, and shape information was used to develop detection algorithms. Two image processing methods were developed based on three randomly selected images and were tested on a larger validation image set of 40 images: (i) segmentation and extractions of color and morphological features followed by Watershed delineation, and is referred to as Algorithm 1 (ALGO1), (ii) finding circular objects by Hough Transformation followed by convolution filtering, and is referred to as Algorithm 2 (ALGO2). ALGO1 and ALGO2 achieved correct classification rates (CCRs) for parasitized eggs of 92% and 96%, respectively. Their CCRs for unhatched eggs were 48% and 94%, and for hatched eggs were 42% and 73%, respectively. Regarding parasitized eggs, both methods performed satisfactorily, but, in general, ALGO2 outperformed ALGO1. These results ensure automatic evaluation of the efficiency of biological control of Cadra cautella by the egg parasitoid Trichogramma bourarachae by quantifying the rate of parasitization. The developed detection methods can be used by producers of biocontrol agents for online monitoring of Trichogramma and similar insect natural enemies during mass production and before release against crop pests. Moreover, with few adjustments these methods can be used in similar applications such as detecting plant diseases.

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