Vibro-Acoustic Codling Moth Larvae Infestation Detection in Apples

Within recent years, the demand for organic produce has greatly increased due to many factors, including increasing knowledge about such things as dietary fiber and balanced gastrointestinal bacterial ecosystems. This increase in demand, coupled with the financial penalties for sending invasive species and pests across borders, presents a need for a scalable and accurate system to non-destructively detect infestation. The proposed work addresses this problem by testing the performance of a non-destructive vibro-acoustic method for detecting lava activity in apples. This involved 3 steps; design a mechanical data collection prototype for testing apples, a evaluate a set of features, and test the detection performance using machine learning algorithms. The mechanical data collection prototype aims to solve some of the issues that arose when collecting repeatable vibro-acoustic data from apples. The second piece aims to show the feasibility of a scalable model which takes vibro-acoustic data, performs multi-domain feature extraction, and then utilizes a SVM/ANN backend to detect codling moth infestation in apples. The final piece describes a procedure in which a novel CNN architecture pair is created to assess the quality of results with and without an acoustic reference channel. The data collection prototype produced higher quality data than previous setups. The feature extraction and SVM/ANN showed the ability to characterize patterns and detect infestation. The best of these was an SVM which had 87.34% accuracy on classifying 5 second segments from apples not in the training set, which was run on one iteration of a randomized dataset split. The CNN architectures showed potential for further development, with the noise-inclusive model performing over 8% better. However, both models show limited potential for generalizing to new apples with accuracies of (35.15% without noise, 43.92% with noise). The lower detection rates were limited by the intermittent larval activity rates, since the low accuracy rates were driven primarily by missed detections in the 5 second windows on apples labeled as infested. If the percentage of activity in any five second window is too low, then the “infested” sample will get classified as healthy due to that window having no larval sounds. The other notable issue regarding generalization potential was the sample size: the number of distinct apples used was too small, especially for deep learning applications. A much larger number of apples will be needed for future work

Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers\u27 expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects\u27 attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import-export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods\u27 application in the detection and classification of insect infestation in fruits and vegetables

Warwickshire Group (Pennsylvanian) red-beds of the Canonbie Coalfield, England-Scotland border, and their regional palaeogeographical implications

Late Carboniferous red-beds, < 700 m thick, at outcrop and in the subsurface of the Canonbie Coalfield can be assigned to the Warwickshire Group. They are preserved within the axial part of the Solway Syncline and are divisible into the Eskbank Wood, Canonbie Bridge Sandstone and Becklees Sandstone formations. Sedimentation largely took place on a well-drained alluvial plain, characterized mainly by early, primary oxidation of the strata. Large, northerly-flowing braided river systems were common, with overbank and floodplain fines deposited lateral to the channels; soils formed during intervals of low sediment aggradation. The Canonbie succession includes some of the youngest Carboniferous rocks preserved in the UK. Correlation of the Eskbank Wood Formation is equivocal, but using petrographical, heavy mineral, zircon age dating and palaeocurrent data, the Canonbie Bridge Sandstone Formation can be unambiguously correlated with the Halesowen Formation of Warwickshire, the Pennant Sandstone Formation of South Wales and the offshore Boulton Formation. This suggests that southerly-derived detritus travelled considerable distances from the Variscan highlands of Brittany and/or central Germany across the southern North Sea and UK areas, to a position some hundreds of kilometres north of that previously recognized. The Becklees Sandstone Formation has much in common with the Salop Formation of the English Midlands. It appears to have no preserved equivalent elsewhere in the UK or in the UK sector of the southern North Sea but resembles stratigraphically higher parts of the southern North Sea succession seen in the Dutch sector