Determining wood chip size: image analysis and clustering methods

One of the standard methods for the determination of the size distribution of wood chips is the oscillating screen method (EN 15149- 1:2010). Recent literature demonstrated how image analysis could return highly accurate measure of the dimensions defined for each individual particle, and could promote a new method depending on the geometrical shape to determine the chip size in a more accurate way. A sample of wood chips (8 litres) was sieved through horizontally oscillating sieves, using five different screen hole diameters (3.15, 8, 16, 45, 63 mm); the wood chips were sorted in decreasing size classes and the mass of all fractions was used to determine the size distribution of the particles. Since the chip shape and size influence the sieving results, Wang’s theory, which concerns the geometric forms, was considered. A cluster analysis on the shape descriptors (Fourier descriptors) and size descriptors (area, perimeter, Feret diameters, eccentricity) was applied to observe the chips distribution. The UPGMA algorithm was applied on Euclidean distance. The obtained dendrogram shows a group separation according with the original three sieving fractions. A comparison has been made between the traditional sieve and clustering results. This preliminary result shows how the image analysis-based method has a high potential for the characterization of wood chip size distribution and could be further investigated. Moreover, this method could be implemented in an online detection machine for chips size characterization. An improvement of the results is expected by using supervised multivariate methods that utilize known class memberships. The main objective of the future activities will be to shift the analysis from a 2-dimensional method to a 3- dimensional acquisition process

Morphological variation on tomato leaves due to different nitrogen contents

Elliptic Fourier Analysis (EFA) is a method used to quantify shape differences.  It mathematically describes the entire shape of an object by transforming the contour into Fourier coefficients, used as variables for statistical analysis, and involving the fitting of some type of curve to the object outline.  Generally, the shape of agricultural products such as fruit, vegetables, grain and in addition other organs of plant is one of the most important factors for their classification and grading in relation to commercial quality and organoleptic properties.  The aim of this study is to quantify the morphological variation of the shape of tomato leaves in response to their different nitrogen (N) content using the EFA coefficients, the fractal geometry and the perimeter ratio in combination with the Partial Least Squares Discriminant Analysis (PLS-DA).  The analyses were realized on a tomato crop where each sample was chemically analyzed at the laboratory to establish the N content.  The leaves (168) were divided into 3 groups following different N concentrations.  Results suggest no relation between leaves lengths and N concentration is present following the Kruskal-Wallis performed with a p=0.735.  The PLS-DA performing on the EFA coefficients, fractal index and perimeter ratio shows a high sensitivity, sensibility, and reduced mean classification error (82.3%, 81.07% and 18.3% respectively).  The percentages of the correct classification in the model resulted to be 69.29% while the independent test equal to 56.1%.  This study demonstrated the relation between leaf shape and N content (expressed in 3 concentration groups).Keywords: Tomato leaf, elliptic Fourier analysis, fractal index, perimeter ratio, partial least squares discriminant analysis

Neinvazivna metoda za utvrđivanje organski gajene ribe

U poslednjih nekoliko godina, prisutne su drugačije tendencije u akvakulturi, koje pre svega imaju za cilj plasiranje novih proizvoda, od kojih je jedan i riba gajena u organskoj akvakulturi. Razlikovanje ribe gajene u organskoj akvakulturi od one gajene na konvencionalni način je teško, ali se razlika može napraviti preko njenog izgleda. U ovom eksperimentu brancin je hranjen konvencionalnom i organskom hranom i u toku gajenja, pravljene su fotografije primeraka. Nakon kalibracije boje, određene su merne tačke na svakoj fotografiji, a nakon toga su geometrijskim i morfometrijskim metodama dobijene RGB matrice. Tako dobijena matrica (195x135,225) je prvobitno analizirana korišćenjem 50-50 MANOVA metode, a nakon toga su urađeni diskriminantna analiza i na kraju dendrogram. Svi uzorci su klasifikovani korišćenjem tri diskriminantna modela. Tako je dendrogram sa ukupno 9 različitih klasa pokazao da se ribe koje su gajene u organskoj akvakulturi slične ribama uzorkovanim iz prirodnih populacija. Rezultati su pokazali i da dve grupe riba, hranjenih različitim komercijalnim hranama u ovom eksperimentu, jedne u organskoj, a druge u konvencionalnoj akvakulturi mogu biti prepoznate po boji njihovog tela. Šta više, što duže vremena ribe provedu u jednom od ova dva načina gajenja, to se boja njihovog tela više razlikuje. Deo tela koji pokazuje najveće promene u boji jeste glava, koja je značajno svetlije boje u grupi riba gajenih u organskoj akvakulturi. Tako je dokazano da analiza boje tela može biti iskorišćena za razlikovanje riba koje su gajene u drugačijim uslovima korišćenjem različitih protokola i načina gajenja. Međutim, ovaj zaključak se može primeniti samo na ove, konkretne podatke, ne može biti generalizovan i ne može se primeniti na sve ribe gajene u organskoj akvakulturi

A Novel Morphometry-Based Protocol of Automated Video-Image Analysis for Species Recognition and Activity Rhythms Monitoring in Deep-Sea Fauna

The understanding of ecosystem dynamics in deep-sea areas is to date limited by technical constraints on sampling repetition. We have elaborated a morphometry-based protocol for automated video-image analysis where animal movement tracking (by frame subtraction) is accompanied by species identification from animals' outlines by Fourier Descriptors and Standard K-Nearest Neighbours methods. One-week footage from a permanent video-station located at 1,100 m depth in Sagami Bay (Central Japan) was analysed. Out of 150,000 frames (1 per 4 s), a subset of 10.000 was analyzed by a trained operator to increase the efficiency of the automated procedure. Error estimation of the automated and trained operator procedure was computed as a measure of protocol performance. Three displacing species were identified as the most recurrent: Zoarcid fishes (eelpouts), red crabs (Paralomis multispina), and snails (Buccinum soyomaruae). Species identification with KNN thresholding produced better results in automated motion detection. Results were discussed assuming that the technological bottleneck is to date deeply conditioning the exploration of the deep-sea

Plant Phenotyping Research Trends, a Science Mapping Approach

Modern plant phenotyping, often using non-invasive technologies and digital technologies, is an emerging science and provides essential information on how genetics, epigenetics, environmental pressures, and crop management (farming) can guide selection toward productive plants suitable for their environment. Thus, phenotyping is at the forefront of future plant breeding. Bibliometric science mapping is a quantitative method that analyzes scientific publications throughout the terms present in their title, abstract, and keywords. The aim of this mapping exercise is to observe trends and identify research opportunities. This allows us to analyze the evolution of phenotyping research and to predict emerging topics of this discipline. A total of 1,827 scientific publications fitted our search method over the last 20 years. During the period 1997–2006, the total number of publications was only around 6.1%. The number of publications increased more steeply after 2010, boosted by the overcoming of technological bias and by a set of key developments at hard and software level (image analysis and data storage management, automation and robotics). Cluster analysis evidenced three main groups linked to genetics, physiology, and imaging. Mainly the model plant “Arabidopsis thaliana” and the crops “rice” and “triticum” species were investigated in the literature. The last two species were studied when addressing “plant breeding,” and “genomic selection.” However, currently the trend goes toward a higher diversity of phenotyped crops and research in the field. The application of plant phenotyping in the field is still under rapid development and this application has strong linkages with precision agriculture. EU co-authors were involved in 41.8% of the analyzed papers, followed by USA (15.4%), Australia (6.0%), and India (5.6%). Within the EU, coauthors were mainly affiliated in Germany (35.8%), France (23.7%), and United Kingdom (18.4%). Time seems right for new opportunities to incentivize research on more crops, in real field conditions, and to spread knowledge toward more countries, including emerging economies. Science mapping offers the possibility to get insights into a wide amount of bibliographic information, making them more manageable, attractive, and easy to serve science policy makers, stakeholders, and research managers

Potencial applications of automated video-image analysis in the pelagic and demersal environment including the deep-sea

Peer ReviewedPostprint (published version

A New Laboratory Radio Frequency Identification (RFID) System for Behavioural Tracking of Marine Organisms

Radio frequency identification (RFID) devices are currently used to quantify several traits of animal behaviour with potential applications for the study of marine organisms. To date, behavioural studies with marine organisms are rare because of the technical difficulty of propagating radio waves within the saltwater medium. We present a novel RFID tracking system to study the burrowing behaviour of a valuable fishery resource, the Norway lobster (Nephrops norvegicus L.). The system consists of a network of six controllers, each handling a group of seven antennas. That network was placed below a microcosm tank that recreated important features typical of Nephrops’ grounds, such as the presence of multiple burrows. The animals carried a passive transponder attached to their telson, operating at 13.56 MHz. The tracking system was implemented to concurrently report the behaviour of up to three individuals, in terms of their travelled distances in a specified unit of time and their preferential positioning within the antenna network. To do so, the controllers worked in parallel to send the antenna data to a computer via a USB connection. The tracking accuracy of the system was evaluated by concurrently recording the animals’ behaviour with automated video imaging. During the two experiments, each lasting approximately one week, two different groups of three animals each showed a variable burrow occupancy and a nocturnal displacement under a standard photoperiod regime (12 h light:12 h dark), measured using the RFID method. Similar results were obtained with the video imaging. Our implemented RFID system was therefore capable of efficiently tracking the tested organisms and has a good potential for use on a wide variety of other marine organisms of commercial, aquaculture, and ecological interest

A new colorimetrically-calibrated automated video-imaging protocol for day-night fish counting at the OBSEA coastal cabled observatory

Field measurements of the swimming activity rhythms of fishes are scant due to the difficulty of counting individuals at a high frequency over a long period of time. Cabled observatory video monitoring allows such a sampling at a high frequency over unlimited periods of time. Unfortunately, automation for the extraction of biological information (i.e., animals’ visual counts per unit of time) is still a major bottleneck. In this study, we describe a new automated video-imaging protocol for the 24-h continuous counting of fishes in colorimetrically calibrated time-lapse photographic outputs, taken by a shallow water (20 m depth) cabled video-platform, the OBSEA. The spectral reflectance value for each patch was measured between 400 to 700 nm and then converted into standard RGB, used as a reference for all subsequent calibrations. All the images were acquired within a standardized Region Of Interest (ROI), represented by a 2 × 2 m methacrylate panel, endowed with a 9-colour calibration chart, and calibrated using the recently implemented “3D Thin-Plate Spline” warping approach in order to numerically define color by its coordinates in n-dimensional space. That operation was repeated on a subset of images, 500 images as a training set, manually selected since acquired under optimum visibility conditions. All images plus those for the training set were ordered together through Principal Component Analysis allowing the selection of 614 images (67.6%) out of 908 as a total corresponding to 18 days (at 30 min frequency). The Roberts operator (used in image processing and computer vision for edge detection) was used to highlights regions of high spatial colour gradient corresponding to fishes’ bodies. Time series in manual and visual counts were compared together for efficiency evaluation. Periodogram and waveform analysis outputs provided very similar results, although quantified parameters in relation to the strength of respective rhythms were different. Results indicate that automation efficiency is limited by optimum visibility conditions. Data sets from manual counting present the larger day-night fluctuations in comparison to those derived from automation. This comparison indicates that the automation protocol subestimate fish numbers but it is anyway suitable for the study of community activity rhythms.Peer ReviewedPostprint (published version

Nitrogen Concentration Estimation in Tomato Leaves by VIS-NIR Non-Destructive Spectroscopy

Nitrogen concentration in plants is normally determined by expensive and time consuming chemical analyses. As an alternative, chlorophyll meter readings and N-NO3 concentration determination in petiole sap were proposed, but these assays are not always satisfactory. Spectral reflectance values of tomato leaves obtained by visible-near infrared spectrophotometry are reported to be a powerful tool for the diagnosis of plant nutritional status. The aim of the study was to evaluate the possibility and the accuracy of the estimation of tomato leaf nitrogen concentration performed through a rapid, portable and non-destructive system, in comparison with chemical standard analyses, chlorophyll meter readings and N-NO3 concentration in petiole sap. Mean reflectance leaf values were compared to each reference chemical value by partial least squares chemometric multivariate methods. The correlation between predicted values from spectral reflectance analysis and the observed chemical values showed in the independent test highly significant correlation coefficient (r = 0.94). The utilization of the proposed system, increasing efficiency, allows better knowledge of nutritional status of tomato plants, with more detailed and sharp information and on wider areas. More detailed information both in space and time is an essential tool to increase and stabilize crop quality levels and to optimize the nutrient use efficiency