Nondestructive quality evaluation and monitoring of Braeburn apples by Spatially Resolved Spectroscopy.

Contact Spatially Resolved Spectroscopy (SRS) measurements by means of a fiber-optics probe were employed for nondestructive assessment and monitoring of Braeburn apples during shelflife storage. SRS measurements and estimation of optical properties were calibrated and validated by means of liquid optical phantoms with known optical properties and a metamodeling method. The acquired optical properties (absorption and reduced scattering coefficients) for the apples during shelf-life storage were found to provide useful information for nondestructive evaluation of apple quality attributes (firmness and SSC) and for monitoring the changes in their microstructure and chemical composition. On-line SRS measurement was achieved by mounting the SRS probe over a conveyor syste

Real-time canola damage detection: An end-to-end framework with semi-automatic crusher and lightweight ShuffleNetV2_YOLOv5s

The current method employed in detecting damages present in canola kernels is inefficient and time-consuming. The sample preparation process is laborious and the judgment between sound and damaged seeds using visual methods is prone to errors as they are small and indistinguishable. To date, there is no hardware and supporting software solution that can expedite this time-consuming yet crucial task. This study demonstrates an end-to-end damage detection framework that has two components: a semi-automatic machine to crush the canola seeds to prepare the samples rapidly for detecting the damages and a supporting object detection algorithm based on a compressed YOLOv5s model. The lightweight detection model was deployed in an Edge-AI device and integrated with the crusher to detect the damages in real-time. Two Convolutional Neural Network (CNN) architectures, viz. ShuffleNetV2 and MobileNetV3 were compared in terms of model parameters, computational cost, and model size to replace the standard CSPDarknet53 CNN backbone present in YOLOv5s. The best-performing model was deployed into an NVIDIA Jetson Nano embedded device for real-time inferencing. Results indicate that in terms of model size, the ShuffleNetV2_YOLOv5s model was 56.5 and 80.4 % smaller than the MobileNetV3_YOLOv5s and the baseline YOLOv5s models, respectively. While, in terms of computational cost, the ShuffleNetV2_YOLOv5s model was 64.1 % and 99.5 % less expensive than the MobileNetV3_YOLOv5s and the baseline YOLOv5s models, respectively. This study demonstrated an end-to-end framework for detecting damages in canola supported by a real-time and lightweight damage detection model

Spatially resolved diffuse reflectance in the visible and near-infrared wavelength range for non-destructive quality assessment of Braeburn apples

Spectroscopic measurements in the visible and near infrared wavelength range have achieved success in non-destructive assessment of apple quality attributes contributed by chemical components inside the fruit such as sweetness. Nevertheless, the evaluation of quality attributes related to texture of the fruit (e.g. firmness) still remains a challenge. One of the proposed solutions is to acquire and utilize separately scattering and absorption information from spectroscopic readings for quality prediction. Since scattering is related to fruit microstructure and absorption is caused by chemical composition, construction of multivariate calibration models from these optical properties to predict corresponding quality parameters of interest could be a solution for this, and also have potential for non-destructive monitoring of fruit quality from harvest to consumption. In this research, a setup for contact spatially resolved diffuse reflectance measurements in the 500-1000nm range based on a fibre-optics probe was elaborated for the measurement of optical properties (absorption coefficient μa and reduced scattering coefficient μ's) of 'Braeburn' apples. After calibration and validation of the setup on a set of liquid optical phantoms covering the relevant range of optical properties, thirty 'Braeburn' apples were measured before and after shelf-life storage (2 weeks at 18°C in normal atmosphere) with the setup and were analyzed for the main quality attributes (firmness and soluble solids content (SSC)). The estimated μa spectra of the apples indicated chlorophyll degradation during shelf-life storage. PLS models were investigated for apple quality prediction by using estimated optical properties spectra or diffuse reflectance spectra. These spectra covered information on chlorophyll and some carbohydrate and water absorption. The μa spectra also proved better than μ's spectra for predicting SSC and firmness (R2-SSC=0.81; RMSEP(SSC)=0.69%; and R2-firmness=0.71; RMSEP(firmness)=9.68N). The combined μa and μ's spectra did not improve the prediction accuracies as compared to the μa spectra alone. The diffuse reflectance spectra of the detection fibres did not provide a significantly better prediction performance for SSC, but gave slightly better firmness prediction (R2-firmness=0.73-0.83; RMSEP(firmness)=8.91-13.70N) than the μa spectra. © 2013 Elsevier B.V.publisher: Elsevier articletitle: Spatially resolved diffuse reflectance in the visible and near-infrared wavelength range for non-destructive quality assessment of ‘Braeburn’ apples journaltitle: Postharvest Biology and Technology articlelink: http://dx.doi.org/10.1016/j.postharvbio.2013.12.004 content_type: article copyright: Copyright © 2013 Elsevier B.V. All rights reserved.status: publishe

Hyperspectral scatter imaging for contactless food quality evaluation

status: publishe

Contactless and non-destructive differentiation of microstructures of sugar foams by hyperspectral scatter imaging

A hyperspectral scatter imaging system was developed for the contactless acquisition of spatially resolved diffuse reflectance profiles for the optical characterization of turbid food products in the wavelength range from 500 to 960 nm. To investigate the potential of this concept sugar foams with different microstructures, but with similar chemical compositions, have been prepared by applying different mixing times to the same mixtures of sugar and albumin. Hyperspectral scatter images have been acquired from these samples and the absorption and reduced scattering coefficients have been derived from spatially resolved reflectance profiles based on the diffusion approximation of the radiative transfer equation describing the light propagation in turbid media. The estimated reduced scattering coefficients μs′ spectra clearly reflected the effect of the different mixing times on the foam microstructure. On the other hand, similar absorption coefficient spectra were observed, confirming the identical chemical composition of the sugar–albumin matrix. These results indicate that the hyperspectral scatter imaging technique has potential as a non-contact and rapid method for online quality control and process monitoring of foamed food products.publisher: Elsevier articletitle: Contactless and non-destructive differentiation of microstructures of sugar foams by hyperspectral scatter imaging journaltitle: Innovative Food Science & Emerging Technologies articlelink: http://dx.doi.org/10.1016/j.ifset.2013.08.007 content_type: article copyright: Copyright © 2013 Elsevier Ltd. All rights reserved.status: publishe

Estimation of bulk optical properties of turbid media from hyperspectral scatter imaging measurements: Metamodeling approach

In many research areas and application domains, the bulk optical properties of biological materials are of great interest. Unfortunately, these properties cannot be obtained easily for complex turbid media. In this study, a metamodeling approach has been proposed and applied for the fast and accurate estimation of the bulk optical properties from contactless and non-destructive hyperspectral scatter imaging (HSI) measurements. A set of liquid optical phantoms, based on intralipid, methylene blue and water, were prepared and the Vis/NIR bulk optical properties were characterized with a double integrating sphere and unscattered transmittance setup. Accordingly, the phantoms were measured with the HSI technique and metamodels were constructed, relating the Vis/NIR reflectance images to the reference bulk optical properties of the samples. The independent inverse validation showed good prediction performance for the absorption coefficient and the reduced scattering coefficient, with R2 values of 0.980 and 0.998, and RMSEP values of 0.032 cm-1 and 0.197 cm-1. respectively. The results clearly support the potential of this approach for fast and accurate estimation of the bulk optical properties of turbid media from contactless HSI measurements.status: publishe

Metamodeling approach for efficient estimation of optical properties of turbid media from spatially resolved diffuse reflectance measurements

A metamodeling approach is introduced and applied to efficiently estimate the bulk optical properties of turbid media from spatially resolved spectroscopy (SRS) measurements. The model has been trained on a set of liquid phantoms covering a wide range of optical properties representative for food and agricultural products and was successfully validated in forward and inverse mode on phantoms not used for training the model. With relative prediction errors of 10% for the estimated bulk optical properties the potential of this metamodeling approach for the estimation of the optical properties of turbid media from spatially resolved spectroscopy measurements has been demonstrated.status: publishe

Non-destructive characterization of food microstructure and composition by Spatially Resolved Spectroscopy

status: publishe

Nondestructive quality evaluation and monitoring of Braeburn apples by Spatially Resolved Spectroscopy

status: publishe