A Nondestructive Eggshell Thickness Measurement Technique Using Terahertz Waves

Eggshells play a number of important roles in the avian and reptile kingdom: protection of internal contents and as a major source of minerals for developing embryos. However, when researching these respective roles, eggshell thickness measurement remains a bottleneck due to the lack of a non-destructive measurement techniques. As a result, many avian and reptile research protocols omit consideration of eggshell thickness bias on egg or embryo growth and development. Here, we validate a non-destructive method to estimate eggshell thickness based on terahertz (THz) reflectance spectroscopy using chicken white coloured eggs. Since terahertz waves are reflected from outer air-eggshell interface, as well as the inner eggshell-membrane boundary, the resulting interference signals depend on eggshell thickness. Thus, it is possible to estimate shell thickness from the oscillation distance in frequency-domain. A linear regression-based prediction model for non-destructive eggshell thickness measurement was developed, which had a coefficient of determination (R2) of 0.93, RMSEP of 0.009, RPD of 3.45 and RER 13.67. This model can estimate eggshell thickness to a resolution of less than 10 μm. This method has the potential to expand the protocols in the field of avian and reptile research, as well as be applied to industrial grading of eggs

External Defects and Soil Deposits Identification on Potato Tubers using 2CCD Camera and Principal Component Images

Precise recognition of potato external defects and the ability to identify defects and non-defect areas are in demand. Common scab represents a significant issue that requires detection, yet identifying the extent of common scab infection remains challenging when using a standard RGB camera. In this research, a 2CCD camera system that could obtain a set of RGB and near-infrared images, which could enhance defect detection, has been used. Image segmentation strategies based on a single principal component image and the principal component pseudo-colored image have been proposed to identify external potato defects while excluding soil deposits on the potato surface, often recognized as defects by the normal color machine vision system. Performance metrics calculation results show relatively good results, with segmentation true accuracy around 64% for both methods. Principal component pseudo-colored images were able to discriminate defects area and soil deposits in a single image. The methods presented in this paper could be used as the basis to develop further classification and grading algorithms

Static and dynamic evaluations of acoustic positioning system using TDMA and FDMA for robots operating in a greenhouse

Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy, low cost, and ability of extensive greenhouse coverage. Spread Spectrum Sound-based local positioning system (SSSLPS) was proposed to be a navigation tool for multiple agricultural robots by the authors' research team. However, to increase the system capacity for positioning multiple robots in a greenhouse, the near-far problem caused by the interference between speakers needs to be overcome. The use of different access methods, Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA), is essential in the SSSLPS system for solving the near-far problem. The static positioning in a greenhouse was first evaluated by setting different parameters to determine the optimal signal setting for a dynamic experiment. From that, the moving robot tests were added with a motion capture system and tested the performance of TDMA and FDMA. The results demonstrated that TDMA can be used in a stationary sound-based positioning system with 12.2 mm accuracy, but it has a time delay problem in dynamic positioning. A simulation was designed to mimic the position error increases with different moving speeds. Although FDMA has the sound damping problem in high-frequency regions creating a peak detection issue, it achieved a higher accuracy with an average position error of 62.1 mm compared to 180.3 mm of TDMA. This study shows that the TDMA method is suitable for static measurements, while the FDMA method is suitable for measuring dynamic objects and controlling mobile robots

Broadband dielectric spectroscopy of glucose aqueous solution: Analysis of the hydration state and the hydrogen bond network.

Recent studies of saccharides' peculiar anti-freezing and anti-dehydration properties point to a close association with their strong hydration capability and destructuring effect on the hydrogen bond (HB) network of bulk water. The underlying mechanisms are, however, not well understood. In this respect, examination of the complex dielectric constants of saccharide aqueous solutions, especially over a broadband frequency region, should provide interesting insights into these properties, since the dielectric responses reflect corresponding dynamics over the time scales measured. In order to do this, the complex dielectric constants of glucose solutions between 0.5 GHz and 12 THz (from the microwave to the far-infrared region) were measured. We then performed analysis procedures on this broadband spectrum by decomposing it into four Debye and two Lorentz functions, with particular attention being paid to the β relaxation (glucose tumbling), δ relaxation (rotational polarization of the hydrated water), slow relaxation (reorientation of the HB network water), fast relaxation (rotation of the non-HB water), and intermolecular stretching vibration (hindered translation of water). On the basis of this analysis, we revealed that the hydrated water surrounding the glucose molecules exhibits a mono-modal relaxational dispersion with 2-3 times slower relaxation times than unperturbed bulk water and with a hydration number of around 20. Furthermore, other species of water with distorted tetrahedral HB water structures, as well as increases in the relative proportion of non-HB water molecules which have a faster relaxation time and are not a part of the surrounding bulk water HB network, was found in the vicinity of the glucose molecules. These clearly point to the HB destructuring effect of saccharide solutes in aqueous solution. The results, as a whole, provide a detailed picture of glucose-water and water-water interactions in the vicinity of the glucose molecules at various time scales from sub-picosecond to hundreds of picoseconds

Autofluorescence changes of tomato surface tissues during overripening

We investigated the autofluorescence of tomato surface tissues during overripening at 25 °C for 13 days. Microscopic images and fluorescence spectra of tissues, including the epidermis and cuticle, were examined (excitation at 360 nm), revealing that the autofluorescence changes were related to the epidermis, particularly the fluorophores in the cuticle

Monitoring mature tomato (red stage) quality during storage using ultraviolet-induced visible fluorescence image

The potential of UV-induced fluorescence imaging was investigated as a non-destructive tool to monitor postharvest quality degradation of tomatoes harvested at the red stage and stored at 25 °C. The fluorescence images (excitation at 365 nm) were found to be a better indicator of tomato quality degradation than color images after color saturation. Tomatoes were stored at 25 °C for 9 d. The changes in color and fluorescence of tomato were evaluated by two types of images: Color and fluorescence images. A conventional colorimeter was also used for as a reference. Changes in the RGB ratio for these two types of images were opposite. In the color images, the G ratio decreased rapidly for the initial 3 or 5 d and then stabilized afterwards. On the other hand, in the fluorescence images, the G ratio increased continuously up to 9 d. Given that temperature conditions during transportation and storage of tomatoes is not always ideal, the results from this research provide the foundation for developing a postharvest monitoring system of mature tomato quality degradation

Effect of relative humidity and light exposure on fluorescence compound dynamics, soluble solid and acidity of Japanese Citrus Iyokan during postharvest treatment

The Miyauchi iyokan (iyokan) citrus fruit is typically harvested in late December to prevent damage from the winter weather. At the time of harvest, the ratio of Soluble Solids (SS) to acid content is generally low, commonly used to assess the quality of the juice. Therefore, the goal during postharvest treatment is to decrease the acid content and improve the SS levels. The quality of citrus can be influenced by environmental factors such as relative humidity (RH) and exposure to light, so it is important to monitor their effects. Hence, this study aims to observe the changes in internal quality indicators, such as the SS/acid ratio and fluorescence compounds, under different RH and light conditions to understand how the citrus characteristics are affected. The postharvest treatment involved storing the citrus fruit at temperatures between 5-10°C for two months under various conditions i.e., in the dark and exposed to light, with high RH (80-90%) and low RH (40-50%). The SS/acid ratio did not show significant changes during the two months of storage under any treatments. However, the high RH condition resulted in a slightly higher SS/acid ratio. Similarly, the Tryptophan-like compound did not exhibit any significant response to the different treatments. However, the intensity of fluorescence from polymethoxylated flavones (PMFs) was higher in the dark treatment compared to the light treatment. PMFs play various roles in signaling and defense mechanisms in plants. Additionally, there was a notable increase in PMFs after thirty days of storage, indicating a response to light-induced stress

Classification of Soymilk and Tofu with Diffuse Reflection Light Using a Deep Learning Technique

Tofu is an ancient soybean product that is produced by heating soymilk containing a coagulation agent. Owing to its benefits to human health, it has become popular all over the world. An important index that determines the final product’s (tofu’s) quality is firmness. Coagulants such as CaSO4 and MgCl2 affect the firmness. With the increasing demand for tofu, a monitoring methodology that ensures high-quality tofu is needed. In our previous paper, an opportunity to monitor changes in the physical properties of soymilk by studying its optical properties during the coagulation process was implied. To ensure this possibility, whether soymilk and tofu can be discriminated via their optical properties should be examined. In this study, a He–Ne laser (Thorlabs Japan Inc., Tokyo, Japan, 2015) with a wavelength of 633 nm was emitted to soymilk and tofu. The images of the scattered light on their surfaces were discriminated using a type of deep learning technique. As a result, the images were classified with an accuracy of about 99%. We adjusted the network architecture and hyperparameters for the learning, and this contributed to the successful classification. The construction of a network that is specific to our task led to the successful classification result. In addition to this monitoring method of the tofu coagulation process, the classification methodology in this study is worth noting for possible use in many relevant agricultural fields

Estimation of Citrus Maturity with Fluorescence Spectroscopy Using Deep Learning

To produce high-quality citrus, the harvest time of citrus should be determined by considering its maturity. To evaluate citrus maturity, the Brix/acid ratio, which is the ratio of sugar content or soluble solids content to acid content, is one of the most commonly used indicators of fruit maturity. To estimate the Brix/acid ratio, fluorescence spectroscopy, which is a rapid, sensitive, and cheap technique, was adopted. Each citrus peel was extracted, and its fluorescence value was measured. Then, the fluorescent spectrum was analyzed using a convolutional neural network (CNN). In fluorescence spectroscopy, a matrix called excitation and emission matrix (EEM) can be obtained, in which each fluorescence intensity was recorded at each excitation and emission wavelength. Then, by regarding the EEM as an image, the Brix/acid ratio of juice from the flesh was estimated via performing a regression with a CNN (CNN regression). As a result, the Brix/acid ratio absolute error was estimated to be 2.48, which is considerably better than the values obtained by the other methods in previous studies. Hyperparameters, such as depth of layers, learning rate, and the number of filters used for this estimation, could be observed using Bayesian optimization, and the optimization contributed to the high accuracy

Identification of UV-fluorescence components associated with and detection of surface damage in green pepper (Capsicum annum L)

Fluorescence imaging has been used to detect fruit surface damage, but has not yet been applied to vegetables, such as green pepper. In this report, we extract and identify fluorescent components from the exocarp (skin) of green pepper. The fluorescence excitation and emission wavelengths of these extracted compounds were determined using a fluorescence spectrophotometer and identified using nuclear magnetic resonance spectroscopy and mass spectrometry. Red and blue fluorescent components with excitation and emission wavelengths 667 – 685 nm and 400 - 438 nm respectively, were found. In subsequent research, the red fluorescent compounds were targeted, as these compounds have a higher fluorescence intensity, around 97 a.u. Pheophytin a is one of these red fluorescent compounds, appearing in the mass spectrum at 871 m/z. Furthermore, when a fluorescence imaging system was set up, with halogen illumination, it was shown that this system could successfully detect surface damage in green pepper