There are several destructive and nondestructive methods for quality evaluation of agricultural products. Most of the employed traditional techniques are time-consuming and involve considerable degree of manual works. Destructive methods provide reasonable success rate of quality determination of fruits; however, they practically have many concerns about effectiveness, time, and cost. Therefore, developing portable, fast, and cost-effective techniques without harming fruits are desired for fruit quality evaluation. This work aims to develop a complete nondestructive quality evaluation system with (a) ultrasonic testing and (b) volume estimation by automatic machine vision techniques. The ultrasonic system consisted of a programmable bipolar remote pulser unit, a couple of piezoelectric probes for ultrasonic signal acquisitions as a transmitter and a receiver, an oscilloscope, and a computer. Visual appearance (size/volume) was determined using a machine vision system based on image processing techniques. Five different images of a fruit from different angles were captured by high-resolution digital cameras. Volume of the fruit was computed after horizontal and vertical distance of the fruit’s images captured. The calculated volume values by the computer vision system are validated with the theoretical values. Although nondestructive ultrasonic estimation and volume estimation by image processing methods are cheap, fast, and practical, the results obtained in our experiments concluded that these methods are not as reliable as claimed in the literature.

This paper presents fabrication and packaging of a capacitive micromachined ultrasonic transducer (CMUT) using anodically bondable low temperature co-fired ceramic (LTCC). Anodic bonding of LTCC with Au vias-silicon on insulator (SOI) has been used to fabricate CMUTs with different membrane radii, 24 µm, 25 µm, 36 µm, 40 µm and 60 µm. Bottom electrodes were directly patterned on remained vias after wet etching of LTCC vias. CMUT cavities and Au bumps were micromachined on the Si part of the SOI wafer. This high conductive Si was also used as top electrode. Electrical connections between the top and bottom of the CMUT were achieved by Au-Au bonding of wet etched LTCC vias and bumps during anodic bonding. Three key parameters, infrared images, complex admittance plots, and static membrane displacement, were used to evaluate bonding success. CMUTs with a membrane thickness of 2.6 µm were fabricated for experimental analyses. A novel CMUT-IC packaging process has been described following the fabrication process. This process enables indirect packaging of the CMUT and integrated circuit (IC) using a lateral side via of LTCC. Lateral side vias were obtained by micromachining of fabricated CMUTs and used to drive CMUTs elements. Connection electrodes are patterned on LTCC side via and a catheter was assembled at the backside of the CMUT. The IC was mounted on the bonding pad on the catheter by a flip-chip bonding process. Bonding performance was evaluated by measurement of bond resistance between pads on the IC and catheter. This study demonstrates that the LTCC and LTCC side vias scheme can be a potential approach for high density CMUT array fabrication and indirect integration of CMUT-IC for miniature size packaging, which eliminates problems related with direct integration.

Fleshy fruits are an essential part of the human diet providing vital vitamins, minerals and other health-promoting compounds. The quality of ripe fruit (such as texture, color, shelf life, sugar content) has significant effect on influences consumer acceptance, resistance against pathogens and transportability to long distances. Tomato is one of most largely grown agricultural products in the world, therefore, it is essential to deliver the fruit in high quality manner. There is a need of determining the quality attributes of this fruit (non-destructively) by fast and cost-effective techniques without damage due to the increasing demand of the in agro- industrially controlled areas. Most of the commonly employed techniques are time consuming and involve a considerable degree of manual work. Sample collection, cutting, grading and laboratory tests are among the limitations. Visual appearance is the main source of information about quality. This work aims to estimate volume of tomato, variety grown in Turkey, by image processing techniques. Five different images of a tomato are captured using high resolution digital cameras. Volume of the fruit is computed by estimating horizontal and vertical distance of captured images. The results are validated with experimental results. The main purpose of this study is to make fast and cheap determination of the fruit quality evaluation process without damaging the fruit and making it ready for packaging.

Laser-induced thermotherapy (LITT) has been widely studied since it is a minimally invasive technique for focal destruction of liver tumors without side effects. However, there are still some concerns about the treatment and monitoring thermal effects during operation. Although real-time imaging modalities are available, like magnetic resonance imaging, they are not cost-effective and not applicable to all conditions. This paper presents artificial neural network (ANN) modeling of laser-induced thermal damages on ex vivo liver tissue. In this work three laser sources, i.e. a diode pumped laser with a wavelength of 980 nm, a 1070 nm yttrium lithium fluoride fiber laser, and a 1940 nm thulium fiber laser, were used in order to thermally damage tissues by applying the laser until coagulation observed. The diameter and depth of coagulation were empirically measured and used to train the ANN model by finding the correlation between laser parameters (application time, power, penetration depth, wavelength, and spot size) and thermal damages. Thermal damage can be determined by observing coagulation diameter and coagulation depth. The prediction ability and accuracy of the trained ANN model were tested by comparing the actual and simulated results. Our result showed that the ANN successfully predicts LITT damage in terms of coagulation diameter and coagulation depth, with a very high accuracy. The trained ANN model was compared with two mathematical models. In terms of performance, the ANN is a very useful and practical tool for determining LITT damage.

Quality evaluation of agricultural products is most commonly conducted using destructive methods. Ripeness and maturity of fruits are determined by measuring internal and external characteristic of fruits. Destructive method enables to measure texture, color, sugar content etc. Destructive methods increase success rate of quality determination of fruits, however, it practically has many concerns about effectiveness, reliability and cost. Therefore, it is necessary to develop fast, portable and cost-effective techniques without harming fruits to meet demand of consumer for fresh and healthy fruits. Visual appearance is an important method to obtain external characteristic (size, color) of fruits for grading or sorting. This work aims to develop custom design non-destructive quality evaluation system to reduce conventional destructive quality evaluations processes of fruits. The developed system in this study for fruit quality determination consists of two parts: (a) volume estimation by automatic machine vision and (b) ultrasonic testing. Volume estimation part was finished by one of our previous study and in this study, we mostly focused on developing ultrasonic part of the system. The ultrasonic part consisted of a programmable bipolar remote pulser unit (Ultrasonar, US 100) with a frequency range between 1 Hz to 10 MHz, two of 55 kHz piezoelectric probes for ultrasonic signal transmission and reception, an oscilloscope, and a PC. Ultrasonic signal generated by US 100 was applied to fruits (tomato, apple, peach) by transmiter probe and sound waves that passthrough fruit was collected back by receiver probe. Correlation between ultrasonic parameters (velocity and attenuation) and fruits characteristic is evaluated for such fruits. However, our results showed that quality evaluation of fruits with ultrasonic testing is not expected as in literature.