Projects

Infield High-Throughput Plant Phenotyping

by Yu Jiang, Rui Xu, and Shangpeng Sun

Breeding of crops has to be more efficient to fulfil the requirement of feeding over nine billion people in the world. In order to improve breeding efficiency, phenotypic traits of crops need to be quickly and accurately measured in the field, and thus requiring new technologies of infield high-throughput phenotyping of crops. … Read More

Cotton Foreign Matter Detection using Hyperspectral Transmittance Imaging

by Mengyun Zhang

Cotton plays an important role in the U.S. national economy. This commodity can be contaminated by various foreign matter (FM) during harvesting and processing, leading to potential damage to textile products. … Read More

Blueberry Bruise Detection by Pulse-Phase Thermography

by Jesse Kuzy

As part of an ongoing grant to analyze blueberry damage during harvesting and processing, new sensing technologies are being explored for detection of blueberry bruises. … Read More

Blueberry Bruise Characterization by Magnetic Resonance Imaging (MRI)

by Jesse Kuzy

Current blueberry bruise evaluation techniques rely on visual size estimation and firmness measurements. … Read More

Develop the Second Generation of Berry Impact Recording Device (BIRD)

by Rui Xu

This Project is to improve the BIRD sensor based on the first generation. The second generation will make it lighter and smaller. It records the acceleration of the sensor. It uses PIC18LF14K50 as the microcontroller, along with a 3 axis accelerometer, one memory chip and one rechargeable battery. The sensor can record the acceleration from -200g to 200g for each axis, which is enough for the sensor to record most of the impacts that occurred on machine harvesting and packaging process. Read More »

Cotton Trash Detection and Identification using Hyperspectral Imaging

by Yu Jiang

Cotton is an important natural fiber resource contributing to economies around the world, and its production is an important economic factor in the United States as the leading exporter, accounting for over one-third of global trade in raw cotton (USDA, 2013)… Read More »

Quantitative Determination of Onion Internal Quality Using Reflectance, Interactance, and Transmittance Modes of Hyperspectral Imaging

by Haihua Wang

This study demonstrated the feasibility of using a hyperspectral imaging system with three measurement modes to quantitatively estimate the internal quality of onions. This approach achieved respectable results in comparison to spectroscopy, which has been predominantly used for this purpose in the past… Read More »

Shortwave infrared hyperspectral imaging for detecting sour skin (Burkholderiacepacia)-infected onions

by Weilin Wang

This study presents an effort of using the SWIR hyperspectral imaging to detect sour skin, one of the most serious onion postharvest diseases. The spectral characteristics of the infected onions were distinct from those of the healthy onions… Read More »

Estimating the diameter and volume of Vidalia sweet onions using the consumer-grade RGB-depth camera

by Weilin Wang

Size is an essential metric for the postharvest grading of Vidalia sweet onions. Currently, the size of the Vidalia onion is mainly measured by machine vision systems using 2-D imaging or mechanical sizers. This work investigated the potential of using the RGB-depth sensor to improve the accuracy and efficiency of quantifying the size features of onions… Read More »

Measurement of optical properties of onion skin and flesh at 633 nm

by Weilin Wang

Evaluating onion quality using optical techniques is challenging because of the presence of dry outer skin and the layered structure of onion fleshy tissues. To better understand the light propagation in onions, the optical properties of dry skin and fleshy tissues from two cultivars were measured at 632.8 nm by using a single integrating sphere based system… Read More »

A multimodal quality inspection system based on 3D, hyperspectral, and X-ray imaging for onions

by Weilin Wang

In this study, a novel multimodal machine vision system utilizing color, 3-D depth, spectral, and X-ray imaging technologies was designed for quality inspection of onions. A LabVIEW program was also developed to control and synchronize hardware devices for data acquisition… Read More »

Fluorescence imaging to characterize cotton foreign matter

by Adnan Mustafic

A fluorescent imaging setup consisting of blue LED and the UV LED excitation sources with an SLR camera was constructed based on the excitation/emission analysis by fluorescence spectroscopy. Under the blue LED excitation light the following cotton trash types were imaged: bark, brown leaf, bract, green leaf, and hull… Read More »

UAV

by Rui Xu

The application of robots in agriculture has been studies for several decades. As an aerial platform, the Unmanned Aerial Vehicle (UAV) is widely used in precision agriculture to acquire aerial image to monitor the crop variability. However, to acquire aerial images, for example, hyperspectral image, needs satellite or large payload planes in order to carry the imaging equipment. Those large payload planes are expensive and unaffordable for small farms. Recently, the development of small UAVs provide an inexpensive solution for small farms. The small UAV can be used to acquire high resolution aerial image at a low flight height. Currently, our lab is developing an aerial imaging platform using small UAV to monitor the crop growth. This aerial imaging platform could be used to acquire color image, thermal image and multispectral image based on the specific application.

BIRD Sensor Android App

by Jagadish Kumar

The project aims to analyze the BIRD sensor data in real time in the work field. It involves interfacing the BIRD II sensor with the android phone using USB host protocol and analyzing the impact data collected by the sensor by plotting various graphs like acceleration vs time, raw X, Y and Z accelerations with time, etc. The project also aims at providing a user friendly GUI. View Images »

E-nose Upgrade

by Kaya Sumire Abe

The work was done based on the project “Detecting sour skin diceased onions using a customized gas sensor array” by Tharun Konduru, in 2013. The project consists of an array of chemical sensors interfaced by a microcontroller PIC18F4550 using PIC BASIC PRO programming language. The main tasks for this upgrade were replacing the serial communication to USB, the EEPROM to an SD card, and developing a printed circuit board design for the upgraded system.

E-nose Upgrade Continued

by Jesse Kuzy

Current objectives for the e-nose include finalization of the PCB, development of a new design for the sensor chamber, and transfer to a smaller housing. Long-term goals include total physical redesign, possible integration of features previously developed by Kaya Abe, and eventually, development of analytical models for collected data.