Yuzhen Lu

Yuzhen Lu
Mississippi State University | MSU · Department of Agricultural and Biological Engineering

PhD
I am now looking for a PhD/MS student in Summer/Fall 2022: https://www.yuzhenlu.com/media/MSU_GraduateAssistantship.pdf

About

61
Publications
32,793
Reads
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788
Citations
Introduction
I am currently offering a MS/PhD assistantship in sensing, machine learning and automation/robotics for foods and agriculture. If interested, see the position at https://www.yuzhenlu.com/media/MSU_GraduateAssistantship.pdf
Additional affiliations
November 2020 - present
Mississippi State University
Position
  • Professor (Assistant)
December 2019 - November 2020
North Carolina State University
Position
  • Researcher
April 2019 - December 2019
USDA/ARS
Position
  • Researcher
Education
September 2014 - July 2018
Michigan State University
Field of study
  • Biosystems Engineering

Publications

Publications (61)
Conference Paper
Full-text available
Weeds are among the major threats to cotton production. Overreliance on herbicides for weed control has accelerated the evolution of herbicide-resistance in weeds and brought increasing concerns about environments, food safety and human health. Machine vision systems for automated or robotic weeding have received significant interest in integrated,...
Article
Full-text available
In agricultural image analysis, optimal model performance is keenly pursued for better fulfilling visual recognition tasks (e.g., image classification, segmentation, object detection and localization), in the presence of challenges with biological variability and unstructured environments. Large-scale, balanced and ground-truthed image datasets are...
Article
Full-text available
Precision weed management offers a promising solution for sustainable cropping systems through the use of chemical-reduced/non-chemical robotic weeding techniques, which apply suitable control tactics to individual weeds or small clusters. Therefore, accurate identification of weed species plays a crucial role in such systems to enable precise, ind...
Preprint
Full-text available
In agricultural image analysis, optimal model performance is keenly pursued for better fulfilling visual recognition tasks (e.g., image classification, segmentation, object detection and localization), in the presence of challenges with biological variability and unstructured environments. Large-scale, balanced and ground-truthed image datasets, ho...
Article
Full-text available
Cotton, a major crop worldwide, is harvested in mechanized production systems once at the end of the growing season. To facilitate harvest and maximize fiber quality, the plants are typically defoliated when about 60% of the cotton bolls are open. Due to non-uniform maturation, the bolls that have opened early expose their fiber to weather until ha...
Article
Full-text available
As an emerging cash crop, industrial hemp (Cannabis sativa L.) grown for cannabidiol (CBD) has spurred a surge of interest in the United States. Cultivar selection and harvest timing are important to produce CBD hemp profitably and avoid economic loss resulting from the delta-9-tetrahydrocannabinol (THC) concentration in the crop exceeding regulato...
Article
Full-text available
Plant segmentation is a crucial task in computer vision applications for identification/classification and quantification of plant phenotypic features. Robust segmentation of plants is challenged by a variety of factors such as unstructured background, variable illumination, biological variations, and weak plant-background contrast. Existing color...
Chapter
Infield grading and sorting could help apple growers achieve cost savings in postharvest handling by removing inferior fruit that are not suitable for fresh market consumption. An apple infield grading and sorting system, including sub-systems of singulation and rotation, grading, and sorting, was developed. The grading system’s repeatability coeff...
Article
Full-text available
Highlights A new, improved apple harvest assist and in-field sorting (HAIS) machine was developed. The HAIS machine has several major innovations for enhanced harvesting and infield sorting efficiencies. Laboratory tests showed superior performance in fruit grading and sorting and bin filling and handling. Field tests showed only 0.4% of harvested...
Preprint
Full-text available
Precision weed management offers a promising solution for sustainable cropping systems through the use of chemical-reduced/non-chemical robotic weeding techniques, which apply suitable control tactics to individual weeds. Therefore , accurate identification of weed species plays a crucial role in such systems to enable precise, individualized weed...
Article
Full-text available
Loblolly pine (Pinus taeda L.) is a commercially important timber species planted across a wide temperature gradient in the southeastern U.S. It is critical to ensure that the planting stock is suitably adapted to the growing environment to achieve high productivity and survival. Long-term field studies, although considered the most reliable method...
Article
Full-text available
Loblolly pine is an economically important timber species in the United States, with almost 1 billion seedlings produced annually. The most significant disease affecting this species is fusiform rust, caused by Cronartium quercuum f. sp. fusiforme. Testing for disease resistance in the greenhouse involves artificial inoculation of seedlings followe...
Article
Full-text available
Pickling cucumbers are susceptible to bruising during harvest and postharvest handling. It is thus desirable to segregate bruised fruit before they are marketed as fresh products or processed as pickles. Structured-illumination reflectance imaging (SIRI) is an emerging optical imaging modality for food quality and safety inspection. This study repo...
Article
Full-text available
Automation continues to play a greater role in agricultural production with commercial systems now available for machine vision identification of weeds and other pests, autonomous weed control, and robotic harvesters for fruits and vegetables. The growing availability of autonomous machines in agriculture indicates that there are opportunities to i...
Article
Full-text available
Pickling cucumbers are susceptible to chilling injury (CI) during postharvest refrigerated storage, which would result in quality degradation and economic loss. It is thus desirable to remove the defective fruit before they are marketed as fresh products or processed into pickled products. Chlorophyll fluorescence is sensitive to CI in green fruits...
Article
Infield pre-sorting is intended to remove processing-grade (inferior) fruit that are not suitable for the fresh market, so that growers can handle sorted apples differentially in postharvest storage and packing to achieve cost savings. To achieve this goal, we developed an apple infield grading and sorting system, in which fruit singulation, rotati...
Article
Full-text available
The most important climatic variable influencing growth and survival of loblolly pine is the yearly average minimum winter temperature (MWT) at the seed source origin, and it is used to guide the transfer of improved seed lots throughout the species’ distribution. This study presents a novel approach for the assessment of freeze-induced damage and...
Article
Full-text available
Computer vision technologies have attracted significant interest in precision agriculture in recent years. At the core of robotics and artificial intelligence, computer vision enables various tasks from planting to harvesting in the crop production cycle to be performed automatically and efficiently. However, the scarcity of public image datasets r...
Article
Full-text available
In the past 20 years, hyperspectral imaging has been widely investigated as an emerging, promising technology for evaluating quality and safety of horticultural products. This technology has originated from remote sensing and joins the domains of machine vision and point spectroscopy to provide superior image segmentation for the detection of defec...
Article
Full-text available
This article reviews the research and development progress of mechanical harvest technologies for fresh market apples over the past decades with a focus on the predominant technologies of shake-and-catch, robots, and harvest-assist platform methods. In addition, based on the review it points out the bottlenecks and future trends of these three tech...
Conference Paper
Loblolly pine (Pinus taeda L.) is a commercially important timber species that is planted across a wide temperature gradient in the southeastern United States. Ensuring the planting stock is suitably adapted to the growing environment is critical to achieve high productivity and survival. Mean winter minimum temperature (MMT) is an important climat...
Article
HIGHLIGHTS A Matlab GUI, siriTool, was developed for structured-illumination reflectance imaging. siriTool enables image preprocessing, feature extraction, and classification. siriTool was demonstrated for detection of spot defects on pickling cucumbers. Abstract . Structured-illumination reflectance imaging (SIRI) is an emerging imaging modality...
Article
Chlorophyll fluorescence imaging (CFI) is useful for detecting physiological disorders or defects for green-skinned horticultural products, because defective and normal plant tissues would have different responses to ultraviolet (UV) or short-wavelength visible excitation. This study was intended to evaluate the effectiveness of a new CFI approach...
Conference Paper
Full-text available
Structured-illumination reflectance imaging (SIRI) is an emerging imaging modality that provides more useful discriminative features for enhancing detection of defects in fruit and other horticultural and food products. In this study, we developed a Matlab graphical user interface (GUI), i.e., siriTool, developed to facilitate image analysis in SIR...
Article
Full-text available
Peaches are susceptible to fungal infection after harvest, and detection of the symptom at early stage is critical to reducing economic loss for the industry, but is challenging because the symptom is not visible at the surface of infected fruit. This research was therefore aimed to develop a non-destructive and accurate method, based on structured...
Article
Full-text available
Structured-illumination reflectance imaging (SIRI), compared to conventional uniform illumination based modalities, provides a new means for defect detection of fruit. The capability of SIRI for defect detection, however, mainly depends on its image resolution and contrast and depth-resolving features. This study was therefore aimed at providing th...
Conference Paper
Pickling cucumbers are susceptible to mechanical and chilling injuries during harvest and postharvest refrigerated storage. It is thus desirable to sort out the injured fruit before they are marketed as fresh products or processed as pickles at the processing plant. Structured-illumination reflectance imaging (SIRI) and chlorophyll fluorescence ima...
Article
Full-text available
Machine vision technology coupled with uniform illumination is now widely used for automatic sorting and grading of apples and other fruits, but it still does not have satisfactory performance for defect detection because there are a large variety of defects, some of which are difficult to detect under uniform illumination. Structured-illumination...
Conference Paper
Full-text available
Machine vision technology coupled with uniform illumination is now widely used for automatic sorting and grading of apples and other fruits, but it still does not have satisfactory performance for defect detection because there are a large variety of defects, some of which are difficult to detect under uniform illumination. Structured-illumination...
Article
Image enhancement is critical to detection of fruit defects by imaging techniques. Vignetting and noise are major image artifacts, which can seriously affect image segmentation results, especially in inspecting the curved-surface objects like fruit. It is common to use a calibration object or a mathematic model to reduce the vignetting effect in de...
Poster
Full-text available
Machine vision technology coupled with uniform illumination is now widely used for automatic sorting and grading of apples and other fruits, but it still does not have satisfactory performance for defect detection because there are a large variety of defects, some of which are difficult to detect under uniform illumination. Structured-illumination...
Article
Three-dimensional (3-D) geometry information is valuable for fruit quality evaluation. This study was aimed at exploring an emerging structured-illumination reflectance imaging (SIRI) system, coupled with phase analysis, for reconstructing surface profiles of fruit. Phase-shifted sinusoidal patterns, distorted by the fruit geometry, were acquired a...
Article
Full-text available
In this research, a structured illumination reflectance imaging (SIRI) system was used as a novel method for fresh bruise detection of apples. The SIRI system projects sinusoidal patterns of illumination onto samples, and image demodulation is then used to recover depth-specific information through varying the spatial frequency of the illumination...
Article
Full-text available
Apples are susceptible to a wide range of defects that can occur in the orchard and during the post-harvest period. Detection of these defects by non-destructive sensing techniques is of great importance for the apple industry and has been an intensive research topic over the past two decades. This review presents an overview of common defects in a...
Article
Full-text available
Thresholding is an important step in the segmentation of image features, and the existing methods are not all effective when the image histogram exhibits a unimodal pattern, which is common in defect detection of fruit. This study was aimed at developing a general automatic thresholding methodology for fast and effective segmentation of bruises fro...
Conference Paper
Full-text available
Three-dimensional (3-D) shape information is valuable for fruit quality evaluation. This study was aimed at developing phase analysis techniques for reconstruction of the 3-D surface of fruit from the pattern images acquired by a structured-illumination reflectance imaging (SIRI) system. Phase-shifted sinusoidal patterns, distorted by the fruit geo...
Article
Full-text available
SIRI is a new, promising imaging modality for enhancing quality detection of food. A liquid-crystal tunable filter (LCTF)-based multispectral SIRI system was developed and used for selecting optimal wavebands to detect bruising in apples. Immediately after impact bruising, apples of ‘Delicious’, ‘Royal Gala’, ‘Granny Smith’ and ‘Golden Delicious’ w...
Article
Full-text available
New, non-destructive sensing techniques for fast and more effective quality assessment of fruits and vegetables are needed to meet the ever-increasing consumer demand for better, more consistent and safer food products. Over the past 15 years, hyperspectral imaging has emerged as a new generation of sensing technology for non-destructive food quali...
Article
Full-text available
The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) parameters. In this work, we present empirical comparison between the standard LSTM recurrent neural network architecture and three new parameter-reduced variants obtained by el...
Article
Structured-illumination reflectance imaging (SIRI) provides a new means for enhanced detection of defects in horticultural products. Implementing the technique relies on retrieving amplitude images by illuminating the object with sinusoidal patterns of single spatial frequencies, which, however, are limited in interrogating the tissues at different...
Technical Report
Full-text available
Food image recognition is one of the promising applications of visual object recognition in computer vision. In this study, a small-scale dataset consisting of 5822 images of ten categories and a five-layer CNN was constructed to recognize these images. The bag-of-features (BoF) model coupled with support vector machine was first tested as comparis...
Article
Full-text available
Structured illumination using sinusoidal patterns has been utilized for optical imaging of biological tissues in biomedical research and, of horticultural products. Implementation of structured-illumination imaging relies on retrieval of amplitude images, which is conventionally achieved by a phase-shifting technique that requires collecting a mini...
Conference Paper
Full-text available
This study presented a first exploration of using composite sinusoidal patterns that integrated two and three spatial frequencies of interest, in structured-illumination reflectance imaging (SIRI) for enhanced detection of defects in food (e.g., bruises in apples). Three methods based on Fourier transform were proposed to retrieve amplitude images...
Article
Full-text available
A structured-illumination reflectance imaging (SIRI) system was recently developed in our laboratory for enhanced quality evaluation of horticultural products. It was implemented using a digital camera to acquire reflectance images from food products subjected to sinusoidal patterns of illumination, instead of conventional diffuse or uniform illumi...
Conference Paper
Full-text available
Uniform or diffuse illumination is the standard in implementing different imaging modalities. This form of illumination, however, has some major limitations in acquisition of useful information from food products because reflectance from the food products is nonuniform due to irregular, curved product surfaces. Moreover, diffuse illumination is not...
Conference Paper
Full-text available
Detection of fresh bruises in apples remains a challenging task due to the absence of visual symptoms and significant chemical alterations of fruit tissues during the initial stage after the fruit have been bruised. This paper reports on a new structured-illumination reflectance imaging (SIRI) technique for enhanced detection of fresh bruises in ap...
Chapter
The apple is one of the most consumed fruits in the world, and there is a critical need for enhanced computer vision technology for the quality assessment of apples. This chapter gives a review on recent advances in various computer vision techniques for detecting surface and internal defects and assessing texture and flavor in apples. While color...
Technical Report
Full-text available
Image de-blurring is important in many cases of imaging a real scene or object by a camera. This project focuses on de-blurring an image distorted by an out-of-focus blur through a simulation study. A pseudo-inverse filter is first explored but it fails because of severe noise amplification. Then Tikhonov regularization methods are employed, which...
Article
Full-text available
A structured-illumination reflectance imaging (SIRI) system was developed for the detection of fresh bruises in apples. The system consisted of a high-performance digital camera, a broadband DC-regulated light source, and a digital light engine for generating specific patterns of illumination. Sinusoidal patterns of illumination at a series of spat...
Article
Full-text available
This article presents the application of Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) coupled with chemometric techniques for rapid and non-destructive determination of oil content in rapeseed. The oil content of 150 rapeseed samples, as measured by Soxhlet extraction, were used as reference values for model calibration by p...
Article
Full-text available
Fourier-transform mid-infrared photoacoustic spectroscopy was utilized for rapid and nondestructive determination of nitrogen in rapeseeds. Rapeseed spectra were characterized by independent component analysis for quantitative calibration. A calibration model was built by using independent components as the input for partial least squares. Compared...
Article
Full-text available
Fast acquisition of nutritional information of rapeseeds is important for rapeseed breeding programs, evaluation of soil nutrient conditions and even fertilization recommendations. Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) was employed to determine nitrogen, phosphorus and potassium content in rapeseeds. Calibration model...
Article
Full-text available
Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) was employed to determine the contents of magnesium and potassium in rapeseeds. A total of 180 samples were collected for this purpose. A Savitzky–Golay filter was used for the spectral pretreatment. The whole sample set was divided into calibration and prediction sets composed of...
Article
Full-text available
Fourier transform infrared attenuated total reflectance (FTIR-ATR) spectroscopy was employed to characterize rapeseed oils. The spectral features of rapeseed oils were first investigated. Spectral data was processed using principal component analysis (PCA) and linear discriminant analysis (LDA) to discriminate the oils from three cultivars of rapes...
Article
Full-text available
Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) combined with multivariate discriminant analysis was employed to classify colors of rapeseeds. A total of 129 rapeseed varieties representing three colors (black, reddish and mottled-yellow) were scanned in the range of 500– 4000 cm À1. A Savitzky–Golay algorithm was used for the...
Article
Full-text available
Fast and nondestructive determination of rapeseed protein content carries significant implications in rapeseed production. This study presented the first attempt of using Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS) to quantify protein content of rapeseeds. The full-spectrum model was first built using Partial least squares...

Questions

Question (1)
Question
In constructing analytical signals, Hilbert transform based on FFT or FIR hilbert filter both suffer from Gibbs Oscillations at the ends of signals. Can Hilbert-Huang transform be used to address or mitigate the issue in image processing?

Projects

Projects (3)
Project
Robotic platform development for in-field sensor data acquisition; Algorithm development for phenotyping and characterization of plant growth and health; Data-driven decision making for precision horticulture management.
Archived project
Hardware and software improvements for high-performance fruit sorting and grading, and automatic bin handling and filling; Development of new adjustable picking platforms for improved ergonomics; Development of a new paddle based sorting system for two-class fruit sorting