scholarly journals Quantifying Variation in Soybean Due to Flood Using a Low-Cost 3D Imaging System

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2682 ◽  
Author(s):  
Wenyi Cao ◽  
Jing Zhou ◽  
Yanping Yuan ◽  
Heng Ye ◽  
Henry T. Nguyen ◽  
...  
Keyword(s):  
Plant Height ◽  
3D Imaging ◽  
Plant Architecture ◽  
Imaging System ◽  
Low Cost ◽  
Plant Phenotyping ◽  
Soybean Plant ◽  
Plant Canopy ◽  
Petiole Length ◽  
Dry Biomass

Flood has an important effect on plant growth by affecting their physiologic and biochemical properties. Soybean is one of the main cultivated crops in the world and the United States is one of the largest soybean producers. However, soybean plant is sensitive to flood stress that may cause slow growth, low yield, small crop production and result in significant economic loss. Therefore, it is critical to develop soybean cultivars that are tolerant to flood. One of the current bottlenecks in developing new crop cultivars is slow and inaccurate plant phenotyping that limits the genetic gain. This study aimed to develop a low-cost 3D imaging system to quantify the variation in the growth and biomass of soybean due to flood at its early growth stages. Two cultivars of soybeans, i.e. flood tolerant and flood sensitive, were planted in plant pots in a controlled greenhouse. A low-cost 3D imaging system was developed to take measurements of plant architecture including plant height, plant canopy width, petiole length, and petiole angle. It was found that the measurement error of the 3D imaging system was 5.8% in length and 5.0% in angle, which was sufficiently accurate and useful in plant phenotyping. Collected data were used to monitor the development of soybean after flood treatment. Dry biomass of soybean plant was measured at the end of the vegetative stage (two months after emergence). Results show that four groups had a significant difference in plant height, plant canopy width, petiole length, and petiole angle. Flood stress at early stages of soybean accelerated the growth of the flood-resistant plants in height and the petiole angle, however, restrained the development in plant canopy width and the petiole length of flood-sensitive plants. The dry biomass of flood-sensitive plants was near two to three times lower than that of resistant plants at the end of the vegetative stage. The results indicate that the developed low-cost 3D imaging system has the potential for accurate measurements in plant architecture and dry biomass that may be used to improve the accuracy of plant phenotyping.

scholarly journals Rapid‐accurate anthropometric body shape assessment with low‐cost novel 3D imaging system (391.2)

2014 ◽  
Vol 28 (S1) ◽  
Author(s):  
Kang Zhang ◽  
Jolene Zheng ◽  
Chenfei Gao ◽  
Diana Thomas ◽  
Xin Li ◽  
...  
Keyword(s):  
3D Imaging ◽  
Body Shape ◽  
Imaging System ◽  
Low Cost

Stereo Vision Embedded System Proposal for Plant Phenotyping

2017 ◽  
Vol 11 (03) ◽  
pp. 293-309
Author(s):  
Nícolas dos Santos Rosa ◽  
Paulo E. Cruvinel ◽  
João de Mendonça Naime
Keyword(s):  
Embedded System ◽  
Stereo Vision ◽  
Plant Architecture ◽  
Vision System ◽  
Low Cost ◽  
Plant Phenotyping ◽  
Decision Making Processes ◽  
Preliminary Study ◽  
High Chance

This paper presents the design process of an embedded stereo vision system, which investigates the most relevant criteria for developing the hardware and software architectures for plant phenotyping. In other words, this paper is the result of a preliminary study in which the main motivation was the evaluation of the viability of a low-cost visual system for such field of knowledge. In addition, the implications of the adversities in an actual agricultural scenario under the system design are presented, since the system should not only meet the portability requirements but also the quality and precision for the measurements carried out by cameras. After the use of such method, the systems obtained may present a high chance of satisfying a set of constraints, and meeting their possibility to be used for machine vision applied in agricultural decision-making processes related to plant architecture and in situ recognition.

scholarly journals A Nondestructive Method to Estimate Plant Height, Stem Diameter and Biomass of Rice under Field Conditions Using Digital Image Analysis

2017 ◽  
Vol 10 (1) ◽  
pp. 1-7 ◽  
Author(s):  
M Mano ◽  
M Igawa
Keyword(s):  
Plant Height ◽  
Plant Traits ◽  
Agricultural Research ◽  
Low Cost ◽  
Ground Surface ◽  
Time Lapse ◽  
Nondestructive Method ◽  
Stem Diameter ◽  
Plant Phenotyping ◽  
Continuous Data

Plant phenotyping intends measuring complex plant traits, and is important in agricultural research for enhancing yield improvement. Manual plant phenotyping is laborious and destructive, and hence a less-laborious and non-destructive method is required. Here, we proposed a nondestructive method to estimate continuous data of plant traits such as height, stem diameter and biomass using a low cost time-lapse camera. The camera was installed at a rice field in Japan, and captured images for four target plants every three hour. The plant height and stem diameter were determined from the images by referencing scale bars that were placed next to the target plants and above the ground surface. Both the height and the diameter were compared to directly measured ones, and the relationships between those were in good agreement. Plant volumes were estimated from the height and stem diameter assuming a shape of rice plant is cylindrical. Above ground biomass without panicles was determined by rice plants sampled from the field. The determined biomass increased in proportion to the plant volume, and its relationship used to produce continuous data of the rice biomass. The results suggest that the proposed method can be considered as a useful tool of the plant phenotyping.J. Environ. Sci. & Natural Resources, 10(1): 1-7 2017

scholarly journals Affordable Imaging Lab for Noninvasive Analysis of Biomass and Early Vigour in Cereal Crops

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Rita Armoniené ◽  
Firuz Odilbekov ◽  
Vivekanand Vivekanand ◽  
Aakash Chawade
Keyword(s):  
Imaging System ◽  
Low Cost ◽  
Dry Weight ◽  
Automated Analysis ◽  
Coefficient Of Determination ◽  
Plant Phenotyping ◽  
Cereal Crops ◽  
Small Scale ◽  
Noninvasive Analysis ◽  
Early Vigour

Plant phenotyping by imaging allows automated analysis of plants for various morphological and physiological traits. In this work, we developed a low-cost RGB imaging phenotyping lab (LCP lab) for low-throughput imaging and analysis using affordable imaging equipment and freely available software. LCP lab comprising RGB imaging and analysis pipeline is set up and demonstrated with early vigour analysis in wheat. Using this lab, a few hundred pots can be photographed in a day and the pots are tracked with QR codes. The software pipeline for both imaging and analysis is built from freely available software. The LCP lab was evaluated for early vigour analysis of five wheat cultivars. A high coefficient of determination (R2 0.94) was obtained between the dry weight and the projected leaf area of 20-day-old wheat plants and R2 of 0.9 for the relative growth rate between 10 and 20 days of plant growth. Detailed description for setting up such a lab is provided together with custom scripts built for imaging and analysis. The LCP lab is an affordable alternative for analysis of cereal crops when access to a high-throughput phenotyping facility is unavailable or when the experiments require growing plants in highly controlled climate chambers. The protocols described in this work are useful for building affordable imaging system for small-scale research projects and for education.

scholarly journals Accuracy and reliability of a low-cost, handheld 3D imaging system for child anthropometry

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0205320 ◽  
Author(s):  
Joel Conkle ◽  
Parminder S. Suchdev ◽  
Eugene Alexander ◽  
Rafael Flores-Ayala ◽  
Usha Ramakrishnan ◽  
...  
Keyword(s):  
3D Imaging ◽  
Imaging System ◽  
Low Cost

scholarly journals Three-Dimensional Reconstruction of Soybean Canopies Using Multisource Imaging for Phenotyping Analysis

2018 ◽  
Vol 10 (8) ◽  
pp. 1206 ◽  
Author(s):  
Haiou Guan ◽  
Meng Liu ◽  
Xiaodan Ma ◽  
Song Yu
Keyword(s):  
3D Reconstruction ◽  
Laser Scanning ◽  
Imaging System ◽  
Three Dimensional ◽  
Plant Phenotyping ◽  
Phenotypic Traits ◽  
Soybean Plant ◽  
Imaging Device ◽  
Soybean Canopy ◽  
Greenness Index

Geometric three-dimensional (3D) reconstruction has emerged as a powerful tool for plant phenotyping and plant breeding. Although laser scanning is one of the most intensely used sensing techniques for 3D reconstruction projects, it still has many limitations, such as the high investment cost. To overcome such limitations, in the present study, a low-cost, novel, and efficient imaging system consisting of a red-green-blue (RGB) camera and a photonic mixer detector (PMD) was developed, and its usability for plant phenotyping was demonstrated via a 3D reconstruction of a soybean plant that contains color information. To reconstruct soybean canopies, a density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to extract canopy information from the raw 3D point cloud. Principal component analysis (PCA) and iterative closest point (ICP) algorithms were then used to register the multisource images for the 3D reconstruction of a soybean plant from both the side and top views. We then assessed phenotypic traits such as plant height and the greenness index based on the deviations of test samples. The results showed that compared with manual measurements, the side view-based assessments yielded a determination coefficient (R2) of 0.9890 for the estimation of soybean height and a R2 of 0.6059 for the estimation of soybean canopy greenness index; the top view-based assessment yielded a R2 of 0.9936 for the estimation of soybean height and a R2 of 0.8864 for the estimation of soybean canopy greenness. Together, the results indicated that an assembled 3D imaging device applying the algorithms developed in this study could be used as a reliable and robust platform for plant phenotyping, and potentially for automated and high-throughput applications under both natural light and indoor conditions.

scholarly journals A collaborative, mixed‐methods evaluation of a low‐cost, handheld 3D imaging system for child anthropometry

2018 ◽  
Vol 15 (2) ◽  
pp. e12686 ◽  
Author(s):  
Joel Conkle ◽  
Kate Keirsey ◽  
Ashton Hughes ◽  
Jennifer Breiman ◽  
Usha Ramakrishnan ◽  
...  
Keyword(s):  
Mixed Methods ◽  
3D Imaging ◽  
Imaging System ◽  
Low Cost ◽  
Mixed Methods Evaluation

Low-cost high-performance CMOS terahertz imaging system

2015 ◽  
Author(s):  
Chung Hsing Li ◽  
Tzu-Chao Yan ◽  
Yuhsin Chang ◽  
Chyong Chen ◽  
Chien-Nan Kuo
Keyword(s):  
High Performance ◽  
Imaging System ◽  
Low Cost ◽  
Terahertz Imaging
Sign in / Sign up

Export Citation Format

Share Document