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Analyzing Nitrogen Effects on Rice Panicle Development by Panicle Detection and Time-Series Tracking

Plant Phenomics 2023年第2期5卷 253-267页

作者： Qinyang Zhou Wei Guo Na Chen Ze Wang Ganghua Li Yanfeng Ding seishi ninomiya Yue Mu College of Agriculture Academy for Advanced Interdisciplinary StudiesCollaborative Innovation Center for Modern Crop Production co-sponsored by Province and MinistryNanjing Agricultural UniversityNanjing 210095China Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishi-TokyoTokyo 188-0002Japan

Detailed observation of the phenotypic changes in rice panicle substantially helps us to understand the yield *** recent studies,phenotyping of rice panicles during the heading–flowering stage still lacks comprehensive analysis,especially of panicle development under different nitrogen *** this work,we proposed a pipeline to automatically acquire the detailed panicle traits based on time-series images by using the YOLO v5,ResNet50,and DeepSORT *** with field observation data,the proposed method was used to test whether it has an ability to identify subtle differences in panicle developments under different nitrogen *** result shows that panicle counting throughout the heading–flowering stage achieved high accuracy(R^(2)=0.96 and RMSE=1.73),and heading date was estimated with an absolute error of 0.25 *** addition,by identical panicle tracking based on the time-series images,we analyzed detailed flowering phenotypic changes of a single panicle,such as flowering duration and individual panicle flowering *** rice population,with an increase in the nitrogen application:panicle number increased,heading date changed little,but the duration was slightly extended;cumulative flowering panicle number increased,rice flowering initiation date arrived earlier while the ending date was later;thus,the flowering duration became *** a single panicle,identical panicle tracking revealed that higher nitrogen application led to earlier flowering initiation date,significantly longer flowering days,and significantly longer total duration from vigorous flowering beginning to the end(total DBE).However,the vigorous flowering beginning time showed no significant differences and there was a slight decrease in daily DBE.

关键词： heading identical flowering

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Plant Phenomics:Emerging Transdisciplinary Science

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Plant Phenomics 2019年第1期1卷 39-41页

作者： seishi ninomiya Frédéric Baret Zong-Ming(Max)Cheng University of Tokyo TokyoJapan French National Institute of Agricultural Research ParisFrance Nanjing Agricultural University NanjingChina University of Tennessee TNUSA

Humankind is facing an unprecedented challenge to produce enough food for the coming decades because of population growth and increase in the average demand per capita,changes in climate conditions,and limitations in arable land area,as well as pressure on the water and *** main avenues should be concurrently taken to increase crop productivity:improving genetics to get more efficient and resilient crops and developing optimal crop management *** description and understanding of crop functioning will therefore be instrumental both for genetic improvement and crop *** will help to associate functional traits with the genome which will accelerate genetic progress by having more efficient techniques to design ideotypes adapted to particular pedoclimatic and crop management conditions and create them from the available genetic diversity.

关键词： crops Plant adapted

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The Japanese agricultural case-base InformationRetrieval System using Semi-Discrete MatrixDecomposition

The Japanese agricultural case-base InformationRetrieval Sys...

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国际农业工程大会

作者： seishi ninomiya HeadNetwork Computing Lab. Dept. Information Science ＆ Technology National Agriculture Research Center 3-1-1 Kannondai Tsukuba City Ibaraki 305-8666 Japan

＜正＞ In this paper, we present a Japanese document retrieval system that uses a new method of matrix *** order to improve the precision and recall ratio in the document retrieval system, a mathematical method called...

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A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting

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Plant Phenomics 2019年第1期1卷 1-14页

作者： Sambuddha Ghosa Bangyou Zheng Scott Chapman Andries B.Potgieter David R.Jordan Xuemin Wang Asheesh K.Singh Arti Singh Masayuki Hirafuji seishi ninomiya Baskar Ganapathysubramanian Soumik Sarkar Wei Guo Department of Mechanical Engineering Iowa State UniversityAmesIAUSA Department of Computer Science Iowa State UniversityAmesIAUSA CSIRO Agriculture and Food St.LuciaQLDAustralia School of Agriculture and Food Sciences The University of QueenslandGattonQLD 4343Australia Queensland Alliance for Agriculture and Food Innovation(QAAFI) The University of QueenslandGattonQLDAustralia Queensland Alliance for Agriculture and Food Innovation(QAAFI) The University of QueenslandWarwickQLDAustralia Department of Agronomy Iowa State UniversityAmesIAUSA International Field Phenomics Research Laboratory Institute for Sustainable Agro-Ecosystem Services

The yield of cereal crops such as sorghum(Sorghum bicolor ***)depends on the distribution of crop-heads in varying branching ***,counting the head number per unit area is critical for plant breeders to correlate with the genotypic variation in a specific breeding ***,measuring such phenotypic traitsmanually is an extremely labor-intensive process and suffers from low efficiency and human ***,the process is almost infeasible for large-scale breeding plantations or *** learning-based approaches like deep convolutional neural network(CNN)based object detectors are promising tools for efficient object detection and ***,a significant limitation of such deep learningbased approaches is that they typically require a massive amount of hand-labeled images for training,which is still a tedious ***,we propose an active learning inspired weakly supervised deep learning framework for sorghum head detection and counting from UAV-based *** demonstrate that it is possible to significantly reduce human labeling effort without compromising final model performance(R^(2)between human count and machine count is 0.88)by using a semitrained CNN model(i.e.,trained with limited labeled data)to perform synthetic *** addition,we also visualize key features that the network *** improves trustworthiness by enabling users to better understand and trust the decisions that the trained deep learning model makes.

关键词： Unmanned aerial vehicles (UAV)

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Easy MPE:Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping

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Plant Phenomics 2019年第1期1卷 30-38页

作者： Léa Tresch Yue Mu Atsushi Itoh Akito Kaga Kazunori Taguchi Masayuki Hirafuji seishi ninomiya Wei Guo International Field Phenomics Research Laboratory Institute for Sustainable Agro-Ecosystem ServicesGraduate School of Agricultural and Life SciencesThe University of TokyoTokyoJapan 2Montpellier SupAgroMontpellierFrance 3Plant Phenomics Research CenterNanjing Agricultural UniversityNanjingChina 4Memuro Upland Farming Research StationHokkaido Agricultural Research CenterNational Agriculture and Food Research OrganizationHokkaidoJapan 5Institute of Crop ScienceNational Agriculture and Food Research OrganizationTsukuba CityIbarakiJapan

Microplot extraction(PE)is a necessary image processing step in unmanned aerial vehicle-(UAV-)based research on breeding *** present,it is manually using ArcGIS,QGIS,or other GIS-based software,but achieving the desired accuracy is *** therefore developed an intuitive,easy-to-use semiautomatic program for MPE called Easy MPE to enable researchers and others to access reliable plot data UAV images of whole fields under variable field *** program uses four major steps:(1)binary segmentation,(2)microplot extraction,(3)production of∗.shp files to enable further file manipulation,and(4)projection of individual microplots generated from the orthomosaic back onto the raw aerial UAV images to preserve the image *** rows were successfully identified in all trial *** performance of the proposed method was evaluated by calculating the intersection-over-union(IOU)ratio between microplots determined manually and by Easy MPE:the average IOU(±SD)of all trials was 91%(±3).

关键词： enable image union

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How Useful Is Image-Based Active Learning for Plant Organ Segmentation?

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Plant Phenomics 2022年第1期4卷 384-394页

作者： Shivangana Rawat Akshay L.Chandra Sai Vikas Desai Vineeth N.Balasubramanian seishi ninomiya Wei Guo Department of Computer Science and Engineering Indian Institute of TechnologyHyderabadIndia Department of Computer Science University of FreiburgGermany Graduate School of Agricultural and Life Sciences The University of TokyoJapan

Training deep learning models typically requires a huge amount of labeled data which is expensive to acquire,especially in dense prediction tasks such as semantic ***,plant phenotyping datasets pose additional challenges of heavy occlusion and varied lighting conditions which makes annotations more time-consuming to *** learning helps in reducing the annotation cost by selecting samples for labeling which are most informative to the model,thus improving model performance with fewer *** learning for semantic segmentation has been well studied on datasets such as PASCAL VOC and ***,its effectiveness on plant datasets has not received much *** bridge this gap,we empirically study and benchmark the effectiveness of four uncertainty-based active learning strategies on three natural plant organ segmentation *** also study their behaviour in response to variations in training configurations in terms of augmentations used,the scale of training images,active learning batch sizes,and train-validation set splits.

关键词： consuming lighting sizes

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Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle

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Horticulture Research 2018年第1期5卷 22-31页

作者： Yue Mu Yuichiro Fujii Daisuke Takata Bangyou Zheng Koji Noshita Kiyoshi Honda seishi ninomiya Wei Guo International Field Phenomics Research Laboratory Institute for Sustainable Agro-ecosystem ServicesThe University of Tokyo1-1-1 Midori-choNishi-TokyoTokyo188-0002Japan Research Institute for Agriculture Okayama Prefectural Technology Center for AgricultureForestry and Fisheries1174-1 KodaokiAkaiwaOkayama709-0801Japan Fukushima University 1 KanayagawaFukushimaFukushima960-1248Japan CSIRO Agriculture and Food Queensland Bioscience Precinct306 Carmody RoadSt.LuciaQLD4067Australia JST PRESTO Kawaguchi Center Building4-1-8 HonchoKawaguchiSaitama332-0012Japan Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 YayoiBunkyoTokyo113-8657Japan International Digital Earth Applied Science Research Center Chubu University1200 MatsumotochoKasugaiAichi-ken487-8501Japan

In orchards, measuring crown characteristics is essential for monitoring the dynamics of tree growth and optimizing farm management. However, it lacks a rapid and reliable method of extracting the features of trees with an irregular crown shape such as trained peach trees. Here, we propose an efficient method of segmenting the individual trees and measuring the crown width and crown projection area (CPA) of peach trees with time-series information, based on gathered images. The images of peach trees were collected by unmanned aerial vehicles in an orchard in Okayama, Japan, and then the digital surface model was generated by using a Structure from Motion (SfM) and Multi-View Stereo (MVS) based software. After individual trees were identified through the use of an adaptive threshold and marker-controlled watershed segmentation in the digital surface model, the crown widths and CPA were calculated, and the accuracy was evaluated against manual delineation and field measurement, respectively. Taking manual delineation of 12 trees as reference, the root-mean-square errors of the proposed method were 0.08 m (R^(2) = 0.99) and 0.15 m (R^(2) = 0.93) for the two orthogonal crown widths, and 3.87 m2 for CPA (R^(2) = 0.89), while those taking field measurement of 44 trees as reference were 0.47 m (R^(2) = 0.91), 0.51 m (R^(2) = 0.74), and 4.96 m2 (R^(2) = 0.88). The change of growth rate of CPA showed that the peach trees grew faster from May to July than from July to September, with a wide variation in relative growth rates among trees. Not only can this method save labour by replacing field measurement, but also it can allow farmers to monitor the growth of orchard trees dynamically.

关键词： crown tree watershed

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Next-generation regenerative therapy for ischemic stroke using peripheral blood mononuclear cells

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Neural Regeneration Research 2024年第11期19卷 2341-2342页

作者： Masato Kanazawa Itaru ninomiya Yutaka Otsu Masahiro Hatakeyama Department of Neurology Brain Research InstituteNiigata UniversityNiigataJapan

Stroke is the second leading cause of death and the third leading cause of disability worldwide after heart *** predict that stroke deaths and permanent disabilities will increase worldwide by the year ***-target therapies may be insufficient,because ischemic cerebral injury involves several ***-mediated therapies are ideal,because they target multiple cell types to enhance protection and recovery.

关键词： ischemic death cerebral

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Advanced Sensor-Network with Field Monitoring Servers and MetBroker

Advanced Sensor-Network with Field Monitoring Servers and Me...

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国际农业工程大会

作者： Masayuki Hirafuji Tokihiro Fukatsu Hu Haoming Takuji Kiura Matthew Laurenson Dongxian He Atsushi Yamakawa Akifumi Imada seishi ninomiya National Agricultural Research Center National Agricultural Research Center National Agricultural Research Center/JST National Agricultural Research Center Horticulture and Food Research Institute of New Zealand CAAS National Agricultural Research Center/JSPS fellow National Agricultural Research Center/JST Ibaraki University National Agricultural Research Center

＜正＞ Field Server is a Web server which can be installed in fields, and Field Monitoring Server （FMS） is a kind of Field Servers for monitoring. Sensors embedded in FMSs are air-temperature, humidity, intensity of solar radiation, leaf wetness, soil moisture, CO2 concentration, UV, IR, CCD/CMOS camera and so on. Field Servers are connected by Wi-Fi （Wireless-LAN） respectively as Ad-Hoc network, and simultaneously Field Servers provide

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External defects and severity level evaluation of potato using single and multispectral imaging in near infrared region Author links open overlay panel

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Information Processing in Agriculture 2024年第1期11卷 80-90页

作者： Dimas Firmanda Al Riza Slamet Widodo Kazuya Yamamoto Kazunori ninomiya Tetsuhito Suzuki Yuichi Ogawa Naoshi Kondo Laboratory of Biosensing Engineering Graduate School of AgricultureKyoto UniversityKitashirakawaKyoto 6068267Japan Department of Biosystems Engineering Faculty of Agricultural TechnologyUniversitas BrawijayaJl.VeteranMalang 65145Indonesia Department of Mechanical and Biosystem Engineering Bogor Agricultural UniversityJl.Raya Darmaga Kampus IPB DarmagaBogor 16680Indonesia Technology Development Department Shibuya Seiki Co.Ltd.66Takaoka-choMatsuyamaEhime 7918036Japan

Non-invasive potato defects detection has been demanded for sorting and grading *** on the classification of the defects has been available,however,investigation on the severity level calculation is *** the detection of the common scab,it has been found that imaging in the infrared region provide an interesting characteristic that could distinguish defected area to normal ***,investigations on this wavelength range is interesting to add more knowledge and for *** this research,the multispectral image has been obtained and investigated especially at three wavelengths(950,1150,1600 nm).Image pre-processing and pseudo-color conversion techniques were explored to enhance the contrast between defects,normal background skin area and soil *** show that external defects,such as common scab and some mechanical damage types,appear brighter in the near infrared region,especially at 1600 nm against the normal skin *** has been found that pseudo-color images conversion provides more information regarding type if surface characteristics compared to grayscale single *** segmentation using pseudo-color images after multiplication operation pre-processing could be used for common scab and mechanical damage detection excluding soil deposits with a Dice Sorensen coefficient of *** addition,image segmentation using single image at 1600 nm shown relatively better results with Dice Sorensen coefficient of 0.72 with note that thick soil deposits will also be *** severity level evaluation had an R2 correlation of 0.84 against standard measurements of severity.

关键词： Multispectral imaging Pseudo-color Common scab External defects Near infrared

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