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Bio-Master:Design and Validation of a High-Throughput Biochemical Profiling Platform for Crop Canopies

Plant Phenomics 2023年第4期5卷 864-875页

作者： Ruowen liu Pengyan Li Zejun Li Zhenghui liu Yanfeng Ding Wenjuan Li shouyang liu Engineering Research Center of Plant Phenotyping Ministry of EducationJiangsu Collaborative Innovation Center for Modern Crop ProductionAcademy for Advanced Interdisciplinary StudiesNanjing Agricultural UniversityNanjingChina College of Agriculture Nanjing Agricultural UniversityNanjingChina State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China the Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingChina

Accurate assessment of crop biochemical profiles plays a crucial role in diagnosing their physiological *** conventional destructive methods,although reliable,demand extensive laboratory work for measuring various *** the other hand,nondestructive techniques,while efficient and adaptable,often suffer from reduced precision due to the intricate interplay of the field environment and canopy *** a delicate balance between efficiency and accuracy,we have developed the Bio-Master phenotyping *** system is capable of simultaneously measuring four vital biochemical components of the canopy profile:dry matter,water,chlorophyll,and nitrogen ***-Master initiates the process by addressing structural influences,through segmenting the fresh plant and then further chopping the segment into uniform small ***,the system quantifies hyperspectral reflectance and fresh weight over the sample within a controlled dark chamber,utilizing an independent light *** final step involves employing an embedded estimation model to provide synchronous estimates for the four biochemical components of the measured *** this study,we established a comprehensive training dataset encompassing a wide range of rice varieties,nitrogen levels,and growth *** process regression model was used to estimate biochemical contents utilizing reflectance data obtained by ***-one-out validation revealed the model's capacity to accurately estimate these contents at both leaf and plant *** Bio-Master,measuring a single rice plant takes approximately only 5 min,yielding around 10 values for each of the four biochemical components across the vertical ***,the Bio-Master system allows for immediate measurements near the field,mitigating potential alterations in plant status during transportation and *** a result,our measurements are more likely to faithfully represent in situ *** summariz

关键词： Master utilizing reflectance

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A Novel Feature Selection Strategy Based on Salp Swarm Algorithm for Plant Disease Detection

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Plant Phenomics 2023年第2期5卷 209-225页

作者： Xiaojun Xie Fei Xia Yufeng Wu shouyang liu Ke Yan Huanliang Xu Zhiwei Ji College of Artificial Intelligence Nanjing Agricultural UniversityNanjingJiangsu 210095China Center for Data Science and Intelligent Computing Nanjing Agricultural UniversityNanjingJiangsu 210095China State Key Laboratory for Crop Genetics and Germplasm Enhancement Bioinformatics CenterAcademy for Advanced Interdisciplinary StudiesNanjing Agricultural UniversityNanjingJiangsu 210095China Academy for Advanced Interdisciplinary Studies Nanjing Agricultural UniversityNanjingJiangsu 210095China Department of the Built Environment College of Design and EngineeringNational University of Singapore4 Architecture DriveSingapore 117566Singapore

Deep learning has been widely used for plant disease recognition in smart agriculture and has proven to be a powerful tool for image classification and pattern ***,it has limited interpretability for deep *** the transfer of expert knowledge,handcrafted features provide a new way for personalized diagnosis of plant ***,irrelevant and redundant features lead to high *** this study,we proposed a swarm intelligence algorithm for feature selection[salp swarm algorithm for feature selection(SSAFS)]in image-based plant disease *** is employed to determine the ideal combination of handcrafted features to maximize classification success while minimizing the number of *** verify the effectiveness of the developed SSAFS algorithm,we conducted experimental studies using SSAFS and 5 metaheuristic *** evaluation metrics were used to evaluate and analyze the performance of these methods on 4 datasets from the UCI machine learning repository and 6 plant phenomics datasets from *** results and statistical analyses validated the outstanding performance of SSAFS compared to existing state-of-the-art algorithms,confirming the superiority of SSAFS in exploring the feature space and identifying the most valuable features for diseased plant image *** computational tool will allow us to explore an optimal combination of handcrafted features to improve plant disease recognition accuracy and processing time.

关键词： Plant image redundant

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Identification of sap flow driving factors of jujube plantation in semi-arid areas in Northwest China

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International Journal of Agricultural and Biological Engineering 2017年第2期10卷 172-183页

作者： Wei Xinguang Li Bo Guo Chengjiu Wang Youke He Jianqiang shouyang liu Wang Tieliang Yao Mingze College of Water Conservancy Shenyang Agricultural UniversityShenyang 110866China College of Water Resources and Architectural Engineering Northwest A&F UniversityYangling 712100China Unite of Modelling Agricultural and Hydrological Systems in the Mediterranean Environment French National Institute of Agronomic Research(INRA)Avignon 84914France

Jujube is widely cultivated in the semi-arid region of the Loess Plateau in Northwest China due to its high water deficit *** such an ecologically vulnerable area,it is critical to explore the water consumption processes of key tree species and their responses to driving *** flow data gathered during a two-year field study in a jujube plantation were analyzed as a surrogate for transpiration *** measured sap flows were related to changes in the soil water content,meteorological factors(the vapor pressure deficit and the level of photosynthetically active radiation),and plant physiological factors(the sap wood area,leaf area and leaf area index).The factors that govern sap flow were found to vary depending on the growing season,and on hourly and daily *** plants’drought tolerance could be predicted based on their peak sap flows and the variation in their sap flow rates at different soil water *** sap flow was most strongly affected by the water content of the topmost(0-20 cm)soil *** the studied meteorological factors,the photosynthetically active radiation had a greater effect on sap flow than the vapor pressure *** correlation we found could be applied to predict jujube tree water consumption and assist the design of irrigation scheme.

关键词： jujube sap flow soil water content photosynthetically active radiation the Loess Plateau

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Self-Supervised Plant Phenotyping by Combining Domain Adaptation with 3D Plant Model Simulations: Application to Wheat Leaf Counting at Seedling Stage

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Plant Phenomics 2023年第2期5卷 226-238页

作者： Yinglun Li Xiaohai Zhan shouyang liu Hao Lu Ruibo Jiang Wei Guo Scott Chapman Yufeng Ge Benoit de Solan Yanfeng Ding Frédéric Baret Plant Phenomics Research Centre Academy for Advanced Interdisciplinary StudiesJiangsu Collaborative Innovation Center for Modern Crop ProductionNanjing Agricultural UniversityNanjingChina Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan School of Agriculture and Food Sciences The University of QueenslandSt.LuciaQueensland 4072Australia Department of Biological Systems Engineering University of Nebraska-LincolnLincolnNebraska 68583United States INRAE Avignon UniversitéUMR EMMAHUMT CAPTE228route de l’aérodrome-CS 4050984914 Avignon Cedex 9France ARVALIS Institut du Végétal 3 Rue Joseph et Marie Hackin75116 ParisFrance

The number of leaves at a given time is important to characterize plant growth and *** this work,we developed a high-throughput method to count the number of leaves by detecting leaf tips in RGB *** digital plant phenotyping platform was used to simulate a large and diverse dataset of RGB images and corresponding leaf tip labels of wheat plants at seedling stages(150,000 images with over 2 million labels).The realism of the images was then improved using domain adaptation methods before training deep learning *** results demonstrate the efficiency of the proposed method evaluated on a diverse test dataset,collecting measurements from 5 countries obtained under different environments,growth stages,and lighting conditions with different cameras(450 images with over 2,162 labels).Among the 6 combinations of deep learning models and domain adaptation techniques,the Faster-RCNN model with cycle-consistent generative adversarial network adaptation technique provided the best performance(R^(2)=0.94,root mean square error=8.7).Complementary studies show that it is essential to simulate images with sufficient realism(background,leaf texture,and lighting conditions)before applying domain adaptation ***,the spatial resolution should be better than 0.6 mm per pixel to identify leaf *** method is claimed to be self-supervised since no manual labeling is required for model *** self-supervised phenotyping approach developed here offers great potential for addressing a wide range of plant phenotyping *** trained networks are available at https://***/YinglunLi/Wheat-leaf-tip-detection.

关键词： Wheat seedling Plant

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修剪对黄土丘陵区枣树蒸腾的调控作用

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农业机械学报 2014年第12期45卷 194-202,315页

作者：魏新光陈滇豫 liu shouyang 汪星高志永汪有科西北农林科技大学水利与建筑工程学院陕西杨凌712100 法国国家农业科学研究院地中海气候与农业水利系统模拟实验室阿维尼翁84914 国家节水灌溉杨凌工程技术研究中心陕西杨凌712100

对枣树树体进行梯度修剪,采用热扩散探针(TDP)液流监测系统和中子水分仪对枣树的蒸腾和土壤水分进行同步动态监测,通过2年连续监测发现:修剪对枣树不同时间尺度上的蒸腾均有显著影响。修剪可以显著降低枣树开花坐果期和果实膨大期的树... 详细信息

对枣树树体进行梯度修剪,采用热扩散探针(TDP)液流监测系统和中子水分仪对枣树的蒸腾和土壤水分进行同步动态监测,通过2年连续监测发现:修剪对枣树不同时间尺度上的蒸腾均有显著影响。修剪可以显著降低枣树开花坐果期和果实膨大期的树体蒸腾,降低对土壤水分的消耗。与对照处理相比,轻度、中度和重度修剪的枣树全生育期蒸腾总量分别下降31.7%、52.0%和68.6%。通过线性和非线性的分析方法,分析了蒸腾和树体规格指标之间的关系,构建了自然降水量和修剪目标产量的数学模型。提出适宜的陕北枣林可持续经营的目标产量为1.2×104kg/hm2,适宜的节水型修剪调控树体指标为冠幅体积和新稍长度。

关键词：节水型修剪蒸腾树体结构土壤干层灰色关联度

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Global Wheat Head Detection(GWHD)Dataset:A Large and Diverse Dataset of High-Resolution RGB-Labelled Images to Develop and Benchmark Wheat Head Detection Methods

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Plant Phenomics 2020年第1期2卷 243-254页

作者： Etienne David Simon Madec Pouria Sadeghi-Tehran Helge Aasen Bangyou Zheng shouyang liu Norbert Kirchgessner Goro Ishikawa Koichi Nagasawa Minhajul A.Badhon Curtis Pozniak Benoit de Solan Andreas Hund Scott C.Chapman Frédéric Baret Ian Stavness Wei Guo Arvalis Institut du végétal3 Rue Joseph et Marie Hackin75116 ParisFrance UMR1114 EMMAH INRAECentre PACABâtiment ClimatDomaine Saint-Paul228 Route de l’AérodromeCS 4050984914 Avignon CedexFrance Plant Sciences Department Rothamsted ResearchHarpendenUK Institute of Agricultural Sciences ETH ZurichUniversitätstrasse 28092 ZurichSwitzerland CSIRO Agriculture and Food Queensland Biosciences Precinct306 Carmody RoadSt Lucia4067 QLDAustralia Plant Phenomics Research Center Nanjing Agricultural UniversityNanjingChina Institute of Crop Science National Agriculture and Food Research OrganizationJapan Hokkaido Agricultural Research Center National Agriculture and Food Research OrganizationJapan Department of Computer Science University of SaskatchewanCanada Department of Plant Sciences University of SaskatchewanCanada School of Food and Agricultural Sciences The University of QueenslandGatton4343 QLDAustralia Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan

The detection of wheat heads in plant images is an important task for estimating pertinent wheat traits including head population density and head characteristics such as health,size,maturity stage,and the presence of *** studies have developed methods for wheat head detection from high-resolution RGB imagery based on machine learning ***,these methods have generally been calibrated and validated on limited *** variability in observational conditions,genotypic differences,development stages,and head orientation makes wheat head detection a challenge for computer ***,possible blurring due to motion or wind and overlap between heads for dense populations make this task even more *** a joint international collaborative effort,we have built a large,diverse,and well-labelled dataset of wheat images,called the Global Wheat Head Detection(GWHD)*** contains 4700 high-resolution RGB images and 190000 labelled wheat heads collected from several countries around the world at different growth stages with a wide range of *** for image acquisition,associating minimum metadata to respect FAIR principles,and consistent head labelling methods are proposed when developing new head detection *** GWHD dataset is publicly available at http://***/and aimed at developing and benchmarking methods for wheat head detection.

关键词： Wheat wheat maturity

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Shuttleworth-Wallace模型模拟陕北枣林蒸散适用性分析

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农业机械学报 2015年第3期46卷 142-151页

作者：卫新东刘守阳陈滇豫汪有科汪星魏新光西北农林科技大学水利与建筑工程学院陕西杨凌712100 长安大学地球科学与资源学院西安710054 法国国家农业科学研究院(INRA)地中海气候与农业水利系统模拟实验室阿维尼翁84914 中国科学院水利部水土保持研究所陕西杨凌712100

在生态脆弱的陕北黄土丘陵区,林地耗水是生态学者长期关注的热点问题,准确测算植物耗水量是环境水分研究的关键。根据陕北山地枣林的立地条件和蒸散过程特点,结合2012年的实测资料,确定了相关模型参数,实现了Shuttleworth-Wallace(SW)和... 详细信息

在生态脆弱的陕北黄土丘陵区,林地耗水是生态学者长期关注的热点问题,准确测算植物耗水量是环境水分研究的关键。根据陕北山地枣林的立地条件和蒸散过程特点,结合2012年的实测资料,确定了相关模型参数,实现了Shuttleworth-Wallace(SW)和Penman-Monteith(PM)模型对枣林蒸散量的模拟,并利用2013年茎流计监测的蒸腾量和水量平衡原理推求的蒸散量,对这2个模型进行了比较和检验。结果表明:就整个枣树生育期10 d尺度蒸散量而言,SW模型模拟精度优于PM模型。此外,2模型精度随枣树生育期变化而变化,且萌芽展叶期精度均最低。SW模型日蒸腾量模拟精度满足要求,但易受到天气状况影响,晴天模型精度优于雨天。SW模型精度在陕北山地枣林里得到验证,是半干旱区山地枣林耗水规律研究的有效工具。

关键词：梨枣 Shuttleworth-Wallace 模型 Penman-Monteith 蒸散量

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种植年限对黄土丘陵半干旱区山地枣树蒸腾的影响

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农业机械学报 2015年第7期46卷 171-180页

作者：魏新光王铁良刘守阳李波聂真义汪有科沈阳农业大学水利学院沈阳110866 法国国家农业科学研究院地中海气候与农业水利系统模拟实验室阿维尼翁84914 国家节水灌溉杨凌工程技术研究中心陕西杨凌712100 中国科学院水利部水土保持研究所陕西杨凌712100

为了研究山地成年枣树的蒸腾特征以及不同种植年限枣树蒸腾耗水的差异性,运用TDP液流监测系统对山地枣树的蒸腾进行了连续3年的动态监测。通过分析发现：枣树蒸腾日内变化呈单峰变化趋势,而且随着生育期变化呈窄峰-宽峰-窄峰变化。水汽... 详细信息

为了研究山地成年枣树的蒸腾特征以及不同种植年限枣树蒸腾耗水的差异性,运用TDP液流监测系统对山地枣树的蒸腾进行了连续3年的动态监测。通过分析发现：枣树蒸腾日内变化呈单峰变化趋势,而且随着生育期变化呈窄峰-宽峰-窄峰变化。水汽压亏缺（VPD）和光合有效辐射量（PAR）对枣树的蒸腾存在明显的时滞现象和阈值特征,蒸腾对VPD和PAR响应的上限阈值分别为3.5 k Pa和1 000-1 200μmol/（m^2·s）。枣树全生育期逐日蒸腾呈现明显的单峰现象,夜间蒸腾约占全日蒸腾的5%-33%。2012—2014年不同树龄枣树蒸腾量由小到大依次为3 a、5 a、12 a,不同树龄枣树蒸腾耗水之间存在极显著的差异性（p0.01）,而且年际之间的蒸腾波动变化规律不同。由于采取了树体修剪调控措施,12 a生成年枣树年际之间蒸腾差异并不显著（p〉0.05）,各年耗水量基本稳定在293-334 mm之间。由此可见,通过控制树体规模可以调控树体的水分消耗。

关键词：枣树蒸腾量树龄差异性

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黄土丘陵区枣林土壤水分动态及其对蒸腾的影响

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农业机械学报 2015年第6期46卷 130-140页

作者：魏新光聂真义刘守阳佘檀马建鹏汪有科西北农林科技大学水利与建筑工程学院陕西杨凌712100 国家节水灌溉杨凌工程技术研究中心陕西杨凌712100 西北农林科技大学水土保持研究所陕西杨凌712100 法国国家农业科学研究院地中海气候与农业水利系统模拟实验室阿维尼翁84914 中国科学院水利部水土保持研究所陕西杨凌712100

为了探明黄土高原半干旱区山地枣林蒸腾和土壤水分间的关系，对山地枣林的土壤水分和枣树茎液流动态进行了连续 3 年的定位监测，结果表明：土壤水分时空变异性显著，土壤水分垂直方向上随着土层深度的增加，变异系数（Cv）逐渐降低。... 详细信息

为了探明黄土高原半干旱区山地枣林蒸腾和土壤水分间的关系，对山地枣林的土壤水分和枣树茎液流动态进行了连续 3 年的定位监测，结果表明：土壤水分时空变异性显著，土壤水分垂直方向上随着土层深度的增加，变异系数（Cv）逐渐降低。其自上而下可划分为土壤水分变化层（0-2.6m）、土壤水分干层（2.6-6.0m）和土壤水分恢复层（6.0-10.0m）。枣树液流监测的参数在生育期和休眠期间具有显著性差异，根据这一特征可以对枣树生育期进行较为准确的界定。基于液流参数特征确定的生育期与观察树体萌芽落叶确定的生育期时长基本一致，均约为 160d，但基于液流参数确定的生育期较后者约提前 5d。土壤水分的增加会使枣树液流（瞬时蒸腾）的谷值出现时间提前，峰值出现时间推后，“午休”时间缩短，旺盛蒸腾时间延长，反之亦然。枣树生育前期蒸腾均呈逐日增加趋势，而生育中后期蒸腾和土壤水分呈极显著的正相关关系。

关键词：土壤水分蒸腾土壤干层液流特征黄土丘陵区

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秦岭地区连香树分布现状与濒危机理

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东北林业大学学报 2012年第6期40卷 19-22页

作者：杨荣慧孙宝胜刘守阳西北农林科技大学杨凌712100

研究了陕西秦岭和秦巴山区连香树种群分布区域、生存立地环境、种群径级结构、自然繁殖更新特征和濒危因素等。结果表明:陕西连香树主要分布于秦岭北纬35°30'～37°48'之间的17个县,分布在海拔高度1 408～1 889 m。区内种群均为远距离... 详细信息

研究了陕西秦岭和秦巴山区连香树种群分布区域、生存立地环境、种群径级结构、自然繁殖更新特征和濒危因素等。结果表明:陕西连香树主要分布于秦岭北纬35°30'～37°48'之间的17个县,分布在海拔高度1 408～1 889 m。区内种群均为远距离间断性片状、块状、散生和单株生存。秦岭连香树主要濒危因素为雌雄异株,且株间距离较远致使授粉不良,种子个形微小、质量轻,发育质量差。较厚的林下枯枝落叶层阻碍了种子与土壤的接触,即使种子发芽胚根也易枯萎,不易发育成苗。此外,人为砍伐使种源母树减少,砍伐后虽偶有从根基萌蘖新株,但萌蘖繁殖只能维持种群现状。由于自身繁殖更新的局限性和人类对其生存环境的破坏,致使连香树种群结构断代严重,种群消亡的危险性在不断加剧。

关键词：秦岭连香树资源分布种群结构濒危因素

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