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不同水分处理对甘平果实裂果及相关生理特性的影响

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西南大学学报（自然科学版） 2024年第6期46卷 74-87页

作者：陈晓林陈星宏马梦雨马岩岩郑永强易时来吕强谢让金西南大学柑桔研究所/国家柑橘工程技术研究中心/国家数字种植业(柑橘)创新分中心重庆400712

选取易裂果品种甘平作为研究对象,统计果实发育过程中不同土壤水分变化幅度及不同土壤相对含水量处理下裂果的发生率,检测各处理下树体及果实相关的生理指标变化,利用数据统计学探究其与裂果的相关性,进而解析水分调控对甘平裂果发生率... 详细信息

选取易裂果品种甘平作为研究对象,统计果实发育过程中不同土壤水分变化幅度及不同土壤相对含水量处理下裂果的发生率,检测各处理下树体及果实相关的生理指标变化,利用数据统计学探究其与裂果的相关性,进而解析水分调控对甘平裂果发生率的影响.结果显示,甘平裂果时间主要发生在盛花后120~150 d,即果实膨大期(每年7-8月),属于外裂果.水分控制试验结果显示,土壤相对含水量75%、变化幅度20%以内能有效控制裂果发生.与其他处理相比,75%土壤含水量下植株的光合速率最强,叶片和果实的相对含水量、水势、N、K和Ca含量显著增高,果实的总果胶、纤维素质量分数最高,而OFR,H_(2)O_(2),MDA的摩尔质量最低.相关性分析结果显示,叶片和果皮的水势和含水量、果皮细胞纤维素和总果胶的质量分数以及活性氧代谢与裂果率显著相关,推测在适宜的土壤含水量,植株能有效增强光合作用和抗逆性,进而通过增加果皮厚度和延展性增强果实的抗裂性.

关键词：甘平裂果水分平衡细胞壁物质活性氧酶活性

重庆三峡库区塔罗科血橙不同树形的冠层特性、产量和品质分析

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西南大学学报（自然科学版） 2024年第1期46卷 59-68页

作者：田洋喻莹何瑞杰何满郑永强吕强谢让金马岩岩邓烈朱文祥易时来西南大学柑桔研究所/中国农业科学院柑桔研究所/国家柑桔工程技术研究中心/国家数字种植业(柑橘)创新分中心重庆400712 重庆三峡职业学院农林科技学院重庆万州404155 重庆蕤峰园农业有限公司重庆万州404000

以11年生枳橙砧塔罗科血橙为试验对象,设计圆头形、主干形、开心形等3种树形处理,研究不同树形对血橙冠层特性、快速叶绿素荧光、果实产量及品质等的影响,提出重庆三峡库区塔罗科血橙最适宜的树形,为血橙优质丰产树形培养和树体改造提... 详细信息

以11年生枳橙砧塔罗科血橙为试验对象,设计圆头形、主干形、开心形等3种树形处理,研究不同树形对血橙冠层特性、快速叶绿素荧光、果实产量及品质等的影响,提出重庆三峡库区塔罗科血橙最适宜的树形,为血橙优质丰产树形培养和树体改造提供技术支撑与理论依据.结果表明,3种树形的冠层特性存在明显差异,其中冠层透光性从强到弱依次为开心形、主干形、圆头形;主干形和开心形的PSII原初最大光能转换效率(Fv/Fm)、春梢叶片单位面积吸收的光能(ABS/CSo)明显提升,反应中心的热消耗(DIo/RC)和秋梢叶片单位面积热耗散能量(DIo/CSo)显著降低.主干形和开心形均能有效提升春、秋梢叶片的光合结构性能(PI abs,PI total),以主干形处理相对最佳.2022-2023年度产量、单果质量、固酸比和维生素C含量从高到低均依次为主干形、开心形、圆头形,可溶性固形物和花色苷含量从高到低依次为开心形、主干形、圆头形.因此,重庆三峡库区塔罗科血橙宜选择主干形树形进行培养,以获得最佳产量和品质.

关键词：重庆三峡库区塔罗科血橙树形冠层特性产量品质

目标检测算法YOLOv5s用于柑桔成熟果实检测的改进

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中国南方果树 2024年第1期53卷 224-231页

作者：蹇川郑永强刘艳梅马岩岩易时来吕强谢让金西南大学工程技术学院重庆400715 西南大学柑桔研究所/国家柑桔工程技术研究中心/国家数字种植业(柑桔)创新分中心重庆400712 重庆市北碚区经济作物技术推广站重庆400700

巡检机器人精准检测成熟柑桔果实,对于保证柑桔果园产量巡检作业效率和质量至关重要。考虑到成熟柑桔果实特有的颜色空间、果实遮挡导致的小目标以及巡检机器人有限的硬件资源,提出一种简单有效的基于YOLOv5s的柑桔成熟果实检测方法—... 详细信息

巡检机器人精准检测成熟柑桔果实,对于保证柑桔果园产量巡检作业效率和质量至关重要。考虑到成熟柑桔果实特有的颜色空间、果实遮挡导致的小目标以及巡检机器人有限的硬件资源,提出一种简单有效的基于YOLOv5s的柑桔成熟果实检测方法———改进YOLOv5s。改进YOLOv5s,主要设计一个由3层Context Aggregation Block(CABlock)组成的金字塔结构特征提取层并将其插入到YOLOv5s网络的Head部分。改进YOLOv5s模型具有如下优点:(1)集成的底层CABlock通过特征通道注意力机制和空间注意力机制,能更好更快地学习小目标局部成熟果实颜色和纹理特征、重叠果实边缘特征;(2)多层CABlock构建的特征金字塔能够有效地避免小目标随网络深度增加而消失,从而降低小目标果实漏检率。柑桔成熟果实识别验证试验结果表明,改进YOLOv5s的检测准确率和平均精度分别为98.21%和98.07%,较原始YOLOv5s分别提升了0.31和0.17百分点,较FasterR-CNN分别提升了8.41和8.31百分点,识别遮挡果实、重叠果实以及小目标果实的平均精度分别为99.4%、97.2%和98.0%;单张成熟柑桔果实图像的平均检测时间32.5ms,模型占用内存15.8 MB。该改进YOLOv5s模型可实现果园自然环境下柑桔成熟果实快速准确地检测识别与产量预估,可为柑桔果园巡检机器人产量巡检提供技术支持。

关键词：柑桔成熟果实 YOLOv5s Context Aggregation Block 目标检测产量预估

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Prediction of nitrogen and phosphorus contents in citrus leaves based on hyperspectral imaging

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International Journal of Agricultural and Biological Engineering 2015年第2期8卷 80-88页

作者： Liu Yanli Lyu Qiang He Shaolan Yi Shilai Liu Xuefeng xie rangjin Zheng Yongqiang Deng Lie College of Horticulture and Landscape Southwest UniversityBeibeiChongqing 400715China Citrus Research Institute Southwest University-Chinese Academy of Agricultural SciencesBeibeiChongqing 400712China

The nutritional status of citrus leaves is very important to the determining of fertilization *** spectrum technique is a quick,un-injured method and is becoming widely used for plant nutrient *** possibility and method of using spectrum technique to estimate the nutrient of citrus leaf was explored in this study.A total amount of 135 leaves from the mature spring shoots of navel orange trees(*** Osbeck,“Newhall”)were collected and randomly grouped into two sets of samples:100 leaves for the calibration set and 35 leaves for the prediction *** hyperspectral images were scanned upper and lower side of each leaf and then the total nitrogen(N)and phosphorus(P)contents of each leaf were *** raw spectra data were extracted to generate average spectra curves,preprocessed with five different methods,and was used to build N and P content prediction *** performances of the five preprocessing methods,i.e.,Savitzky-Golay smoothing(SGS),standard normal variate(SNV),multiplicative scatter correction(MSC),first-derivative(1-Der)and second-derivative(2-Der),were tested with linear partial least squares(PLS)models and nonlinear least squares-support vector machine(LS-SVM)*** results showed that the SG-PLS and PLS were the best for the N predicting(Rp=0.9049,RMSEP=0.1041)and P(Rp=0.9235,RMSEP=0.0514)in citrus leaves,respectively;the hyperspectral image data from leaf‟s upper side predicting better for the contents of N and *** study suggested that the hyperspectral image data from the upper side of the citrus leaves are suitable for nondestructive estimation of nutrient content.

关键词： citrus leaves nitrogen phosphorus prediction hyperspectral imaging

Estimation of carbon and nitrogen contents in citrus canopy by low-altitude remote sensing

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International Journal of Agricultural and Biological Engineering 2016年第5期9卷 149-157页

作者： Liu Xuefeng Lyu Qiang He Shaolan Yi Shilai Hu Deyu Wang Zhitao xie rangjin Zheng Yongqiang Deng Lie Citrus Research Institute Southwest University-Chinese Academy of Agricultural SciencesChongqing 400712China Institute of Optics-Mechanics-Electronics Technology and Application East China Jiaotong UniversityNanchang 330013China College of Horticulture and Landscape Southwest UniversityChongqing 400715China

The study aimed to investigate the fast and nondestructive method for detecting carbon and nitrogen content in citrus *** multispectral imagery of Tarocco blood orange(Citrus sinensis ***)plant canopy was obtained by a multispectral camera array mounted at an eight-rotor unmanned aerial vehicle(UAV)flying at an altitude of 100 m above the canopy in Wanzhou District of Chongqing Municipality,*** spectral reflectance data of the whole canopy,mature leaf areas and young leaves areas were extracted from the *** spectral pre-processing methods,multiplicative scatter correction(MSC)and standard normal variable(SNV),and two modeling methods,the partial least squares(PLS)and the least squares support vector machine(LS-SVM),were adopted and compared for their prediction accuracy of total content of nitrogen,soluble sugar and starch in the *** results showed that,based on the spectral data extracted from the mature leaves in the multispectral imagery,the PLS model based on the original spectrum obtained a Rp(correlation coefficient)of 0.6469 and RMSEP(root mean squares error of prediction)of 0.1296,suggested that it was the best for the prediction of total nitrogen content;the PLS model based on MSC(multiplicative scatter correction)spectrum pre-processing was the best for predicting total soluble sugar content(Rp=0.6398 and RMSEP=8.8891);and the LS-SVM model based on MSC was the best for the starch content prediction(Rp=0.6822 and RMSEP=14.9303).The prediction accuracy for carbon and nitrogen contents based on the spectral data extracted from the whole canopy and the young leaves were lower than that from the mature *** results indicate that it is feasible to estimate the carbon and nitrogen contents by low-altitude airborne multispectral images.

关键词： citrus canopy low-altitude remote sensing carbon and nitrogen contents soluble sugar starch estimation

Rapid detection of chlorophyll content and distribution in citrus orchards based on low-altitude remote sensing and bio-sensors

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International Journal of Agricultural and Biological Engineering 2018年第2期11卷 164-169页

作者： Kejian Wang Wentao Li Lie Deng Qiang Lyu Yongqiang Zheng Shilai Yi rangjin xie Yanyan Ma Shaolan He Citrus Research Institute of Chinese Academy of Agricultural Sciences Southwest UniversityBeibeiChongqing 400712China

The accuracy of detecting the chlorophyll content in the canopy and leaves of citrus plants based on sensors with different scales and prediction models was investigated for the establishment of an easy and highly-efficient real-time nutrition diagnosis technology in citrus *** fluorescent values of leaves and canopy based on the Multiplex 3.6 sensor,canopy hyperspectral reflectance data based on the FieldSpec4 radiometer and spectral reflectance based on low-altitude multispectral remote sensing were collected from leaves of Shatang mandarin and then ***,the associations of the leaf SPAD(soil and plant analyzer development)value with the ratio vegetation index(RVI)and normalized differential vegetation index(NDVI)were *** leaf SPAD value predictive model was established by means of univariate and multiple linear regressions and the partial least squares *** distribution maps of the relative canopy chlorophyll content based on spectral reflectance in the orchard were automatically *** results showed that the correlations of the SPAD values obtained from the Multiplex 3.6 sensor,FieldSpec4 radiometer and low-altitude multispectral remote sensing were highly *** measures of goodness of fit of the predictive models were R^(2)=0.7063,RMSECV=3.7892,RE=5.96%,and RMSEP=3.7760 based on RVI_((570/800)) and R^(2)=0.7343,RMSECV=3.6535,RE=5.49%,and RMSEP=3.3578 based on NDVI[(570,800)(570,950)(700,840)].The technique to create spatial distribution maps of the relative canopy chlorophyll content in the orchard was established based on sensor information that directly reflected the chlorophyll content of the plants in different parts of the orchard,which in turn provides evidence for implementation of orchard productivity evaluation and precision in fertilization management.

关键词： citrus remote sensing bio-sensor chlorophyll detection spectrum ratio vegetation index(RVI) normalized differential vegetation index(NDVI) spatial distribution map

Mass extinctions, their causes and consequences: an interview with Douglas *** and Shuzhong Shen

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National Science Review 2024年第1期11卷 66-70页

作者： Shucheng xie State Key Laboratory of Biogeology and Environmental Geology China University of Geosciences at Wuhan

‘Mass extinctions’ have been a hot topic for several decades. What triggers a mass extinction? How does a mass extinction impact the evolution of life? How does our ecosystem recover after a mass extinction? These questions attracted the interest of both scientists and the public *** spoke to two renowned researchers in the field of mass extinctions: Prof. Douglas H. Erwin from the National Museum of Natural History of the USA, and Prof. Shuzhong Shen from Nanjing University, China.

关键词： Stratigraphy

Detection of Huanglongbing(citrus greening) based on hyperspectral image analysis and PCR

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Frontiers of Agricultural Science and Engineering 2019年第2期6卷 172-180页

作者： Kejian WANG Dongmei GUO Yao ZHANG Lie DENG rangjin xie Qiang LV Shilai YI Yongqiang ZHENG Yanyan MA Shaolan HE Southwest University/Citrus Research Institute of Chinese Academy of Agricultural Sciences Chongqing 400712 China National Agricultural Technology Extension and Service Center Beijing 100125 China Chengdu Plant Quarantine Station Chengdu 610000 China Key Laboratory of Modern Precision Agriculture System Integration Research China Agricultural University Beijing 100083 China

Huanglongbing (HLB, citrus greening) is one of the most serious quarantine diseases of citrus worldwide. To monitor in real-time, recognize diseased trees, and efficiently prevent and control HLB disease in citrus, it is necessary to develop a rapid diagnostic method to detect HLB infected plants without symptoms. This study used Newhall navel orange plants as the research subject, and collected normal color leaf samples and chlorotic leaf samples from a healthy orchard and an HLB-infected orchard, respectively. First, hyperspectral data of the upper and lower leaf surfaces were obtained, and then the polymerase chain reaction (PCR) was used to detect the HLB bacterium in each leaf. The PCR test results showed that all samples from the healthy orchard were negative, and a portion of the samples from the infected orchard were positive. According to these results, the leaf samples from the orchards were divided into disease-free leaves and HLB-positive leaves, and the least squares support vector machine recognition model was established based on the leaf hyperspectral reflectance. The effect on the model of the spectra obtained from the upper and lower leaf surfaces was investigated and different pretreatment methods were compared and analyzed. It was observed that the HLB recognition rate values of the calibration and validation sets based on upper leaf surface spectra under 9-point smoothing pretreatment were 100% and 92.5%, respectively. The recognition rate values based on lower leaf surface spectra under the second-order derivative pretreatment were also 100% and 92.5%, respectively. Both upper and lower leaf surface spectra were available for recognition of HLB-infected leaves, and the HLB PCR-positive leaves could be distinguished from the healthy by the hyperspectral modeling analysis. The results of this study show that early and nondestructive detection of HLBinfected leaves without symptoms is possible, which provides a basis for the hyperspectral diagnosi

关键词： citrus HLB hyperspectral identification PCR

Turbulence Statistics of Thermo-Buoyancy Supercritical Fuel Flow in a Regenerative Cooling Channel

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Journal of Thermal Science 2024年第1期33卷 126-137页

作者： SUN Feng xie Gongnan School of Marine Science and Technology Northwestern Polytechnical UniversityXi'an 710072China Department of Thermal Engineering Tsinghua UniversityBeijing 100084China

Active regenerative cooling with supercritical hydrocarbon fuel is considered as the most promising thermal protection *** existence of buoyancy force would lead to strongly anisotropic flow and thermal transport *** is closely related to the cooling performance of the *** elucidate the mechanisms of turbulent transport,the large eddy simulation(LES) was performed to assess turbulence statistics within different turbulence *** results indicated that the buoyancy and inertial force together dominated the change of turbulent ***,the spatial thermal buoyancy effect significantly suppressed the vertical velocity *** is due to the laminar motion caused by the buoyancy force,thereby weakening the thermal *** the statistics of velocity fluctuation,it was found that the buoyancy force and inertial force greatly weaken the vertical and streamwise velocity fluctuation,*** the statistics of thermal transport,the results pointed out that the near-wall heat transport characteristics need to be paid more *** thickness of the temperature mixing boundary layer led to the attenuation of vertical heat flux,which inhibited vertical temperature diffusion and predisposed to extreme conditions of heat transfer *** results can enhance the academic understanding of the heat transfer mechanism of supercritical fluids,and give guidance for further applications of thermal protection.

关键词： active regenerative cooling large eddy simulation(LES) buoyancy force turbulence statistics