基于高光谱成像技术的柑橘黄龙病病情诊断及分类

【目的】柑橘黄龙病(Citrus Huanglongbing,HLB)是一种无法根治且易扩散的病害,建立柑橘黄龙病病情诊断及分类的方法,以及时发现并去除病株,防止感染其他果树。【方法】基于高光谱成像技术,利用最小噪声分离变换进行降维去噪、像元纯净指数获取纯净像元并建立训练集,通过Fisher判别法对柑橘黄龙病病情进行鉴别并分类。【结果】通过对训练集设置适当的门限值,柑橘黄龙病病情识别正确率达90%以上。【结论】利用高光谱技术进行柑橘黄龙病病情诊断具有较高的可行性。     

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

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 HLB-infected leaves without symptoms is possible, which provides a basis for the hyperspectral diagnosis of citrus with HLB.     

武汉市藏龙岛地区行道树绿化现状调查

对武汉市藏龙岛地区24条道路的绿化配置模式进行了调查,统计了行道树的品种、高度、胸径、应用频度及长势等指标。结果表明,该地区道路的绿化形式有一板二带式、二板三带式、三板四带式、四板五带式与其他5种形式,行道树种植设计形式有树池式、树带式、混合式及其他4种形式,行道树树种有13种,隶属于11科12属,以香樟、杜英、法桐、垂柳为主,有4条道路的行道树长势较差,有明显的病虫危害现象。     

果树在信阳市园林绿化中的应用分析

结合信阳地区的气候条件,分析了适宜在本地栽培并可用于园林绿化的果树,如枇杷、石榴、银杏、枣树、板栗等,并提出果树在园林绿化应用中应注意的问题。     

柑橘变温压差膨化干燥工艺优化研究

通过变温压差膨化干燥技术生产柑橘膨化产品,采用二次回归正交旋转组合实验设计和响应面分析法,探讨原料预干燥后含水率、膨化温度、真空干燥时间等工艺参数对膨化产品质量的影响,对其工艺参数组合进行优化.结果表明:原料预干燥后含水率、膨化温度和真空干燥时间对膨化柑橘含水率、脆度、膨化度和色泽有显著影响;柑橘膨化最佳生产工艺为,预干燥后原料含水率35%、膨化温度95℃、停滞时间5 min、压力差0.1 MPa、抽空温度80℃、真空干燥时间2.5 h;响应面分析法可以直观反映各因素与膨化产品质量指标之间的关系,实现对柑橘变温压差膨化工艺的优化.     

Spectral requirements on airborne hyperspectral remote sensing data for wheat disease detection

Remote sensing approaches are of increasing importance for agricultural applications, particularly for the support of selective agricultural measures that increase the productivity of crop stands. In contrast to multi-spectral image data, hyperspectral data has been shown to be highly suitable for the detection of crop growth anomalies, since they allow a detailed examination of stress-dependent changes in certain spectral ranges. However, the entire spectrum covered by hyperspectral data is probably not needed for discrimination between healthy and stressed plants. To define an optimal sensor-based system or a data product designed for crop stress detection, it is necessary to know which spectral wavelengths are significantly affected by stress factors and which spectral resolution is needed. In this study, a single airborne hyperspectral HyMap dataset was analyzed for its potential to detect plant stress symptoms in wheat stands induced by a pathogen infection. The Bhattacharyya distance (BD) with a forward feature search strategy was used to select relevant bands for the differentiation between healthy and fungal infected stands. Two classification algorithms, i.e. spectral angle mapper (SAM) and support vector machines (SVM) were used to classify the data covering an experimental field. Thus, the original dataset as well as datasets reduced to several band combinations as selected by the feature selection approach were classified. To analyze the influence of the spectral resolution on the detection accuracy, the original dataset was additionally stepwise spectrally resampled and a feature selection was carried out on each step. It is demonstrated that just a few phenomenon-specific spectral features are sufficient to detect wheat stands infected with powdery mildew. With original spectral resolution of HyMap, the highest classification accuracy could be obtained by using only 13 spectral bands with a Kappa coefficient of 0.59 in comparison to Kappa 0.57 using all spectral bands of the HyMap sensor. The results demonstrate that even a few hyperspectral bands as well as bands with lower spectral resolution still allow an adequate detection of fungal infections in wheat. By focusing on a few relevant bands, the detection accuracy could be enhanced and thus more reliable information could be extracted which may be helpful in agricultural practice.     

基于改进MobileNetV2的柑橘害虫分类识别方法

为提高柑橘害虫识别精准度和防治效果,本研究构建包含10类对柑橘危害程度较重的害虫图像数据集,基于神经网络MobileNetV2与注意力机制ECA开发轻量化且高识别精度的ECA＿MobileNetV2模型,并基于该模型开发一款边缘计算App。将ECA注意力机制嵌入MobileNetV2网络的反残差结构尾部,以增强原网络的跨通道信息交互能力,提升原网络的特征提取能力。测试结果显示,ECA＿MobileNetV2模型对柑橘害虫的分类准确率达到93.63%,相比于MobileNetV2、GoogLeNet和ResNet18模型分别提高了1.68、1.44和2.40个百分点,而模型参数量、浮点运算数和模型大小分别为3.50×10⁶、328.06×10⁶和8.72 MB,复杂度仅略高于MobileNetV2,可以在手机上以边缘计算的形式运行。研究结果表明,本研究开发的智能识别工具能够对不同种类的柑橘害虫进行快速、有效的分类识别。     

A high-resolution airborne four-camera imaging system for agricultural remote sensing

This paper describes the design and testing of an airborne multispectral digital imaging system for remote sensing applications. The system consists of four high resolution charge coupled device (CCD) digital cameras and a ruggedized PC equipped with a frame grabber and image acquisition software. The cameras are sensitive in the 400 to 1000 nm spectral range and provide 2048 × 2048 active pixels with 12-bit data depth. A 24 mm lens is attached to each camera via an F to C mount adapter, resulting in an imaging size of 0.63 times the flight altitude. The four cameras are equipped with blue (430–470 nm), green (530–570 nm), red (630–670 nm), and near-infrared (NIR) (810–850 nm) bandpass interference filters, respectively, but have the flexibility to change filters for desired wavelengths and bandwidths. The cameras are arranged in a quad configuration and attached to adjustable mounts that facilitate aligning the cameras horizontally, vertically, and rotationally. The image acquisition software allows the synchronized black-and-white band images from the cameras to be viewed on the computer monitor in any one of the four modes: a quad, one band image at a time, a normal color composite, or a color-infrared (CIR) composite. The band images are refreshed continuously to allow the operator to selectively save images with correct areas of interest. The selected four-band composite image is saved as a tiff file and consecutive images can be saved in 1-s intervals. A band-to-band alignment procedure based on the first- and second-order polynomial transformations was presented to further align the four band images. The system performed well in both stationary and airborne testing conditions. Airborne images obtained from agricultural fields, rangelands, and waterways demonstrate that this system has potential for monitoring crop pest conditions, mapping invasive weeds and assessing natural resources.     

Determining leaf stomatal properties in citrus trees utilizing machine vision and artificial intelligence

Precision Agriculture - Identifying and quantifying the number and size of stomata on leaf surfaces is useful for a wide range of plant ecophysiological studies, specifically those related to...     

Determining leaf nutrient concentrations in citrus trees using UAV imagery and machine learning

Precision Agriculture - Nutrient assessment of plants, a key aspect of agricultural crop management and varietal development programs, traditionally is time demanding and labor-intensive. This...     

铅胁迫对六种绿化树种叶片生理生化特性的影响

为给受污染地区绿化树种的选择提供借鉴,通过盆栽实验研究了不同浓度Pb胁迫对6个2年生绿化树种叶片生理生化的影响。结果表明:随着浓度的升高,6种绿化植物的SOD、POD活性呈现先升高后急剧下降的趋势,而相对电导率则呈一直上升的趋势。随铅胁迫时间的延长,SOD、POD、CAT活性和相对电导率均呈现逐渐增加的趋势。各树种抗铅胁迫能力表现为:侧柏>栾树>连翘>紫叶小檗>迎春>红瑞木;侧柏抗铅迫胁能力极显著的大于红瑞木和栾树,连翘显著大于紫叶小檗、迎春,极显著>红瑞木。栾树和连翘之间的差异不显著,紫叶小檗和迎春之间的差异也不显著。     

拟木蠹蛾对广西桂中地区绿化树种危害调查

2011年10月至2012年2月,采用线路踏查法和标准地调查法对广西柳州市和来宾市绿化树种拟木蠹蛾危害进行调查。共调查122种绿化树,受拟木蠹蛾危害的树种达45种,占调查树种总数的36.9%,平均危害程度达成灾标准的8种,局部成灾的31种,发生普遍,危害严重。拟木蠹蛾主要分布于树干中下部,98%蛀道向下,主要从树枝分叉和破伤处侵入。建议在生产上采用人工的、物理的或化学的方法进行防治。     

一种快速高效适于柑桔AFLP分析的DNA提取方法

利用改进的CTAB法提取了柑类、桔类、橙类及部分柑桔杂交实生后代等120多个品种的基因组,结果表明:该方法提取的DNA溶液无色透明,紫外分光光度计测得A260/A280为1.8～1.9,1%琼脂糖凝胶电泳为清晰的一条带,RNA去除干净,无降解现象,DNA的纯度和质量能满足AFLP分析要求.     

基于Mixup算法和卷积神经网络的柑橘黄龙病果实识别研究

目的 解决传统柑橘黄龙病果实图像识别方法依赖人工设计特征、费时费力、网络模型参数量大、识别准确率低等问题。方法 首先,采集柑橘黄龙病的果实图像,并对其进行翻转、旋转、仿射、高斯扰动等数据扩增;采用Mixup算法建立样本之间的线性关系,增强模型识别数据样本的鲁棒性;然后,迁移Xception网络在ImageNet数据集上的先验知识,提出一种基于Mixup算法和卷积神经网络的柑橘黄龙病果实识别模型-X-ResNeXt模型;最后,采用动量梯度下降优化方法,有效地减缓震荡影响,并且有效地加速模型向局部最优点收敛。结果 采用数据扩增数据集训练的X-ResNeXt模型准确率可以达到91.38%;在进行迁移学习优化后,训练时间减少了432 s,准确率提升为91.97%;结合Mixup混类数据增强进一步训练,模型准确率提升为93.74%;最后,利用动量梯度下降方法进行模型收敛优化,最终模型的准确率达到94.29%,比Inception-V3和Xception网络分别提高了3.98%和1.51%。结论 在数据量较少情况下,降低模型复杂度并迁移已有先验知识,有助于模型性能提升;Mixup混类数据增强方法有利于提高模型识别柑橘黄龙病果实图像样本的适应性,提升柑橘黄龙病果实识别模型性能;X-ResNeXt模型在准确率与召回率指标上优于经典识别模型,可为柑橘黄龙病的高精度、快速无损识别提供参考。     

晚熟柑橘山地果园小区域环境温湿度差异调查

为完善南充地区晚熟柑橘越冬技术理论体系,探寻山地果园不同小区域环境的温湿度差异,便于科学进行晚熟柑橘越冬管理。本研究于2021-2022年冬季在四川省南充市开展了山地果园不同地势、不同天气下的温湿度差异调查。调查得知,同一山地果园不同地势的温湿度差异明显,尤其是温度的差异。同一果园洼地的平均温度和最低温度最低,≦0 ℃和≦-1 ℃的天数及最长持续时长均为洼地>半山腰>山顶。同时,无论在何种天气条件下,山顶的最低温度都是最高的,洼地的最低温度都是最低。低温霜冻天气下,在凌晨和夜间等温度较低时段内,始终是山顶温度最高,洼地温度最低。在山地果园中洼地整体平均温度、最低温度、低温天数、低温持续时长都是最低或最长的,尤其在霜冻天气时洼地温度低、湿度大,最容易遭受低温冻害,而山顶的晚熟柑橘相对容易越冬。     

白粉病胁迫下小麦叶片光谱响应与智能分类识别

目的 开展基于高光谱技术的白粉病胁迫下田间小麦光谱的响应研究,实现小麦白粉病感染等级的快速确定。方法 采用光纤光谱仪配合积分球和叶片夹采集大田活体小麦叶片可见-近红外光谱;通过光谱数据拟合得到的SF-SPAD (Spectrum fitting SPAD)值来反映叶绿素含量,对叶片感染白粉病进行初步判定;使用PROSPECT模型进行光谱敏感度分析确定敏感波段;结合主成分分析(Principal component analysis, PCA)降维和支持向量机(Support vector machine,SVM)建模,实现对光谱数据的二分类;根据二分类模型判断的病点百分比对小麦病虫害感染程度进行分级。结果 SF-SPAD值随自下而上的叶序的增大而逐渐上升;SF-SPAD值≤0.90的全是病点,≥1.05的全是好点。光谱敏感度分析确定了敏感波段为可见光波段440~500和540~780 nm,降低了数据维度。确定了感染等级(R)与病点百分比(%)的关系为R₁：0~30%、R₂：30%~50%、R₃：50%~70%、R₄：70%~100%。本研究所建模型适用的检测株数最少为20株。结论 结合SF-SPAD值和光谱PCA-SVM二分类建立的监测模型可以准确、快速地判定小麦白粉病感染与否及感染等级,同时可以降低采样数量、减少地面检测工作量、提高检测效率,是一项实用性强、简单、易推广的智能化监测技术。     

银杏雄株花粉特征观察与分类研究

连续2年采集分布在江苏省的89株银杏雄株的花序,通过光学显微镜、扫描电镜和透射电镜观察银杏雄株花粉,探讨银杏雄株种质资源的分类情况。结果表明:①银杏雄株花粉表面纹饰主要表现为4种类型,即球珠镶嵌型、贝甲镶嵌型、线纹镶嵌型和弧纹镶嵌型。②银杏雄株花粉壁厚度为0.861～1.076μm,外壁厚度是内壁的2～6倍。③经对花粉形状指数进行三元变量系统聚类分析,供试雄株可分为4种类型,与花粉形状指数的分类数相同,Ⅰ类4株,Ⅱ类34株,Ⅲ类47株,Ⅳ类4株,证明雄株间花粉表面纹饰和壁厚度性状指标存在显著或极显著差异。     

10种典型城市绿化树木凋落叶对4种作物种子萌发及幼苗生长的化感效应

【目的】研究城市绿化树木凋落叶对不同作物的化感效应,旨在为树木凋落叶多样化利用提供参考。【方法】以10种典型城市绿化树木凋落叶的水浸提液处理黄瓜、高粱、小麦和油菜4种受体种子,在光照培养箱内利用培养皿滤纸法进行种子发芽和幼苗生长试验,观测种子发芽率、发芽指数以及幼苗苗高、苗干质量和叶片叶绿素含量,并计算化感效应指数值,在此基础上,采用主成分分析法研究了不同树木凋落叶水浸提液对4种作物的综合化感效应。【结果】（1）10种树木凋落叶水浸提液对黄瓜种子萌发和幼苗生长均有不同程度的化感效应,其中紫叶李凋落叶水浸提液可使黄瓜种子发芽率和发芽指数均增加,紫叶李、栾树、七叶树和构树凋落叶水浸提液均可促进黄瓜幼苗苗高和叶绿素含量增加,樱花、青桐和海棠凋落叶水浸提液均可促进黄瓜幼苗苗干质量增加。10种树木凋落叶水浸提液对高粱种子的发芽率、苗高、叶绿素含量均有不同程度的抑制作用;10种树木中,只有海棠凋落叶水浸提液使高粱种子发芽指数和幼苗苗干质量增加。10种树木凋落叶水浸提液对小麦种子的发芽指数、苗高和苗干质量均有不同程度的抑制作用;10种树木中,只有樱花和七叶树凋落叶水浸提液增加了小麦种子发芽率和幼苗叶片叶绿素含量。10种树木中,只有海棠凋落叶水浸提液可使油菜种子发芽率、发芽指数和幼苗苗高、叶片叶绿素含量增加,樱花和紫叶李凋落叶水浸提液可使油菜幼苗苗干质量增加。（2）不同树木凋落叶水浸提液对4种作物的综合化感效应表现出很大的差异,其中樱花、海棠、七叶树凋落叶水浸提液对黄瓜、高粱、小麦和油菜4种作物均有明显综合促进作用;紫叶李凋落叶水浸提液对黄瓜、小麦和油菜3种作物均有明显综合促进作用,构树凋落叶水浸提液对黄瓜、高梁和油菜3种作物均有明显综合促进作用,栾树凋落叶水浸提液对黄瓜、高粱和小麦3种作物均有明显综合促进作用。【结论】樱花、海棠和七叶树凋落叶水浸提液对4种作物种子发芽和幼苗生长产生明显综合促进作用,可以作为开发生物有机肥最有潜力的树种。紫叶李、构树和栾树凋落叶水浸提液对3种作物产生明显综合促进作用,也可以考虑作为开发生物有机肥的备用树种。     

坡面液压喷播快速强制绿化的效益分析

该文以技术合理性为基础、生态效益为前提、经济效益为中心建立了坡面液压喷播效益分析评价体系 ,并分析计算了深圳市坡面液压喷播绿化的综合效益 .计算结果表明其综合效益十分显著 ,可以在全国大范围推广 .