Integrating multispectral reflectance and fluorescence imaging for defect detection on apples

This research investigated multispectral imaging to detect various defects on apples. An integrated approach using multispectral imaging in reflectance and fluorescence modes was used to acquire images of three varieties of apples. Eighteen images from a combination of filters ranging from the visible region through the NIR region and from three different imaging modes (reflectance, visible light induced fluorescence, and UV induced fluorescence) were acquired for each apple as a basis for pixel-level classification into normal or disorder tissue. Artificial neural network classification models were developed for two classification schemes, a two-class and a multiple-class. In the two-class scheme, pixels were categorized into normal or disordered tissue, whereas in the multiple-class scheme, pixels were categorized into normal, bitter pit, black rot, decay, soft scald, and superficial scald tissues. A 10-fold cross validation technique was used to assess the performance of the neural network models. The integrated imaging model of reflectance and fluorescence was effective on Honeycrisp variety, whereas single imaging models of reflectance or fluorescence was effective on Redcort and Red Delicious. The technique is promising for accurate recognition of different types of disorder on apple.     

高光谱遥感土壤湿度信息提取研究

精准农作管理中土壤水分、土壤养分等的空间信息分布 ,可通过高光谱遥感传感器获得。本文通过对土壤的光谱反射率与土壤的表面湿度进行分析 ,比较 5种方法在反演土壤表面湿度的能力 ,并对小汤山精准农业试验区的土壤表面湿度进行高光谱填图 ,建立了较为精细的土壤水分空间分布图 ,对高光谱遥感在精准农业中深入应用进行了有效探索。     

Effect of fermentation residue on the spectral reflectance properties of soils

Considering that the reflected electromagnetic energy from a soil sample interacts with many of its components (mineralogy, texture and chemical properties), remote sensing can be important to detect the presence of industry residues in the soil. An example of these residues is the largely used vinasse, originated from the production of ethanol by fermentation of sugarcane. Therefore, the objective of this study was to evaluate, using remote sensing the effect of this residue on the reflectance properties of two important tropical soils, a Typic Quartzipsament (TQ) and a Typic Argiudoll (TA) collected in São Paulo State (Brazil). The soil samples were treated with different doses of the residue and incubated. An Infra Red Intelligent Spectroradiometer sensor was used in laboratory. TQ presented a differentiated spectral reflectance (SR) curve in relation to TA, due to low Fe, organic matter and magnetite contents. Significant spectral differences in the reflectance intensities and absorption bands were found between both soils. The reactions of the residue with soils altered their chemical properties and increased reflectance intensity as well, according to the doses. Higher significant differences were observed in the reflectance of TQ. The proportional increase of the reflectance with doses of residue was due to the increase of calcium and potassium contents present in the product. The bands that detected residue presence in the soils were those of 760–900, 2.080–2.350, 2.350–2.500 nm for TQ, and 760–900, 1.118–1.270, 1.300–1.460, 1.550–1.750 nm for TA. Remote sensing technique as soil line was important on the detection of residue variations. The TM-Landsat data simulation presented the same behavior as in the laboratory, but less detailed. These elements contribute to the increase in reflectance not altering, however, the shape of the curves or the absorption bands. This study presents a new research trend where remote sensing can be used in agriculture as well as in environmental monitoring studies related to residues.     

付里叶变换近红外漫反射光谱分析应用基础的研究

本文讨论了NIRDRSA法,该分析是建立在漫反射光谱参数(反射吸光度或KubelkaMunk函数)的线性与加合性基础上。用数学分析和实验验证的方法研究了线性和加合性,样品的近红外反射率R与样品的化学组成存在非线性的关系。当散射系数为常数时,反射吸光度A(A=-logR)和化学组成存在近似线性关系。为了改善线性,可用反射吸光度的一次微分和二次微分光谱。因此样品中任一组份的含量可以用某一多元线性函数来计算。样品的制备技术、颗粒的大小、样品层的厚度、密度可影响散射系数,因此NIRDRSA必须保持制样条件的一致。本研究还说明付里叶变换光谱仪非常适合于NIRDRSA。     

李家岗下蜀黄土剖面的反射光谱研究

采用色度学方法,系统研究了下蜀黄土典型剖面的反射光谱特征。结合磁化率、微量元素Ｒｂ、Ｓｒ的含量和比值,讨论了色度参数的古气候意义,初步把下蜀黄土形成以来的古气候划分为３个波动旋回。下蜀黄土和黄土高原色度参数的对比,揭示了长江中下游地区更强的化学风化作用和成壤强度。     

叶片的灰尘对高光谱遥感中植被冠层反射率的影响

灰尘作为气溶胶的一部分由于沉降现象而附着于植物叶子的表面,当遥感探测器扫描植被冠层时,所得反射率数据就具有了一定的相似性。在平时我们处理卫星数据时忽略了附着于叶子表面灰尘的影响,没有把植被表面的灰尘作为影响因子考虑进去。随着探测器的发展,光谱分辨率的提高,灰尘对于某些波段的影响越来越大。由于天气变化如降雨可以使植被叶片表面灰尘减少甚至消失,引起植被反射率发生变化,于是本文通过模拟降雨前后植被叶片反射率变化,来研究灰尘的影响程度大小。具体方法为采用ASD野外光谱仪分别测量小麦、冬青等植被采摘后表层附有灰尘的叶片和模拟雨水冲洗灰尘后的叶片。通过同一片叶子两次测得的不同数据处理、比较得出以下结论：1. 附着于植被冠层的灰尘对其反射率有很大影响。2. 没有去尘处理的叶片反射曲线不是灰尘反射曲线和经除尘处理的叶片反射曲线简单的线性叠加。3. 灰尘并不会造成“红边”移动,不会发生“蓝移”和“红移”。     

基于连云港海域浒苔光谱的高光谱特征参数分析

以自然光照相同和水环境固定的条件下3种密度梯度（0.5、2.5和5.0 g/L）的浒苔藻体反射光谱为研究对象,基于反射光谱获取了红边位置、红边斜率、红边面积、黄边位置、黄边面积、蓝边位置、蓝边面积NDVI,RVI[719,680]和VI[555,680]10个单变量参数,综合浒苔藻体的不同生长阶段分析这些特征参数的演变规律。结果表明,红边位置、黄边位置和蓝边位置随着浒苔藻体生长状态的变化而发生偏移量较大;红边位置的最大值、RVI[719,680]最大值、NDVI最大值与浒苔藻体的密度呈现出较高的正相关,相关系数分别为0.992、0.967、0.945。应用高光谱单变量特征参数可较高精度地分析浒苔藻体光谱特征差异。     

Diagnosis of bacterial spot of tomato using spectral signatures

Ultraviolet, visible, and near-infrared reflectance spectroscopy was used to determine the disease severity of tomato (Lycopersicon esculentum) leaves infected with Xanthomonas perforans, the causal agent of bacterial leaf spot of tomato. Chemometric methods were used to identify significant wavelengths and create spectral-based prediction models. Significant wavelengths were identified through analysis of the B-matrix from partial least squares (PLS) regression, analysis of a correlation coefficient spectrum, and through the use of a stepwise multiple linear regression (SMLR) procedure. These analysis methods revealed several significant regions wavelengths and produced predictive models of disease severity based on absorbance spectra. The best model predicted the disease severity of the validation data set with a root mean square difference (RMSD) of 4.9% and a coefficient of determination (R²) of 0.82. The results of this initial study indicate the potential for the use of spectral technology to detect bacterial leaf spot of tomato in the field.     

Spectral measurements of the total aerial N and biomass dry weight in maize using a quadrilateral-view optic

Heterogeneous crop stands require locally adapted nitrogen fertilizer application based on rapid and precise measurements of the local crop nitrogen status. In the present study, we validated a promising technique for the latter, namely a tractor-mounted field spectrometer with an oblique quadrilateral-view measuring optic, measuring solar radiation and canopy reflectance in four directions simultaneously. Dry matter yield (kg ha⁻¹), total N content (g N g⁻¹ dry matter) and total aerial N (aboveground N-uptake) (kg N ha⁻¹) in maize were determined in 10 m² calibration areas in 60 plots differing in their N treatment and seeding density three times in each of three years under field conditions. Results show that the sensor used can reliably determine total aerial N ranging from as little as 5 kg N to 150 kg N ha⁻¹ with R²-values ≥0.81 in 2002 and 2004, and with R²-values ranging from ≥0.57 to 0.84 in 2003. Dry matter yields from as low as 0.3–4.2 t ha⁻¹ could be determined with R²-values ranging from 0.67 to 0.91 in 2002 to 2004. The capacity to ascertain DM yield spectrally was drastically reduced in the higher yield range (>6 t ha⁻¹) probably due to decreased sensitivity of the spectral signal. N-contents were generally not well determined. Taken together there is a good potential to determine reliably differences in total aerial N or DM yield from the five leaf stages unfolded to the five node stage where typically nitrogen applications are carried out.     

High-throughput phenotyping early plant vigour of winter wheat

In contrast to high-throughput genotyping which can manage a large number of plants at relatively low cost, phenotyping of many individual genotypes in field trials is still laborious and expensive. Early plant vigour, as an early selection criterion, is a trait that is visually scored due to a lack of suitable phenotyping methods for an accurate detection of this trait in large field trials. A high-throughput phenotyping technique for scoring early plant vigour would enhance the breeding process. This study was conducted to develop a method for scoring phenotypic differences in early plant vigour of 50 winter wheat (Triticum aestivum L.) cultivars in a 2-years experiment using a vehicle based multispectral active sensor and two commercially available active sensors, GreenSeeker and CropCircle. Pixel analysis of RGB images revealed to be the most feasible and superior method compared to other possible reference methods. A comparison between the two years 2011 and 2012 confirmed that early plant vigour was affected by genotypic differences. A novel spectral plant vigour index (EPVI) was found to accurately reflect the plant vigour at tillering. Different methods were applied to identify optimal combinations of wavelengths to predict early plant vigour, including multivariate modelling and prediction, contour maps for identifying all possible simple ratios and testing of combined indices. The EPVI and the relative amount of green pixels (RAGP) derived from digital images were significantly related with r² = 0.98 to each other in both years. A total of 200 plots, 12 m in length, could be measured within 75 min. The EPVI was shown to be an accurate scoring method for the high-throughput screening of large field trials. The rapidity and accuracy of this novel method may contribute to enhanced selection at early growth stages.