Hyperspectral Imaging System for Precision Weed Control in Processing Tomato

ВПЛИВ БУР’ЯНІВ НА РІВЕНЬ ВОДНОГО ЖИВЛЕННЯ ПОСІВІВ БУРЯКІВ ЦУКРОВИХ

Four field experiments were carried out from 2011 to 2014 in order to evaluate the effects of foramsulfuron, applied at the recommended (60.8 g a.i./ha) and reduced doses (1/3 and 2/3), on the efficacy against several of the most important weeds in maize. For each “year-weed” combination, dose-response curves were applied to estimate the dose of foramsulfuron required to obtain 90% and 95% weed control (ED90 and ED95). Foramsulfuron phytotoxicity on maize and crop yield were assessed. Foramsulfuron at 1/3 of the recommended dose (20.3 g a.i./ha) provided 95% efficacy against redroot pigweed (Amaranthus retroflexus L.), green foxtail (Setaria viridis (L.) Beauv.), wild mustard (Sinapis arvensis L.) and black nightshade (Solanum nigrum L.). Velvetleaf (Abutilon theophrasti Medik.), common lambsquarters (Chenopodium album L.) and barnyardgrass (Echinochloa crus-galli (L.) Beauv.) were satisfactorily controlled (95% weed efficacy) with ED95 ranged from 20 to 50 g/ha of foramsulfuron (about from 1/3 to 5/6 of the recommended dose) depending on growth stage. The recommended dose was effective against pale smartweed (Polygonum lapathifolium L.) at 2-4 true leaves (12-14 BBCH scale), but this dose did not kill plants larger than 2-4 true leaves. The ranking among weed species based on their susceptibility to foramsulfuron was: redroot pigweed = green foxtail = wild mustard = black nightshade > velvetleaf = common lambsquarters = barnyardgrass > pale smartweed. Dose of foramsulfuron can be reduced below recommended dose depending on weed species and growth stage. Foramsulfuron showed a good crop selectivity and had no negative effect on maize yield.

In order to quickly distinguish infertile eggs from fertile eggs, the hyperspectral imaging technology consisting of imaging and spectral information was used for detecting the fertile information of eggs. Before hatching eggs were incubated, a hyperspectral imaging system (wavelength between 400 to 1 000 nm) was used to acquire the images one-by-one manually. The characteristic information of ratios of length to short axis, elongation, roundness and the ratios of the yolk area to the whole area was extracted based on the images. The normalization method was used as the spectral data preprocessing, and then 155 spectral characteristic variables were extracted from 520 nm waveband through the correlation coefficient method. Principal component analysis (PCA) method was adopted to reduce the dimensions of image-spectrum fusion information; the top six principal components were extracted. Support vector machine (SVM) method was used to establish classification of fertile and infertile eggs models, which are based on image, spectrum and image-spectrum fusion information respectively. The accuracy rates of the SVM models were 84.00%, 90.00% and 93.00% respectively. The experimental results show that the model based on image-spectrum fusion information technology is superior to the single information model. Hyperspectral transmission imaging technology is effective and feasible to detect the fertile hatching eggs before incubation. Keywords: hyperspectral image, hatching eggs, information fusion, nondestructive detection DOI: 10.3965/j.ijabe.20150804.1672 Citation: Zhu Z H, Liu T, Xie D J, Wang Q H, Ma M H. Nondestructive detection of infertile hatching eggs based on spectral and imaging information. Int J Agric & Biol Eng, 2015; 8(4): 69－76.

Summary Field experiments were carried out in 2007–2008 at the Research Station in Chylice in potatoes cultivar Ditta and Irga. The aim of the study was to assess the effectiveness of herbicide Sencor 600 SC mixed with herbicide Titus 25 WG. Weed infestation in potatoes was varied depending on the course of vegetation. The number of recorded weed species ranged from 10 to 13. The dominant weed species were: Echinochloa crus-galli, Chenopodium album, Amaranthus retroflexus, Viola arvensis, Matricaria inodora and Solanum nigrum. The mixture of herbicide Sencor 600 SC + Titus 25 WG + Trend 90 EC irrespective of the application date was showed good results in controlling a wide range of weed species as well as full selectivity to potato plants. The efficacy of the applied herbicide mixture ranged in 87–100%. A lower effectiveness was observed for Fallopia convolvulus and Solanum nigrum.

Modelling is carried out for eleven major weeds in cucumber to develop estimated models for weed emergence time. Weed species were grouped according to their emergence patterns. Amaranthus retroflexus, Chenopodium album, Heliotropium europaeum, Polygonum aviculare and Solanum nigrum were early emerging, Convolvulus arvensis, Cyperus rotundus, Cynodon dactylon, Portulaca oleracea and Sorghum halepense were season long emerging Tribulus terrestris was the late emerging weed species. Different non-linear growth curves (Chapman-Richard, Weibull, logistic, Gompertz and cubic spline) fitted to the data of cumulative percent emergence for the different species and years. Cubic spline seemed the best model for many species.

Hyperspectral imaging provides complex image data with spectral information from many fluorescent species contained within the sample such as the fluorescent labels and cellular or pigment autofluorescence. To maximize the utility of this spectral imaging technique it is necessary to couple hyperspectral imaging with sophisticated multivariate analysis methods to extract meaningful relationships from the overlapped spectra. Many commonly employed multivariate analysis techniques require the identity of the emission spectra of each component to be known or pure component pixels within the image, a condition rarely met in biological samples. Multivariate curve resolution (MCR) has proven extremely useful for analyzing hyperspectral and multispectral images of biological specimens because it can operate with little or no a priori information about the emitting species, making it appropriate for interrogating samples containing autofluorescence and unanticipated contaminating fluorescence. To demonstrate the unique ability of our hyperspectral imaging system coupled with MCR analysis techniques we will analyze hyperspectral images of four-color in-situ hybridized rat brain tissue containing 455 spectral pixels from 550 - 850 nm. Even though there were only four colors imparted onto the tissue in this case, analysis revealed seven fluorescent species, including contributions from cellular autofluorescence and the tissue mounting media. Spectral image analysis will be presented along with a detailed discussion of the origin of the fluorescence and specific illustrations of the adverse effects of ignoring these additional fluorescent species in a traditional microscopy experiment and a hyperspectral imaging system.

Rooibos (Aspalathus linearis) and Honeybush (Cyclopia species) are teas indigenous to South Africa that are popularly consumed locally as well as internationally for its purported health benefits. Studies have confirmed anti-oxidant, antimutagenic and anticancer activity mainly due to the presence of polyphenols. Hyperspectral imaging (HSI) integrates conventional spectroscopy and imaging to obtain spectral and spatial information from a sample. The potential of short wave infrared (SWIR) hyperspectral imaging in combination with chemometric data analysis as a rapid quality control method for commercially important herbal teas was investigated. Images were acquired with the sisuChema short wave infrared (SWIR) hyperspectral pushbroom imaging system at a spectral range of 920 – 2514nm. Principal Component Analysis (PCA) was performed to remove background pixels and to visualize the data. Classes (i.e. Rooibos or Honeybush) were interactively assigned using the score images and plots. Partial Least Squares Discriminant Analysis (PLS-DA) classification models developed were subsequently used to accurately predict the species identity of commercially available herbal tea samples introduced as an external dataset, producing a visually interpretable result. The results showed that the labeling information is correct but that Honeybush tea is in most cases present in very low amounts. It is evident that hyperspectral imaging is an objective and non-destructive quality control method that can be successfully used to determine the botanical species included in herbal teas in addition to giving an indication of the abundance of each species in polyherbal tea mixtures.

The aim of this study was to investigate the niche mechanism and diversity of weeds in drip-irrigated and machine-harvested cotton fields in north Xinjiang, China. The dominant classes of weeds in 25 cotton fields under drip-irrigated and machine-harvested in 5 regions of north Xinjiang were investigated by seven-grade visual method, and converted to important value data, the 20 main weeds niche breadth and niche overlap were caculated on the basis of the data above. The ecological similiarity revealed by DCA sorting and minimum spanning tree of graph theory cluster analysis is drawed on the basis of the niche overlap value. The results show that Convolvulus arvensis L., Chenopodium album L., Amaranthus retroflexus L., Solanum nigrum L., Phragmites australis (Cav.) Trin. ex Steud., Setria viridis (L.) Beauv., Abutilon theophrasti Medicus., Hibiscus trionum L., Echinochloa crusgalli (L.) Beauv., nine species of weeds, which are the dominant species (malignant weeds) in drip-irrigated and machine-harvested cotton fields in North Xinjiang, have wide niche. The niche overlap values of S. nigrum L. and C. album L., A. theophrasti Medicus. and A. retroflexus L., H. trionum L. and E. crusgall (L.) Beauv., A. retroflexus L. and E. crusgalli (L.) Beauv. are higher. The minimal spanning tree method based on niche overlap value to reflect similar degree of the ecological needs of the weeds, 20 main weeds will be divided into 4 groups. DCA ordination of 20 main weeds comprehensive ecological needs of 25 sampling sites: the vicious weeds all gathered at the central sorting chart, the distinction is obvious with the general weed and the corresponding of DCA ordination chart with minimal spanning tree is better. The minimal spanning tree by its focus on the results of which show that weeds are the most similar to the ecological requirements, but not be used for the no adjacent species, and no clear that the ecological relationship between them, the DCA sorting can reflect the ecology similar relations between all weeds wholely, though this method will lose a small amount of ecological information through the data conversion. Therefore, the two methods will be combined, complementary advantages, the superiority is obvious. Along with drip irrigation age years increase, S. nigrum L., C. arvensis L., C. album L. and so on, between dominant value of nine species of malignant weeds and the drip irrigation age years has the remarkable regression relations.

VTT Technical Research Centre of Finland has developed a Fabry-Perot Interferometer (FPI) based hyperspectral imager compatible with light weight UAV (Unmanned Aerial Vehicle) platforms (SPIE Proc. 7474¹, 8186B²). The FPI based hyperspectral imager was used in a UAV imaging campaign for forest and agriculture tests during the summer 2011 (SPIE Proc. 8174³). During these tests high spatial resolution Color-Infrared (CIR) images and hyperspectral images were recorded on separate flights. The spectral bands of the CIR camera were 500 - 580 nm for the green band, 580 - 700 nm for the red band and 700 - 1000 nm for the near infrared band. For the summer 2012 flight campaign a new hyperspectral imager is currently being developed. A custom made CIR camera will also be used. The system which includes both the high spatial resolution Color-Infrared camera and a light weight hyperspectral imager can provide all necessary data with just one UAV flight over the target area. The new UAV imaging system contains a 4 Megapixel CIR camera which is used for the generation of the digital surface models and CIR mosaics. The hyperspectral data can be recorded in the wavelength range 500 - 900 nm at a resolution of 10 - 30 nm at FWHM. The resolution can be selected from approximate values of 10, 15, 20 or 30 nm at FWHM.

Optical spectroscopy can be used to distinguish between healthy and diseased tissue. In this study, the design and testing of a single-pixel hyperspectral imaging (HSI) system that uses autofluorescence emission from collagen (400nm) and nicotinamide adenine dinucleotide phosphate (475nm) along with differences in the optical reflectance spectra to differentiate between healthy and thermally damaged tissue is discussed. The changes in protein autofluorescence and reflectance due to thermal damage are studied in ex vivo porcine tissue models. Thermal lesions were created in porcine skin (n=12) and liver (n=15) samples using an IR laser. The damaged regions were clearly visible in the hyperspectral images. Sizes of the thermally damaged regions as measured via HSI are compared to sizes of these regions as measured in white-light images and via physical measurement. Good agreement between the sizes measured in the hyperspectral images, white-light imaging, and physical measurements were found. The HSI system can differentiate between healthy and damaged tissue. Possible applications of this imaging system include determination of tumor margins during surgery/biopsy and cancer diagnosis and staging.

Banana is a significant economic source in Türkiye. Root-knot nematodes, Meloidogyne spp. Göldi, 1897 (Tylenchida: Heteroderidae) are the important pests in banana fields. This study was conducted from 2021 to 2022 to elucidate the relationship between root-knot nematodes and weed species in bananas in the Mediterranean Region. 2% of the banana production area in Adana, Antalya, Hatay and Mersin were surveyed regularly for this purpose. 1m2 frames were placed within a 2m radius around banana plants in the sampled areas. The host of root-knot nematodes with weed species identified within the frames was examined. Survey results indicated that Amaranthus retroflexus L. (46.34%), Portulaca oleracea L. (40.63%), and Solanum nigrum L. (37.84%) were the weed species most infected with root-knot nematodes. Furthermore, molecular analyses revealed that Abutilon theophrasti Medik., Amaranthus spp., Cucumis melo var. agrestis Naudin., Erodium cicutarium (L.) L'Hér. ex Aiton, Kickxia commutata (Bernh. ex Rchb.) Fritsch, Malva spp., Mercurialis annua L., P. oleracea, S. nigrum, and Sonchus oleraceus L. were suitable hosts for root-knot nematodes. This study is an important step in understanding the interaction between root-knot nematodes and weeds in banana. The presence of weed species in agricultural fields should be considered as they may support nematode populations and pose a threat to subsequent crops. Therefore, the implementation of weed control strategies could help producers to control nematode populations.

In South Africa, indigenous herbal teas are enjoyed due to their distinct taste and aroma. The acclaimed health benefits of herbal teas include the management of chronic diseases such as hypertension and diabetes. Quality control of herbal teas has become important due to the availability of different brands of varying quality and the production of tea blends. The potential of hyperspectral imaging as a rapid quality control method for herbal tea blends from rooibos (Aspalathus linearis), honeybush (Cyclopia intermedia), buchu (Agathosma Betulina) and cancerbush (Sutherlandia frutescens) was investigated. Hyperspectral images of raw materials and intact tea bags were acquired using a sisuChema shortwave infrared (SWIR) hyperspectral pushbroom imaging system (920–2514 nm). Principal component analysis (PCA) plots showed clear discrimination between raw materials. Partial least squares discriminant analysis (PLS-DA) models correctly predicted the raw material constituents of each blend and accurately determined the relative proportions. The results were corroborated independently using ultra-high performance liquid chromatography coupled to mass spectrometry (UHPLC-MS). This study demonstrated the application of hyperspectral imaging coupled with chemometric modelling as a reliable, rapid and non-destructive quality control method for authenticating herbal tea blends and to determine relative proportions in a tea bag.

The primary application of hyperspectral imaging is to classify/quantify objects/materials in the scene based on their spectral signatures. The spectral features that are useful can sometimes fall outside the spectral range of a single hyperspectral imager which is usually limited by the spectral response range of the sensor material of the focal plane array within the imager. For these wide spectrum applications, some users are combining data from two (or more) hyperspectral imaging systems. Aside from the optical alignment, size and synchronization issues involved in such a setup, the process of pixel co-registration, i.e. geometrically transforming data from the 2 hyperspectral imaging systems to overlay one another is tedious and complex. Headwall Photonics has integrated two of their off-the-shelf highly optimized hyperspectral imagers (Vis-NIR and SWIR) in an optically co-boresighted configuration together with a high performance data processor to produce a compact system which is easy to use and outputs wide spectrum pixel co-registered hyperspectral data. The process of pixel co-registration in this system is computationally very cheap enabling real-time wide-spectrum hyperspectral imaging applications. This paper presents actual imaging and performance data from these systems showing excellent pixel co-registration, sensitivity and spectral resolution.

A two‐year study was conducted in 2002 and 2003 at the New Mexico State University Agricultural Science Center at Farmington, NM to evaluate postemergence herbicides for control of redroot and prostrate pigweed (Amaranthus retroflexus L. and Amaranthusblitoides S. Wats.), black nightshade (Solanum nigrum L.), common lambsquarters (Chenopodium album L.), and Russian thistle (Salsola iberica Sennen & Pau) and their effect on field corn (Zea mays) injury and yield. Herbicide treatments gave over 95% control of redroot and prostrate pigweed and common lambsquarters through August, in both years. Russian thistle control was 70% or less with DPX 79406, foramsulfuron, and nicosulfuron plus rimsulfuron when applied at 0.0115 plus 0.0115, 0.033, and 0.023 plus 0.012 lb a.i./acre, or in combination with mesotrione at 0.06 lb a.i./acre. Black nightshade control with foramsulfuron applied at 0.033 lb a.i./acre was 30 to 41% better than DPX 79406 or nicosulfuron plus rimsulfuron applied at 0.0115 plus 0.0115 and 0.023 plus 0.012 lb a.i./acre. This research indicates that when nicosulfuron plus rimsulfuron, DPX 79406, and foramsulfuron were applied in combination with diflufenzopyr plus dicamba, dicamba plus atrazine, mesotrione, or dicamba, broadleaf weed control increased significantly without field corn injury or yield reductions.

Hyperspectral (HS) imaging systems are useful in a diverse range of applications that involve detection and classification tasks. However, the low spatial resolution of hyperspectral images may limit the performance of the involved tasks in such applications. In the last years, fusing the information of a HS image with high spatial resolution multispectral (MS) or panchromatic (PAN) images has been widely studied to enhance the spatial resolution. Image fusion has been formulated as an inverse problem whose solution is a HS image which assumed to be sparse in an analytic or learned dictionary. This work proposes a non-local centralized sparse representation model on a set of learned dictionaries in order to regularize the conventional fusion problem. The dictionaries are learned from the observed data taking advantage of the high spectral correlation within the HS image and the non-local self-similarity over the spatial domain of the MS image. Then, conditionally on these dictionaries, the fusion problem is solved by an alternating iterative numerical algorithm. Experimental results with real data show that the proposed method outperforms the state-of-the-art methods under different quantitative assessments.