Effect of the degree of fusariosis on the physical characteristics of individual wheat kernels

This work aims to determine dependencies of single‐kernel (SK) physical traits on the kernel degree of fusariosis. The measurements were taken on samples of grain of six wheat varieties cultivated during 1–3 years. For SK mass, volume and width this dependence resulted in lowered (by at least ten to more than 25% for mass and volume, and ca. 5 to more than 15% for width) values in Fusarium culmorum infested grain as compared with the non‐inoculated control. In addition, moderately infested kernels tended to be of higher mass and size than kernels with no symptoms of infestation. An unexpected effect was a lack of dependence of SK density on the degree of infestation. Moisture content was lower for infested kernels by 6–8%, hardness tended to increase a little for moderate infestation, while it noticeable decreased for the heaviest infestation.     

基于软X射线与低场核磁检测小麦隐蔽性害虫玉米象

针对小麦内部隐蔽性害虫玉米象(Sitophilus zeamais)难以检出的问题,本文将高清软X射线与低场核磁两种检测技术相结合,通过高清软X射线拍摄的图片,观察玉米象在小麦内部的整个生长周期,提取图片纹理特征,用线性判别分析(linear discriminant analysis,LDA)与二次判别分析(quadratic discriminant analysis,QDA)算法进行分类判别,并对被不同虫态玉米象感染的小麦进行低场核磁检测。研究结果表明:在12%水分含量小麦中,玉米象的生长周期大约为36 d,LDA与QDA模型对未感染小麦与不同感染阶段小麦进行单独分类判别时,准确率都达到了95%以上,对卵期以及幼虫具有较高的分类准确率。根据小麦被玉米象感染后特征峰值比例P2b与P22的变化,可以用来作为小麦是否受玉米象感染定性判断的依据。     

Detection of internal wheat seed infestation by Rhyzopertha dominica using X-ray imaging

Standardization for grain grades has been established in most countries to maintain the quality of a crop until it reaches consumers. Different methods have been investigated for their potential to detect insect infestations in grain destined for domestic and export markets. The potential of detecting infestations caused by Rhyzopertha dominica in wheat kernels using a real-time soft X-ray method was determined in this study. Artificially infested wheat kernels were incubated at 30°C and 70% relative humidity and X-rayed sequentially for larval, pupal, and adult stages of R. dominica. Algorithms were used to extract histogram features, textural features, and histogram and shape moments from the X-ray images of wheat kernels. A backpropagation neural network (BPNN) and statistical classifiers were used to identify uninfested and infested kernels using the 57 extracted features. The BPNN correctly identified all uninfested and infested kernels and more than 99% of kernels infested by R. dominica larvae. The classification accuracies determined by the BPNN were higher using all 57 features than when using the histogram and textural features separately. The BPNN performed better than the parametric and non-parametric classifiers in the identification of uninfested and infested kernels by different stages of R. dominica.     

Influence of the degree of fusariosis on technological traits of wheat grain

The paper aims to enlarge the current knowledge about the dependence of technological traits of wheat grain on its degree of infestation (DI) with fusariosis. Samples of grain of four wheat cultivars were obtained from naturally grown crops (control) and from crops inoculated with Fusarium culmorum from which three degrees of kernel infestation were selected. Samples were determined for thousand kernels weight (TKW), total protein, starch and wet gluten (WG) contents, Hagberg falling number (HFN) and sedimentation value (SV). Content of protein and wet gluten showed higher values for moderately infested kernels (up to 15 and 25%, respectively, when compared to control grain) than for kernels lightly or heavily infested. All the remaining traits had values lower than that for control grain and showed a decrease with increasing DI. Decrease for the heaviest infestation was on average: 8, 29, 31 and 34% for starch, TKW, HFN and SV, respectively.     

Detection of granary weevil Sitophilus granarius (L.) eggs and internal stages in wheat grain using soft X-ray and image analysis

In order to prevent grain mass and quality losses, rapid methods for early detection of insect infestation of cereal grain during trade and storage are urgently needed. Amongst many options, the soft X-ray method using roentgenograms is one of the most frequently applied. It has been shown that when some corrections for working parameters of the equipment used are made and some modification of the digital image analysis introduced, the soft X-ray method is suitable for accurate detection of granary weevil eggs laid in wheat kernels if at least 5 days after oviposition have elapsed.     

Susceptibility of Ethiopian wheat varieties to granary weevil and rice weevil infestation at optimal and sub-optimal temperatures

Integrating varietal resistance with temperature manipulation during storage may provide a better option for protection of stored grains and may decrease reliance on the use of synthetic chemicals. The current study was conducted to determine the susceptibility of different varieties of wheat seed to the infestation by the granary weevil, Sitophilus granarius (L.), and rice weevil, Sitophilus oryzae (L.), at optimal (30 °C) and sub-optimal (19 °C) temperatures. Kernels of six wheat varieties namely, Danda'a, Digalu, ET-13-A2, Kakaba, Millennium, and Pavon-76 were examined over a period of 90 d. Significant interactions were detected between wheat varieties and storage temperature for progeny emergence, percentage of insect damaged kernels, grain weight loss, and amount of powder produced per gram of wheat. Kernels of Danda'a, infested with S. oryzae at 30 °C exhibited significantly lower mean progeny counts (13.3 live insects), lower percentage of grain weight loss (4.2%) and insect-damaged kernels (6.4%), and powder production (1.5 mg/g). Kernel weight and hardness index were negatively associated with percentage of insect damaged kernels and grain weight loss. Kernel diameter was positively associated with both of percentage of insect damaged kernels and grain weight loss. Wheat varieties with high Zeleny sedimentation values had lower percentage of insect-damaged kernels and grain weight loss. These results indicated that kernel weight, hardness index, and protein content are predominant factors contributing to wheat resistance against S. granarius and S. oryzae. The varieties Millennium and Danda'a can be considered with other integrated pest management approaches to reduce stored grain losses of wheat in Ethiopia.     

The influence of Rhyzopertha dominica (F.) on the technological quality of cereal grains treated with diatomaceous earth

Laboratory bioassays (temperature 26 ± 1 °C and 60 ± 5% r. h.) were performed to evaluate the insecticidal effect of three different diatomaceous earths (DE) against Rhyzopertha dominica (F.) in wheat, triticale and rye. In order to achieve this, the amount of damaged kernels, amount of debris, wet gluten content, gluten index and rheological properties were assessed in infested samples, infested samples treated with DE Protect-It and two DEs originating from Serbia (S-1 and S-2) and were compared to control (uninfested) samples using Chopin Mixolab. The most susceptible to beetle infestation were rye sample and wheat variety Planeta. The lowest weight of damaged grain was found after applying DE Protect-It to all grain types. The amount of damaged kernels, the amount of debris and loss of mass were the highestin sample treated with DE S-2. While infestation resulted in increase in the amount of damaged kernels and debris and decrease in wet gluten content, and provoked weakening of gluten network structure as well as starch damage, an addition of DE, especially Protect-It, resulted in grain samples of similar technological quality to control (uninfested) sample. The susceptibility of different cereals used in breadmaking to infestation by R. dominica, as well as their response to the insecticidal effect of diatomaceous earth largely varied. Both cereal type and quality, as measured by wet gluten content and gluten index, influenced grain response to infestation. Insecticidal effect of diatomaceous earth, especially DE S-1and DE S-2, was the least effective in terms of triticale. These findings suggest that the application of DE in cereals storage management might largely be affected with grain type as well as grain composition and technological quality.     

基于差分图像边界距离的粮粒孔洞自动检测

粮粒孔洞的自动检测是近红外高光谱图像技术检测粮粒内部害虫中的一个关键问题。提出基于差分图像边界距离的粮粒孔洞自动检测方法,该方法通过求取粮粒(内部)轮廓与阈值分割后二值图像的差分,若差分图像中的目标与粮粒边界的最远距离大于某个阈值时,则该目标应判别为边界(内部)孔洞。用米象的幼虫、蛹和成虫3个侵染阶段粮粒的900帧近红外图像进行训练,用450帧近红外图像进行检验,结果表明该方法不仅可以判断粮粒是否存在孔洞,还能检测出孔洞的数量及形态,其中边界孔洞和内部孔洞的识别率分别为97.33%和95.56%,证实了基于差分图像边界距离的粮粒孔洞检测方法是可行的。     

Comparison of seven methods for stored cereal losses to insects for their application in rural conditions

There are several methods for assessing harvest losses during storage with varying degrees of accuracy, reliability and practical application, however, field conditions may limit their use among subsistence farmers and traders in developing nations. We compared seven standard grain loss methods during natural and controlled infestation by Sitophilus oryzae L. in wheat and barley to select the best procedures for use in farm storage. Methods tested were: 1) visual inspection of infested lots, 2) uncorrected weight loss, 3) modified standard volume/weight ratio, 4) grain count and weight, 5) percentage of damaged grains converted to weight loss, 6) one thousand grain mass, and 7) one thousand grain mass including dust. Previously disinfested cereal lots (wheat, barley, 500 g fresh w) were exposed to 20 newly emerged adult S. oryzae for 90 d at 28 °C and 70% r.h. Naturally- infested wheat lots were also monitored under the same conditions. Before and after this period, fresh and dry weight, number, moisture content of uninfested and damaged grains, weight of 1 L of seeds and dust produced by insect activity, fresh and dry weight of 1000 kernels, and number of adult weevils was determined and applied to appropriate equations of methods (1), (2), (3), (4), (5), (6) and (7). Grain mass loss estimations varied by wide margins (9.3 ± 1.3% to 25.8 ± 2.3% in barley, 2.2 ± 0.7% to 12.5 ± 2.5% in wheat) depending on method employed, suggesting the need for careful selection of the most appropriate procedure under field conditions and farmer/trader interests. While accurate procedures such as method 7 provided dependable results, methods 3 and 5 appear most practical for wheat and barley.     

An automatic algorithm for detection of infestations in X-ray images of agricultural products

An automatic recognition algorithm was developed and tested for detection of certain defects or contaminants in X-ray images of agricultural commodities. Testing of the algorithm on wheat kernels infested with larvae of the granary weevil, Sitophilus granarius (L.) yielded comparable results to those obtained by human subjects evaluating digitized X-ray film images (14.4% overall error vs. 15.6% for human subjects). Further tests on X-ray images of olives infested with the Olive Fly, Bactrocera oleae (L.), yielded a total error of 12% for large infestations and over 50% for the smallest infestations with false positive results below 10%. Testing of alternate training strategies showed that for this type of algorithm, which uses a form of discriminant analysis with a generally “fuzzy” decision boundary, best results are obtained when training with samples that map far away from the boundary, then applying the derived decision function to all samples to be classified.     

Detection of External and Internal Insect Infestation in Wheat by Near-Infrared Reflectance Spectroscopy

Near-infrared spectroscopy (NIR) in the reflectance mode was investigated for the rapid, automatic and non-destructive detection of insect stored-grain pests external or internal to wheat kernels. Convincing calibration performance was obtained for external adult Oryzaephilus surinamensis (L) (saw-toothed grain beetle) in unmilled samples including varieties Beaver (soft wheat) and Mercia (hard wheat) at two moisture contents. With this large substrate variability, the method could differentiate between uninfested samples and samples with approximately 270 insects kg⁻¹ or more. Milling made no improvement. Large spectral differences were observed between uninfested kernels and kernels infested internally with Sitophilus granarius (L) (grain weevil) larvae or pupae, arising from both a changed chemical composition and physical structure. Single uninfested and infested kernels were discriminated by their second derivative (d²) spectra. For both external and internal infestation there was substantial evidence that insect protein and/or chitin and moisture were being detected. NIR should be useful as a rapid method of detection.     

Thermal imaging to detect infestation by Cryptolestes ferrugineus inside wheat kernels

Canada's zero tolerance for live insects in grain received from farmers, and shipped to domestic and export buyers, has necessitated the development of an accurate insect detection method. An infrared thermal imaging system was developed to detect infestation by six developmental stages (four larval instars, pupae and adults) of Cryptolestes ferrugineus under the seed coat on the germ of the wheat kernels. The artificially infested wheat kernels were removed from the incubation room (30 °C), refrigerated (5 °C) for 60 s, maintained at ambient conditions for 20 s, and imaged using a thermal camera to identify each developmental stage (n=283). The means of the highest 5% and 10% of all temperature values on the surface of the grain were significantly higher (=0.05) for grains having young larvae inside and lower for grains having pupae inside. Temperature distribution on the surface of the infested kernels with different stages of C. ferrugineus was highly correlated with the respiration rate of each developmental stage (r=0.83–0.91). The overall classification accuracy for a quadratic function was 83.5% and 77.7% for infested and sound kernels, respectively, and for a linear function, it was 77.6% and 83.0% for infested and sound kernels, respectively, in pairwise discriminations. Thermal imaging has the potential to identify whether the grain is infested or not, but is less effective in identifying which developmental stage is present.     

A comparison of screening methods for insect contamination in wheat

In collaboration with the United States Department of Agriculture and a number of major milling companies, the “Insect-Detect” immunoassay for analyzing insect contamination in grains has been compared with three more traditional methods, X-ray analysis, cracking and flotation, and the insect fragment test (IFT). Testing was carried out in blind fashion using clean wheat samples that were spiked with differing numbers of grain kernels infested with late instar larvae of the granary weevil (Sitophilus granarius (L.)). Three different laboratories analyzed the samples for each of the four methods. The collaborative trials showed that the insect immunoassay clearly provided the most accurate measurement of actual insect infestation, followed by X-ray analysis. While both cracking and flotation and IFT procedures provided a general measure of contamination, they showed much greater variability.     

Detection of internal insects in wheat using a conductive roller mill and estimation of insect fragments in the resulting flour

A laboratory roller mill that monitors the conductance of kernels that pass through it was tested for its ability to estimate the number of insect fragments in flour after milling. This system can test a kilogram of whole wheat in approximately 1 min and requires little sample preparation. Hard red winter wheat samples were infested with lesser grain borers and stored at 24 °C. Infestations ranged from 12 to over 2000 infested kernels per 1 kg or per 30,000 kernels. After crushing of samples in the conductance instrument, the samples were milled into flour and sub-samples were sent to two laboratories for insect fragment analysis. The insect fragments were proportional to the number of detection incidences obtained using the conductance instrument and X-ray images. Insect fragment counts per 50 g of flour ranged from 0 to over 5000. For insect fragment counts from 0 to 250, correlations between fragment counts and conductance mill detection were 0.75 and 0.80 from two separate cereal chemistry laboratories. Therefore, the conductance mill is potentially a good method for testing incoming grain for live internally infesting insects; it is able to test 1 kg of grain in about 1 min and can detect low levels (as low as three insects) of live internal infestations in a 1- or 2-kg sample.     

基于图像处理和神经网络的小麦不完善粒识别方法研究

为了实现图像处理技术对小麦不完善粒的准确快速识别,研究了一种基于小麦不完善粒图像特征和BP神经网络的不完善粒识别方法。采集小麦不完善粒图像,对图像进行中值滤波、形态学运算、图像分割等处理后,针对每个小麦籽粒,提取其形态、颜色和纹理共3大类54个特征参数,采用主成分分析法提取8个主成分得分向量作为模式识别的输入,建立BP神经网络模型,实现对小麦不完善粒的检测识别。结果表明,该模型对完善粒、破损粒、病斑粒、生芽粒和虫蚀粒的判别正确率分别为93%、98%、100%、90%和85%,平均判别正确率达到93%,可有效对小麦不完善粒进行检测识别。     

Application of Image Texture Analysis for Evaluation of X-Ray Images of Fungal-Infected Maize Kernels

The feasibility of image texture analysis to evaluate X-ray images of fungal-infected maize kernels was investigated. X-ray images of maize kernels infected with Fusarium verticillioides and control kernels were acquired using high-resolution X-ray micro-computed tomography. After image acquisition and pre-processing, several algorithms were developed to extract image textural features from selected two-dimensional (2D) images of the kernels. Four first-order statistics (mean, standard deviation, kurtosis and skewness) and four grey level co-occurrence matrix (GLCM) features (correlation, energy, homogeneity and contrast) were extracted from the side, front and top views of each kernel and used as inputs for principal component analysis (PCA). The first-order statistical image features gave a better separation of the control from infected kernels on day 8 post-inoculation. Classification models were developed using partial least squares discriminant analysis (PLS-DA), and accuracies of 67 and 73% were achieved using first-order statistical features and GLCM extracted features, respectively. This work provides information on the possible application of image texture as method for analysing X-ray images.     

Effects of insect-infested kernels on bulk flow properties of wheat

Insect damage to kernels during storage affects the processing quality of wheat and as well as bulk wheat properties, which in turn causes hopper flow problems such as funnel flow, ratholing, arching, or flushing. This study focused on kernel damage by Rhyzopertha Dominica F. (lesser grain borer), one of the most commonly found insects in wheat, and resulting changes in physical properties, such as bulk density, tapped density, true density, and angle of repose, and in flow properties, such as basic flowability energy, stability, aeration, compressibility, and permeability. Bulk and tapped densities of sound hard red winter wheat kernels and infested wheat kernels were about 720 kg/m³ and 775 kg/m³, respectively. Compressibility index (CI), Hausner ratio (HR), and angle of repose of infested wheat kernels were higher than for sound hard red winter wheat kernels, indicating decreased flowability. Grain dust and insect-infested kernels could form localized compacted areas within the grain bins, resulting in uneven flow during discharge. Results from this study indicate that the presence of insect-infested kernels could lead to arching and bridge formation in grain bins, thus affecting the flow characteristics of bulk wheat.     

Extent of damage of unhusked stored rice by Sitotroga cerealella Oliv. (Lepidoptera,gelechiidae) in Bangladesh

Sitotroga cerealella Oliv. causes a considerable amount of damage to unhusked stored rice in Bangladesh, but the details of the extent of such loss are not known. The studies conducted here showed that from 3 to 12 per cent of the rice kernels are attacked over a period of 6–9 months. This causes a total weight loss varying from 4·2 to 11·9 per cent with an average of 8·1 per cent. Only about 56·3 per cent of each infested kernel is needed for complete larval development. The extent of the pest attack was increased by high moisture content. The proportion of kernels of the sundried rice attacked varied from 2 to 4 per cent, whereas it rose to about 45·5 per cent of kernels soaked in water for 18 hr before exposure to infestation.     

Radiographic studies of Sitophilus zeamais Mots. in wheat kernels

Ninety-nine wheat kernels infested by Sitophilus zeamais Mots., were radiographed daily, to study development from egg to adult and behavior of the insects within the kernels. Enlarged photographic prints were prepared from these radiographs to facilitate interpretation.