Detection of Ochyromera ligustri (Coleoptera: Curculionidae: Curculioninae) in Ligustrum spp. (Oleaceae) Using Newly Developed PCR Primers

Ligustrum spp. (Oleaceae) have become invasive species in the US and negatively affect native plant diversity and richness in forests. Ochyromera ligustri (Coleoptera: Curculionidae) is considered a potential biological control agent in the US because adults feed on the foliage and larvae are seed-feeders of Ligustrum spp. To discover the relationships between O. ligustri and Ligustrum spp., fruit dissections or rearing and field observations are required. In the current research project, novel PCR primers were developed to rapidly detect the DNA of O. ligustri in molecular analyses without rearing and observation. The developed PCR primers worked even with 0.01 ng of DNA and did not amplify the DNA of the other five curculionid species tested. When the novel primers were tested with three Ligustrum spp. species common in the southeastern US, the DNA of O. ligustri was detected from all three species. We expect that the novel primers will be utilized to find out the presence and impact of O. ligustri on Ligustrum spp rapidly and accurately.

Frugivorous birds disperse seeds of Ligustrum lucidum, seed-feeding weevils, and parasitic wasps of weevils via endozoochory

Seed dispersal by frugivorous birds is a famous plant-animal interaction. However, we demonstrated that frugivorous birds can disperse seeds of Ligustrum lucidum, and its seed parasite weevils and the parasitic wasps from the weevils in this study. The cryptic tetrad of Ligustrum-disperser-weevil-wasp may be an overlooked phenomenon in seed dispersal syndrome.

Convolutional Neural Networks Using Enhanced Radiographs for Real-Time Detection of Sitophilus zeamais in Maize Grain

The application of artificial intelligence (AI) such as deep learning in the quality control of grains has the potential to assist analysts in decision making and improving procedures. Advanced technologies based on X-ray imaging provide markedly easier ways to control insect infestation of stored products, regardless of whether the quality features are visible on the surface of the grains. Here, we applied contrast enhancement algorithms based on peripheral equalization and calcification emphasis on X-ray images to improve the detection of Sitophilus zeamais in maize grains. In addition, we proposed an approach based on convolutional neural networks (CNNs) to identity non-infested and infested classes using three different architectures; (i) Inception-ResNet-v2, (ii) Xception and (iii) MobileNetV2. In general, the prediction models developed based on the MobileNetV2 and Xception architectures achieved higher accuracy (≥0.88) in identifying non-infested grains and grains infested by maize weevil, with a correct classification from 0.78 to 1.00 for validation and test sets. Hence, the proposed approach using enhanced radiographs has the potential to provide precise control of Sitophilus zeamais for safe human consumption of maize grains. The proposed method can automatically recognize food contaminated with hidden storage pests without manual features, which makes it more reliable for grain inspection.

X-ray computed tomography for quality inspection of agricultural products: A review

The quality of agricultural products relates to the internal structure, which has long been a matter of interest in agricultural scientists. However, inspection methods of the opaque nature of internal information on agricultural products are usually destructive and require sample separation or preparation. X-ray computed tomography (X-ray CT) technology is one of the important nondestructive testing (NDT) technologies without sample separation and preparation. In this study, X-ray CT technology is used to obtain two-dimensional slice images and three-dimensional tomographic images of samples. The purpose of the review was to provide an overview of the working principle of X-ray CT technology, image processing, and analysis. This review aims to focus on the development of the agricultural products (e.g., wheat, maize, rice, apple, beef) and its applications (e.g., internal quality evaluation, microstructure observation, mechanical property measurement, and others) using CT scanner. This paper covers the aspects regarding the advantages and disadvantages of NDT technology, especially the unique advantages and limitations of X-ray CT technology on the quality inspection of agricultural products. Future prospects of X-ray CT technology are also put forward to become indispensable to the quality evaluation and product development on agricultural products.

Efficient detection of internal infestation in wheat based on biophotonics

In the process of grain storage, there are many losses of grain quantity and quality for the sake of insects. As a result, it is necessary to find a rapid and economical method for detecting insects in the grain. The paper innovatively proposes a model of detecting internal infestation in wheat by combining pattern recognition and BioPhoton Analytical Technology (BPAT). In this model, the spontaneous ultraweak photons emitted from normal and insect-contaminated wheat are firstly measured respectively. Then, position, distribution and morphological characteristics can be extracted from the measuring data to construct wheat feature vector. Backpropagation (BP) neural network based on genetic algorithm is employed to take decision on whether wheat kernel has contaminated by insects. The experimental results show that the proposed model can differentiate the normal wheat from the insect-contaminated one at an average accuracy of 95%. The model can also offer a novel thought for detecting internal infestation in the wheat.

X-ray imaging methods for internal quality evaluation of agricultural produce

A number of non-destructive methods for internal quality evaluation have been studied by different researchers over the past eight decades. X-ray and computed tomography imaging techniques are few of them which are gaining popularity now days in various fields of agriculture and food quality evaluation. These techniques, so far predominantly used in medical applications, have also been explored for internal quality inspection of various agricultural products non-destructively, when quality features are not visible on the surface of the products. Though, safety of operators and time required for tests are of concern, the non-destructive nature of these techniques has great potential for wide applications on agricultural produce. This paper presents insight of X-ray based non-destructive techniques such as X-ray imaging and Computed Tomography (CT). The concepts, properties, equipment and their parameters, systems and applications associated with the use of X-rays and CT for agricultural produce have been elaborated.

Molecular techniques for the detection of granary weevil (Sitophilus granarius L.) in wheat and flour

The granary weevil (Sitophilus granarius L.) is a stored grain pest that causes major economic losses. It reduces the quantity and quality of the grain by its feeding and excretion. Sequences of S. granarius mitochondrial cytochrome oxidase subunits genes mtCOI and mtCOII were analysed and compared with mtCOI/II sequences available in GenBank. The analysed genes displayed a high level of homology between corresponding subunits. Attempts were undertaken to develop detection methods for contamination by S. granarius in wheat and wheat flour based on the molecular biology techniques: standard and real-time polymerase chain reaction (PCR) with a TaqMan molecular probe. (TaqMan probes are dual-labelled hydrolysis probes) Specific primers designed based on available sequences for mtCOI and mtCOII genes were applied and optimal reaction conditions established. The specificity of both methods was studied by using a species closely related to S. granarius: S. oryzae and S. zeamais. It is shown that the sensitivity threshold was very high - we were able to detect the equivalent of one beetle per 100 kg of flour when the real-time PCR with TaqMan probe method was applied to model samples. The primer sets used turned out to be species specific, and the technique was rapid, reliable and very sensitive.

Non-destructive diffraction enhanced imaging of seeds

Techniques that make possible the non-destructive continuous observation of plant anatomy and developmental processes provide novel insights into these phenomena. Non-destructive imaging of seeds was demonstrated using the synchrotron-based X-ray imaging technique, diffraction enhanced imaging (DEI). The seed images obtained had good contrast and definition, allowing anatomical structures and physiological events to be observed. Structures such as hypocotyl-root axes, cotyledons, seed coats, air cavities, and embryo-less Brassica napus L. seeds were readily observed using DEI. Embryo axes, scutella, pericarp furrows, coleoptiles, and roots were observable over a time-course in individual germinating Triticum aestivum L. caryopses. Novel anatomical and physiological observations were also made that would have been difficult to make continuously using other techniques. The physical principles behind DEI make it a unique imaging technique. Contrast in DEI is the result of X-ray refraction at the density differences occurring at tissue boundaries, scatter caused by regions containing ordered molecules such as cellulose fibres, and attenuation. Sectioning of samples and the infusion of stains or other contrast agents are not necessary. Furthermore, as high-energy X-rays are used (30-40 keV), little X-ray absorption occurs, resulting in low levels of radiation damage. Consequently, studies of developmental processes may be performed on individuals. Individual germinating B. napus and T. aestivum seeds were imaged at several time points without incurring any apparent radiation damage. DEI offers a unique way of examining plant anatomy, development, and physiology, and provides images that are complementary to those obtained through other techniques.