On the Structure and Molt Controlling Function of the Y-Organ in the Prawn Penaeus indicus

The morphological and histological structure of the Y-organ of Penaeus indicus is described. The gland 1–2 × 0.3 mm (LXW) is located in between the mandibular and posterior dorsoventral muscle at the junction of prebranchial and branchial chambers. Histochemical tests were performed to determine the chemical nature of the Y-organ cells. Significant changes in the size and tinctorial affinity of the Y-organ cells were observed in relation to the molt cycle. Y-organectomy experiments revealed that the onset of premolt development was inhibited, suggesting the presence of molt inducing factor in the Y-organ.     

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.     

A review on genome mapping of penaeid shrimps of commercial importance

Genome mapping of any organism has become vital and most essential to control the gene related functions and also for the production of new traits of the desired properties. Gene mapping has become a very powerful tool in agriculture sector as well as for terrestrial livestock and going to revolutionize both these sectors from the point of view of enhancing production. However, for aquatic organisms, the information pertaining to gene mapping research is limited and only in recent past few attempts have been made in this direction. The rationale behind genome mapping particularly for aquaculture species is to improve the quality of animals through selective breeding and produce genetically superior traits for commercial production. There is a great potential in this field since most of the aquaculture species have not been subjected to genetic improvement. The advantage of gene mapping tool for any organism is to identify and characterize quantitative trait loci associated with commercial important traits and to use these markers in marker‐assisted selection programmes. Now with advent of gene editing (CRIPSR‐Cas) technology one can modify/repair the gene structure and remove the adverse impact of the gene related characters without replacing the whole genome. Gene mapping of polygenic traits of aquaculture species is also gaining lot of importance because of dominant nature of such additional functional genes with unique predominant character in the species. In the present review, attempts have been made to collect details of information on gene mapping of cultivable penaeid shrimps. Furthermore, how these gene maps can be used to modify the gene structure at the targeted cites using gene editing techniques, has also been discussed.     

Hyperspectral waveband selection for internal defect detection of pickling cucumbers and whole pickles

Hyperspectral imaging under transmittance mode has shown potential for detecting internal defect, however, the technique still cannot meet the online speed requirement because of the need to acquire and analyze a large amount of image data. This study was carried out to select important wavebands for further development of an online inspection system to detect internal defect in pickling cucumbers and whole pickles. Hyperspectral transmittance/reflectance images were acquired from normal and defective cucumbers and whole pickles using a prototype hyperspectral reflectance (400-740 nm)/transmittance (740-1000 nm) imaging system. Up to four-waveband subsets were determined by a branch and bound algorithm combined with the k-nearest neighbor classifier. Different waveband binning operations were also compared to determine the bandwidth requirement for each waveband combination. The highest classification accuracies of 94.7 and 82.9% were achieved using the optimal four-waveband sets of 745, 805, 965, and 985 nm at 20 nm spectral resolution for cucumbers and of 745, 765, 885, and 965 nm at 40 nm spectral resolution for whole pickles, respectively. The selected waveband sets will be useful for online quality detection of pickling cucumbers and pickles.