Probabilistic Neural Networks for Segmentation of Features in Corn Kernel Images

A method is presented for clustering of pixel color information to segment features within corn kernel images. Features for blue–eye mold, germ damage, sound germ, shadow in sound germ, hard starch, and soft starch were identified by red, green, and blue (RGB) pixel value inputs to a probabilistic neural network. A data grouping method to obtain an exemplar set for adjustment of the Probabilistic Neural Network (PNN) weights and optimization of a universal smoothing factor is described. Of the 14,427 available exemplars (RGB pixel values sampled from previously collected images), 778 were used for adjustment of the network weights, 737 were used for optimization of the PNN smoothing parameter, and 12,912 were reserved for network validation. Based on a universal PNN smoothing factor of 0.05, the network was able to provide an overall pixel classification accuracy of 86% on calibration data and 75% on unseen data. Much of the misclassification was due to overlap of pixel values among classes. When an additional network layer was added to combine similar classes (blue–eye mold and germ damage, sound germ and shadow in sound germ, and hard and soft starch), network results were significantly enhanced so that accuracy on validation data was 94.7%. Image quality was shown to be important to the success of this algorithm as lighting and camera depth of field effects caused artifacts in the segmented images

Acoustic Properties of Soybeans

Acoustic transmission and impact force response methods were investigated for classification of soybeans. The transmission method was slow and not suitable for real-time application. A polynomial was fitted to the deconvolved frequency spectrum of acoustic impulse data for soybeans. The curve fitting procedure successfully predicted the mass of each soybean. The size of soybeans was related to the bandwidth. Diseased soybeans consistently showed narrower bandwidths than healthy soybeans. The diseased and damaged soybeans had broad variations in low frequency which was quantifiable by threshholding the error of fit in the curve fitting procedure

Conveyors for Bulk Handling of Seed Soybeans

Six soybean-seed conveyors were evaluated for capacity and seed damage. The belt conveyor, the flight conveyor, and the nylon-brush auger did not cause significant damage to soybean seed during conveying. The capacity of the belt conveyor declined significantly at 30° angle of inclination. The steel-flighting auger caused the most amount of damage, followed by the auger with rubber intake, and the pneumatic conveyor

Conveyors for Bulk Handling of Seed

Conveyors are used to fill and unload bulk seed storage bins and to transfer seed within a seed cleaning plant This publication describes commercial conveyors available and how to select one.https://lib.dr.iastate.edu/extension_ag_pubs/1161/thumbnail.jp

Quantitative exposure assessment for confinement of maize biogenic systems

The development of transgenic crops as production platforms for biogenic agents will largely depend on the success of efforts to confine the genes and their expressed proteins in field environments. We have used quantitative exposure assessment to evaluate how management practices affect materials escape due to outcrossing by pollen flow or grain loss during harvest operations. Specifically, we study the use of maize to produce biogenic agents within field-confined systems. Decision trees representing simplified schemes of fully conforming (designed to comply with current regulatory standards for field confined trials), partially conforming, and non-conforming management practices were developed. Exemplifying assumptions and published data for conformance and material fate probabilities were used in Monte Carlo simulations to forecast materials escape by pollen outcrossing and harvest operations from a 1 ha source field. Deterministic analyses showed fully conforming confinement management restricted materials loss to low levels (for this example, outcrossing produced \u3c1 in 106 kernels in receptor fields). The corresponding high-end (90th percentile) probabilistic result was 16- and 4333-fold higher (relative to deterministic outcrossing = 1) for outcrossing and harvest loss, respectively. For partially conforming practice, high-end outcrossing ranged from 100- to \u3e15 000-fold over the base result in receptor fields, and harvest loss was \u3e10 000-fold over the base result. For non-conforming practice, high-end outcrossing produced \u3e15 000-fold greater kernels in receptor fields and high-end harvest loss was at least 19 000-fold greater. Deterministic estimates of off-field loss by machine transfer are as much as 30 000-fold higher for non-conforming operations relative to the base case of pollen outcrossing. Better knowledge of failure frequencies for confinement management practices, improved physical models of materials flows, refined analysis of confinement loss probabilities using quantitative tools, and decision analysis to improve and audit management system performance are all needed to extend understanding of confinement integrity beyond the exemplifying case used here

Morphological Variation in the Wild-Weedy Complex of Sorghum bicolor In Situ in Western Kenya: Preliminary Evidence of Crop-to-Wild Gene Flow?

Crop wild relatives are important components of agroecosystems and have over the years been exploited in breeding programs as sources of genes for novel traits. Information on the extent and patterns of variability is important in formulating effective conservation and utilization strategies for existing crop wild relative populations. We conducted surveys and collections of wild and weedy accessions of Sorghum bicolor (L.) Moench in Lambwe Valley in western Kenya in order to investigate occurrence, distribution, and morphological variability in the wild-weedy complex of S. bicolor under local agroecological conditions. We also attempted to understand the role, if any, of crop-to-wild gene flow in structuring variability within and among populations. The morphological data presented here showed wide variability within wild-weedy sorghum populations with respect to habitats and morphotypes. True wild sorghum populations in national parks and the sugarcane belt were clearly distinguishable from the putative hybrids or intermediate forms found in sorghum fields, in sorghum field margins, and, to some extent, by the roadside near sorghum fields. The existence of these intermediate forms is empirical evidence of introgression between cultivated sorghum and its wild-weedy relatives. Extensive introgression, especially within in situ conservation areas and/or in areas of high diversity, would lead to genetic erosion and possible depletion of these important wild sorghum genetic resources

Color classification of corn germplasm using computer vision

A color classification program was developed for classifying the corn germplasm into seven different color groups based on kernel colors. This heuristic based rule supervised color classification program has an overall accuracy of 99%