Abstract
The Genetically Modified (GMO) Corn Experiment was performed to test the hypothesis that wild animals prefer Non-GMO corn and avoid eating GMO corn, which resulted in the collection of complex image data of consumed corn ears. This study develops a deep learning-based image processing pipeline that aims to estimate the consumption of corn by identifying corn and its bare cob from these images, which will aid in testing the hypothesis in the GMO Corn Experiment. Ablation uses mask regional convolutional neural network (Mask R-CNN) for instance segmentation. Based on image data annotation, two approaches for segmentation were discussed: identifying whole corn ears and bare cob parts with and without corn kernels. The Mask R-CNN model was trained for both approaches and segmentation results were compared. Out of the two, the latter approach, i.e., without the kernel, was chosen to estimate the corn consumption because of its superior segmentation performance and estimation accuracy. Ablation experiments were performed with the latter approach to obtain the best model with the available data. The estimation results of these models were included and compared with manually labeled test data with R 2 = 0.99 which showed that use of the Mask R-CNN model to estimate corn consumption provides highly accurate results, thus, allowing it to be used further on all collected data and help test the hypothesis of the GMO Corn Experiment. These approaches may also be applied to other plant phenotyping tasks (e.g., yield estimation and plant stress quantification) that require instance segmentation.
Highlights
Corn is one of the world’s most important crops and is produced both traditionally and with genetically modified organisms (GMO) (FAOSTAT, 2018)
A whole corn ear had a relatively predictable conical shape regardless of how much of it is consumed, whereas corn kernel parts could be in any shapes and locations based on the consumption of the ear
A deep learning based framework to quantify the consumption of corn with a relatively small number of images collected by community scientists was presented and evaluated
Summary
Corn is one of the world’s most important crops and is produced both traditionally and with genetically modified organisms (GMO) (FAOSTAT, 2018). In 2008, a United States (US) grower observed that mice preferred non-GMO corn over GMO corn (Roseboro, 2008) To test this, another grower repeated the experiment and Instance Segmentation for Corn Consumption published his results online stating that “The squirrel could have switched to GMO, but it did not. Another grower repeated the experiment and Instance Segmentation for Corn Consumption published his results online stating that “The squirrel could have switched to GMO, but it did not It knew it was different” (Roseboro, 2013). Another study done by an Italian group claimed GMO corn to be toxic (Séralini et al, 2012) This led to several studies and debates amongst research community and the corn industry (Butler, 2012). Further studies in favor and against GMO corn were done which is collectively reviewed by Chassy and Tribe (2010) and some of them clarified that “animals are not biased to organic corn.”
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