Development of a Mushroom Growth Measurement System Applying Deep Learning for Image Recognition

Abstract

In Taiwan, mushrooms are an agricultural product with high nutritional value and economic benefit. However, global warming and climate change have affected plant quality. As a result, technological greenhouses are replacing traditional tin houses as locations for mushroom planting. These greenhouses feature several complex parameters. If we can reduce the complexity such greenhouses and improve the efficiency of their production management using intelligent schemes, technological greenhouses could become the expert assistants of farmers. In this paper, the main goal of the developed system is to measure the mushroom size and to count the amount of mushrooms. According to the results of each measurement, the growth rate of the mushrooms can be estimated. The proposed system also records the data of the mushrooms and broadcasts them to the mobile phone of the farmer. This improves the effectiveness of the production management. The proposed system is based on the convolutional neural network of deep learning, which is used to localize the mushrooms in the image. A positioning correction method is also proposed to modify the localization result. The experiments show that the proposed system has a good performance concerning the image measurement of mushrooms.

Deep Learning Techniques for Agronomy Applications

“…Furthermore, the harvest time could be estimated in accordance with observations of the size classification of mushrooms. The results showed that the average harvest time error of the proposed method was 3.7 hours [43].…”

“…Three papers on DL-based image recognition techniques for agronomy applications are as follows: (1) "Automatic segmentation and counting of aphid nymphs on leaves using convolutional neural networks," by Chen et al [41]; (2) "Estimating body condition score in dairy cows from depth images using convolutional neural networks, transfer learning, and model ensembling techniques," by Alvarez et al [42]; and (3) "Development of a mushroom growth measurement system applying deep learning for image recognition," by Lu et al [43].…”

Design and evaluation of an intelligent sorting system for bell pepper using deep convolutional neural networks

“…The global average pooling was employed in the developed classifier block to overcome the overfitting that likely occurs by decreasing the number of parameters (Nasiri et al, 2020). The batch normalization enhances the passage of extracted features from one layer to the next one and improves the accuracy of the deep network (Lu et al, 2019). Regularizations are techniques used to reduce errors by fitting a function appropriately on the given training set and avoiding overfitting.…”

Image Recognition of Agricultural Crops, Plants and Forests

“…Однако, эти теплицы имеют сложную структуру управления [18]. В статье [19] представлена разработка системы контроля роста и подсчета количества грибов на основе интеллектуальной сверточной нейронной сети. Предложенная система записывает данные о грибах и передает их на мобильный телефон фермера (рис.6), что повышает оперативность, эффективность управления производством.…”

“…Предложенная система записывает данные о грибах и передает их на мобильный телефон фермера (рис.6), что повышает оперативность, эффективность управления производством. [19] 7. Распознавание ландшафта по спутниковым изображениям.…”