Protein, oil content, linoleic acid, and lignan are several key indicators for evaluating the quality of flaxseed. In order to optimize testing methods flaxseed’s nutritional enhance efficiency screening high-quality flax germplasm resources, we selected 30 flaxseed species widely cultivated in Northwest China as subjects our study. Firstly, gathered hyperspectral information regarding seeds, along with data on protein, lignan, utilized SPXY algorithm classify sample set. Subsequently,...

As a pillar grain crop in China’s agriculture, the yield and quality of corn are directly related to food security stable development agricultural economy. Corn varieties from different regions have significant differences inblade, staminate root cap characteristics, these provide basis for variety classification. However, characteristics may be mixed actual cultivation, which increases difficulty identification. Deep learning classification research based on nodulation features can help...

Potato is one of the most important food crops in world and occupies a crucial position China’s agricultural development. Due to large number potato varieties phenomenon variety mixing, development industry seriously affected. Therefore, accurate identification key link promote industry. Deep learning technology used identify with good accuracy, but there are relatively few related studies. Thus, this paper introduces an enhanced Swin Transformer classification model named MSR-SwinT...

In order to solve the problem of imaging quality industrial cameras for low-light and large dynamic scenes in many fields, such as smart city target recognition, this study focuses on overcoming two core challenges: first, loss image details due significant difference light distribution complex scenes, second, coexistence dark areas under constraints limited range a camera. To end, we propose high-dynamic-range enhancement method based weights pyramid fusion. verify effectiveness method,...

The protein content of flaxseed ( Linum usitatissimum ) is a crucial factor influencing its nutritional value and quality. Spectral technology combined with advanced modeling methods offers fast, accurate, cost-effective approach for predicting content. In this study, visible-near infrared hyperspectral imaging (VNIR-HIS) was fractional order ant colony optimization (FOACO) to determine the flaxseed. Thirty varieties commonly cultivated in Northwest China were selected, data along...

With the continuous innovation and development of technologies for breeding varieties fruits, there are more than 8000 apples in existence. The accurate identification apple can promote healthy stable global industry protect property rights rights-holders. To avoid economic losses due to improper at seedling-procurement stage, this paper proposes classification using images leaves conjunction with network models traditional methods, supplemented deep-learning such as AlexNet, VGG, ResNet,...

Introduction In the actual planting of wheat, there are often shortages seedlings and broken on long ridges in field, thus affecting grain yield indirectly causing economic losses. Variety identification wheat using physical methods timeliness is unsuitable for universal dissemination. Recognition seedling varieties deep learning models has high accuracy, but fewer researchers exist. Therefore, this paper, a lightweight variety recognition model, MssiapNet, proposed. Methods The model based...

The innovation of germplasm resources and the continuous breeding new varieties apples (Malus domestica Borkh.) have yielded more than 8000 apple cultivars. ability to identify cultivars with ease accuracy can solve problems in related property rights protection promote healthy development global industry. However, existing methods are inconsistent time-consuming. This paper proposes an efficient convenient method for classification using a deep convolutional neural network leaf image input,...

Wheat is a very important food crop for mankind. Many new varieties are bred every year. The accurate judgment of wheat can promote the development industry and protection breeding property rights. Although gene analysis technology be used to accurately determine varieties, it costly, time-consuming, inconvenient. Traditional machine learning methods significantly reduce cost time cultivars identification, but accuracy not high. In recent years, relatively popular deep have further improved...

Wheat is a significant cereal for humans, with diverse varieties. The growth of the wheat industry and protection breeding rights can be promoted through accurate identification To recognize seeds quickly accurately, this paper proposes convolutional neural network-based image-recognition method seeds, namely GC_DRNet. model based on ResNet18 network incorporates dense idea by changing its residual module to introducing global contextual module, reducing model’s parameters improving...

Abstract To overcome the challenges in underwater object detection across diverse marine environments—marked by intricate lighting, small presence, and camouflage—we propose an innovative solution inspired human retina's structure. This approach integrates a cone-rod cell module to counteract complex lighting effects introduces reparameterized multiscale for precise feature extraction. Moreover, we employ Wise Intersection Over Union (WIOU) technique enhance camouflage detection. Our...

Accurate detection and counting of flax plant organs are crucial for obtaining phenotypic data the cornerstone variety selection management strategies. In this study, a Flax-YOLOv5 model is proposed data. Based on solid foundation original YOLOv5x feature extraction network, network structure was extended to include BiFormer module, which seamlessly integrates bi-directional encoders converters, enabling it focus key features in an adaptive query manner. As result, improves computational...

<title>Abstract</title> In the context of traditional wheat cultivation, issues such as a lack seedlings and prolonged monopoly are frequently encountered. These phenomena have considerable impact on both grain yield income farmers. The methods identifying seedling varieties rely manual observation measurement. However, these time-consuming, labor-intensive, susceptible to subjective influences, resulting in poor timeliness robustness. detection accuracy speed variety identification...

This work aims to predict the starch, vitamin C, soluble solids, and titratable acid contents of apple fruits using hyperspectral imaging combined with machine learning approaches. First, a camera by rotating samples was used obtain images fruit surface in spectral range 380~1018 nm, its region interest (ROI) extracted; then, optimal preprocessing method preferred through experimental comparisons; on this basis, genetic algorithms (GA), successive projection (SPA), competitive adaptive...