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Agriculture, Volume 15, Issue 10

May-2 2025 - 97 articles

Cover Story: Environmental control is critical for enhancing the yield and quality of industrially cultivated Pleurotus pulmonarius. To enhance the model’s capability to extract features from each growth stage and address the challenge of precise segmentation in complex scenarios, we propose a real-time detection method based on the improved GSP-RTMDet to control the environment in mushroom houses. This method enhances detection and segmentation outcomes in the real-world environments of houses, offering a more accurate and efficient growth stage perception solution for environmental control. Future work will focus on enhancing the model’s generalization capabilities, improving and refining the model’s ability to express and differentiate growth states, improving production efficiency, and reducing management costs. View this paper
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Articles (97)

  • Article
  • Open Access
4 Citations
1,327 Views
22 Pages

Air-assisted sprayers are an essential piece of equipment for improving spraying efficiency and pesticide utilization; their performance directly affects the effectiveness of pesticide application. This study, addressing the plant protection needs of...

  • Article
  • Open Access
690 Views
20 Pages

The Design and Testing of a New Antitangling and Antisticking Knife for a Wet Clay Soil Environment

  • Guosheng Geng,
  • Tailai Chen,
  • Maohua Xiao,
  • Chenshuo Xie and
  • Cungan Tang

Aiming at the problem that rotary tiller knife rollers are prone to entanglement with straw in the wet and sticky soil environment of rice fields in the middle and lower reaches of the Yangtze River in China, an antitangling and sticking cutter was d...

  • Article
  • Open Access
6 Citations
1,126 Views
24 Pages

Oilseed rape yield critically reflects varietal superiority. Rapid field-scale estimation enables efficient high-throughput breeding. This study evaluates unmanned aerial vehicle (UAV) hyperspectral imagery’s potential for yield prediction at t...

  • Article
  • Open Access
1,130 Views
24 Pages

Response Prediction and Experimental Validation of Vibration Noise in the Conveyor Trough of a Combine Harvester

  • Jianpeng Jing,
  • Guangen Yan,
  • Zhong Tang,
  • Shuren Chen,
  • Runzhi Liang,
  • Yuxuan Chen and
  • Xiaoying He

The noise generated by combine harvesters during operation has drawn growing attention, particularly that of the conveying trough shell, whose noise generation mechanism remains unclear. This study investigated the vibration radiation noise character...

  • Article
  • Open Access
1 Citations
1,898 Views
12 Pages

Slugs are significant agricultural pests, causing extensive crop damage and economic losses. While chemical molluscicides are commonly used for control, concerns about their environmental impact have driven interest in alternative methods, including...

  • Article
  • Open Access
1 Citations
1,868 Views
18 Pages

The content and health impact of harmful heavy metals in agricultural products from strong geological background concentration areas have received increasing attention. To investigate the impact of soil heavy metal contamination on the tea plantation...

  • Article
  • Open Access
2,489 Views
15 Pages

One of the key techniques for successful almond tree cultivation in newly irrigated areas is increasing planting density. To investigate this, field experiments were carried out over five consecutive growing seasons (2019–2023) to evaluate the...

  • Article
  • Open Access
1 Citations
1,543 Views
17 Pages

Enhancing Genomic Prediction Accuracy in Beef Cattle Using WMGBLUP and SNP Pre-Selection

  • Huqiong Zhao,
  • Xueyuan Xie,
  • Haoran Ma,
  • Peinuo Zhou,
  • Boran Xu,
  • Yuanqing Zhang,
  • Lingyang Xu,
  • Huijiang Gao,
  • Junya Li and
  • Zezhao Wang
  • + 1 author

Genomic selection (GS) plays a crucial role in livestock breeding. However, its implementation in Chinese beef cattle breeding is constrained by a limited reference population and incomplete data records. To address these challenges, this study aimed...

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Agriculture - ISSN 2077-0472