Publications by authors named "Lirong Xiang"

High agility, maneuverability, and payload capacity, combined with small footprints, make legged robots well-suited for precision agriculture applications. In this study, we introduce a novel bionic hexapod robot designed for agricultural applications to address the limitations of traditional wheeled and aerial robots. The robot features a terrain-adaptive gait and adjustable clearance to ensure stability and robustness over various terrains and obstacles.

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NLRP3 inflammasomes-mediated proinflammatory response and mitochondrial dysfunction play a critical role in the etiology and pathogenesis of Parkinson's disease. Negative regulation of NLRP3 inflammasome activation through mitophagy may be an important strategy to control NLRP3 inflammasome-mediated proinflammatory responses. Palmatine (PAL), an isoquinoline alkaloid found in various of plants, has potent pharmacological effects such as anti-inflammatory and anti-oxidation.

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The last decades have witnessed a rapid development of noninvasive plant phenotyping, capable of detecting plant stress scale levels from the subcellular to the whole population scale. However, even with such a broad range, most phenotyping objects are often just concerned with leaves. This review offers a unique perspective of noninvasive plant stress phenotyping from a multi-organ view.

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Computer vision (CV), a non-intrusive and cost-effective technology, has furthered the development of precision livestock farming by enabling optimized decision-making through timely and individualized animal care. The availability of affordable two- and three-dimensional camera sensors, combined with various machine learning and deep learning algorithms, has provided a valuable opportunity to improve livestock production systems. However, despite the availability of various CV tools in the public domain, applying these tools to animal data can be challenging, often requiring users to have programming and data analysis skills, as well as access to computing resources.

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  • Rice blast causes significant rice production losses, making early detection vital for global food security.
  • This study introduces a new detection model called RiceBlastYolo, which utilizes UAV images and incorporates advanced image generation techniques for improved accuracy.
  • The RiceBlastYolo model achieved impressive detection metrics, with an accuracy of 99.51% and outperformed other common detection models in precision and recall rates.
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Tea polyphenol and epigallocatechin gallate (EGCG) were considered as key components of tea. The rapid prediction of these two components can be beneficial for tea quality control and product development for tea producers, breeders and consumers. This study aimed to develop reliable models for tea polyphenols and EGCG content prediction during the breeding process using Fourier Transform-near infrared (FT-NIR) spectroscopy combined with machine learning algorithms.

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  • Brassinosteroids (BRs) are plant hormones that play a role in growth, development, and responses to stress, but traditional experiments for studying them are slow and low-throughput.
  • A new automated system called RoAD was developed to conduct high-throughput BR and drought experiments on soil-grown Arabidopsis plants using robotics and advanced imaging techniques.
  • RoAD allows for precise measurement of plant traits and has been extended to study BR responses in maize, offering a powerful tool for understanding how BR affects plant growth and stress management.
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Cellulase plays an important role in addressing the issue of the energy crisis. However, the yield and degradation efficiency of cellulase remain a major challenge. In the present study, we aimed to verify whether ammonium ion (NH) could induce cellulase synthesis from T.

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  • Accurate counting of corn stands is essential for breeders, but manual methods are slow and error-prone.
  • UAVs can collect plant images, but face challenges like motion blur and complex backgrounds that hinder detecting small seedlings.
  • This research developed a reliable automated method using YoloV3 and Kalman filter, achieving over 98% accuracy at early growth stages and can be integrated into various agricultural vehicles for efficient monitoring.
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Metastasis refers to the progressive dissemination of primary tumour cells and their colonization of other tissues and is associated with most cancer-related mortalities. The disproportional and systematic distribution pattern of distant metastasis in different cancers has been well documented, as is termed metastatic organotropism, a process orchestrated by a combination of anatomical, pathophysiological, genetic and biochemical factors. Extracellular vesicles (EVs), nanosized cell-derived membrane-bound particles known to mediate intercellular communication, are now considered crucial in organ-specific metastasis.

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  • * The proposed system uses a turntable to capture multiple 3D views of leafy vegetables, enabling accurate measurement of key growth parameters like height and leaf area through advanced algorithms.
  • * Experiments with 63 pots of lettuce showed a strong correlation between Kinect measurements and traditional methods, validating the system's effectiveness for assessing plant growth and biomass.
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