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The quality and safety of agricultural products are of paramount importance in ensuring the health of the food supply chain. Additionally, the composition and trace elements in agricultural products significantly influence their quality and nutritional value. Therefore, the need for rapid and accurate analysis techniques for agricultural product composition is particularly crucial. In the current landscape of evolving compositional analysis technologies, Laser-Induced Breakdown Spectroscopy (LIBS) technology is emerging as a promising analytical tool with broad applications in agricultural product testing. Its characteristics of being rapid, real-time, and capable of simultaneous detection of multiple elements provide an efficient and reliable means for assessing the quality, monitoring safety, and tracing the origin of agricultural products. This technology is expected to play a significant role in controlling and managing the agricultural industry chain and can offer consumers safer and healthier agricultural products. This paper provides an overview of the research status and recent developments of LIBS technology in agricultural product testing applications in recent years. Based on the current research landscape, challenges and opportunities of applying LIBS technology in fields such as agricultural product quality and safety assessment, soil analysis, assessment of crop nutrition, detection of plant diseases, and identification of agricultural product varieties have been evaluated. Moreover, recommendations for further expanding the application of LIBS technology in the agricultural sector are proposed.
The quality and safety of agricultural products are of paramount importance in ensuring the health of the food supply chain. Additionally, the composition and trace elements in agricultural products significantly influence their quality and nutritional value. Therefore, the need for rapid and accurate analysis techniques for agricultural product composition is particularly crucial. In the current landscape of evolving compositional analysis technologies, Laser-Induced Breakdown Spectroscopy (LIBS) technology is emerging as a promising analytical tool with broad applications in agricultural product testing. Its characteristics of being rapid, real-time, and capable of simultaneous detection of multiple elements provide an efficient and reliable means for assessing the quality, monitoring safety, and tracing the origin of agricultural products. This technology is expected to play a significant role in controlling and managing the agricultural industry chain and can offer consumers safer and healthier agricultural products. This paper provides an overview of the research status and recent developments of LIBS technology in agricultural product testing applications in recent years. Based on the current research landscape, challenges and opportunities of applying LIBS technology in fields such as agricultural product quality and safety assessment, soil analysis, assessment of crop nutrition, detection of plant diseases, and identification of agricultural product varieties have been evaluated. Moreover, recommendations for further expanding the application of LIBS technology in the agricultural sector are proposed.
Objective Shale oil is an important unconventional resource that has become a major development focus. Owing to the possible reserves of petroleum and natural gas, information from core samples, which mainly contain geochemical and mineralogical information, has attracted increasing attention from geologists and energy enterprises. Conventional analytical methods for mineralogical analysis, including inductively coupled plasma optical emission or mass spectrometry (ICP -OES/MS), instrumental neutron activation analysis (INNA), and Xray fluorescence (XRF), are unsuitable for the insitu analysis of shale because of their slow analysis speed and limited detection range. Laserinduced breakdown spectroscopy (LIBS) is a novel analytical method for various materials that uses laser pulses focused on a sample to generate laserproduced plasma and spectral emissions. With the advantages of minimal sample preparation, remote analysis, microsample ablation, and high analytical speed, LIBS is an optional access method for analysis of cores. In this study, multielement quantitative analysis of natural shale and sandstone samples is conducted using a micro -LIBS system. A standardized spectral preprocessing method is developed to reduce spectral uncertainty, and a model input parameter optimization process is established to prevent model overfitting while improving model prediction accuracy. A quantitative analysis of Si, Ca, Fe, Al, Mg, and other elements in the shales and sandstones is performed, and the average predicted rootmeansquare error of most samples is less than 1%, providing technical support for regular mineral component analysis and lithology identification of shales and sandstones.Methods A micro -LIBS system was established in this study, consisting of a laser, spectrometer, timing synchronizer, computer, and optical microscope. The system used a nanosecondpulse laser to generate a laser beam that passes through a laser beam splitter and was sampled by a photodiode to detect the laser timing. The transmitted laser beam was introduced into an optical microscope,adjusted to be coaxial with the microscope illumination light path through a laser mirror, and finally focused on the sample surface through a nearinfrared objective lens to generate plasma. Plasma emission was collected by a shortfocus lens to an optical fiber and connected to a sixchannel spectrometer for spectrum collection; the integration time was set to 1 ms. The laser pulse energy was adjusted to 30 mJ, and the detection delay of the spectrometer was set to 800 ns. Before the spectrum acquisition, two laser shots were applied for preablation to stabilize the pulse energy, and 10 accumulated spectra were collected and analyzed. Partial least squares regression was used for the data analysis.Results and Discussions Because of the variety, inhomogeneity, and complexity of the samples, it is necessary to perform spectral line preprocessing and characteristic spectral line identification of the extracted spectra before quantitative analysis.Therefore, th...
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