In situ diagnosis of mature HLB-asymptomatic citrus fruits by laser-induced breakdown spectroscopy

Nontargeted metabolomics-based multiple machine learning modeling boosts early accurate detection for citrus Huanglongbing

Early accurate detection of crop disease is extremely important for timely disease management. Huanglongbing (HLB), one of the most destructive citrus diseases, has brought about severe economic losses for the global citrus industry. The direct strategies for HLB identification, such as quantitative real-time polymerase chain reaction (qPCR) and chemical staining, are robust for the symptomatic plants but powerless for the asymptomatic ones at the early stage of affection. Thus, it is very necessary to develop a practical method used for the early detection of HLB. In this study, a novel method combining ultra-high performance liquid chromatography/mass spectrometry (UHPLC/MS)-based nontargeted metabolomics and machine learning (ML) was developed for conducting the early detection of HLB for the first time. Six ML algorithms were selected to build the classifiers. Regularized logistic regression (LR-L2) and gradient-boosted decision tree (GBDT) outperformed with the highest average accuracy of 95.83% to not only classify healthy and infected plants but identify significant features. The proposed method proved to be practical for early detection of HLB, which tackled the shortcomings of low sensitivity in the conventional methods and avoid the problems such as lighting condition interference in spectrum/image recognition-based ML methods. Additionally, the discovered biomarkers were verified by the metabolic pathway analysis and content change analysis, which was remarkably consistent with the previous reports.

Detection model of the plasma spectrum based on the polarization recognition rate induced by a low energy density laser

Laser-induced breakdown spectroscopy (LIBS) is a fast recognition method for heavy-metal detection. The recognition rate of the characteristic spectrum is related to the laser-induced energy. In order to analyze the polarization characteristics of plasma and the improvement mechanism of recognition rate under the condition of low energy density, a detection model of polarization recognition rate was established by exploring the intensity formula of discrete spectral data. At the Brewster angle, the LIBS and discrete spectral data of Cd and Cu elements induced by five energies were measured in combination with the polarization spectrometric path. According to the model of polarization recognition rate, the optimization effect of the polarization separation approach on the plasma spectra of heavy-metal elements has been clarified, and the recognition rate of discrete spectra induced by low energy density has been improved. This study shows that the increase of laser energy is helpful to the recognition of characteristic spectral lines. Under the same energy induction, the polarization recognition rate of heavy-metal elements is larger, and this characteristic is more obvious under low energy density. This model not only improves the recognition rate of the plasma spectrum but also greatly reduces the requirement of laser energy and the damage of the medium surface, which is a more effective nondestructive testing technology.

Diagnosis of HLB-asymptomatic citrus fruits by element migration and transformation using laser-induced breakdown spectroscopy

Huanglongbing (HLB) is one of the most devastating bacterial diseases in citrus growth and there is no cure for it. The mastery of elemental migration and transformation patterns can effectively analyze the growth of crops. The law of element migration and transformation in citrus growth is not very clear. In order to obtain the law of element migration and transformation, healthy and HLB-asymptomatic navel oranges collected in the field were taken as research objects. Laser-induced breakdown spectroscopy (LIBS) is an atomic spectrometry technique for material component analysis. By analyzing the element composition of fruit flesh, peel and soil, it can know the specific process of nutrient exchange and energy exchange between plants and the external environment, as well as the rules of internal nutrient transportation, distribution and energy transformation. Through the study of elemental absorption, the growth of navel orange can be effectively monitored in real time. HLB has an inhibitory effect on the absorption of navel orange. In order to improve the detection efficiency, LIBS coupled with SVM algorithms was used to distinguish healthy navel oranges and HLB-asymptomatic navel oranges. The classification accuracy was 100%. Compared with the traditional detection method, the detection efficiency of LIBS technology is significantly better than the polymerase chain reaction method, which provides a new means for the diagnosis of HLB-asymptomatic citrus fruits.

Detection model of copper based on polarization degree induced by low-energy density laser

In order to analyze the mechanism of plasma polarization characteristics and the improvement effect of spectral signal-to-back ratio, the intensity formulas of continuous spectrum and discrete spectrum were derived by exploring the path of the radiation spectrum. At the Brewster angle, the model of polarization degree was established based on the measured spectral data to identify the radiation intensity of plasma. The experimental results showed that the polarization characteristics of the background and discrete spectrum were both observed in the plasma spectrum of a copper element, and there were obvious differences in polarization degree and vibration direction. Moreover, cadmium and chromium were used to verify the detection model. It was found that the characteristic signals of the polarization spectrum were more than the effective peaks in laser-induced breakdown spectroscopy, and the variation trend was relatively gentle. The model retained the effective information in the continuum spectrum and fully explored the basic polarization mechanism of plasma. The measured data were not only convenient to observe the characteristic signal peaks of elements, but also greatly improved the recognition effect. This method could extract effective information of illumination plasma under the condition of low incident light intensity and reduce the damage of medium surface, which is a more effective nondestructive testing technology.