Using Laser Induced Breakdown Spectroscopy and Machine Learning to Identify Jiangxi Spring Tea Harvesting Periods

Lei Tao; Guangyuan Cai; Zhandong Cheng; Lin Huang; Xiuwen He; Jiang Xu; Mingyin Yao

doi:10.3788/LOP231154

Laser & Optoelectronics Progress, Volume. 61, Issue 9, 0930004(2024)

Using Laser Induced Breakdown Spectroscopy and Machine Learning to Identify Jiangxi Spring Tea Harvesting Periods

Lei Tao^1,2, Guangyuan Cai^1,2, Zhandong Cheng^1,2, Lin Huang³, Xiuwen He¹, Jiang Xu^1,2, and Mingyin Yao^1,2、*

Author Affiliations

¹College of Engineering, Jiangxi Agricultural University, Nanchang 330045, Jiangxi, China

²Key Laboratory of Biological Optoelectronics and Application in Jiangxi Universities, Nanchang 330045, Jiangxi, China

³College of Bioscience and Bioengineering, Jiangxi Agricultural University, Nanchang 330045, Jiangxi, China

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Figures & Tables(12)

Fig. 1. Single experimental sample. (a) Tea leaves; (b) tea infusion enrichment

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Fig. 2. Schematic diagram of LIBS main installation

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Fig. 3. LIBS average spectrogram of tea leaves. (a) The original spectrum of Mt. Lushan fog tea leaves; (b) the original spectrum of Dog bull head tea leaves

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Fig. 4. LIBS average spectrogram of tea infusion. (a) The original spectrum of Mt. Lushan fog tea infusion; (b) the original spectrum of Dog bull head tea infusion

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Fig. 5. Baseline corrected average spectrogram of Mt. Lushan fog tea leaves

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Fig. 6. PCA three-dimensional scatter plot of Mt. Lushan fog tea.(a) Tea leaves; (b) tea infusion; (c) fusion data

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Fig. 7. PCA three-dimensional scatter plot of Dog bull head tea (a) Tea leaves; (b) tea infusion; (c) fusion data

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Fig. 8. Comparison chart of the average recognition rate of one thousand times. (a) Mt. Lushan fog Spring tea; (b) Dog bull head Spring tea

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Table 1. Information of spring tea samples

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Table 1. Information of spring tea samples

No.	Harvesting period	Tea name	CNY/50 g	Sample source
1	before-brightness	Mt.Lushan fog tea	120	Jiangxi Gonghehou Tea Industry Co. Ltd. （Jiujiang，China）
2	before-rain	Mt.Lushan fog tea	70	Jiangxi Gonghehou Tea Industry Co. Ltd. （Jiujiang，China）
3	before-brightness	Dog bull head tea	100	Suichuan County Tanghu-guotou Tea Factory（Ji’an，China）
4	before-rain	Dog bull head tea	50	Suichuan County Tanghu-guotou Tea Factory（Ji’an，China）

Table 2. Preferred 11 spectrum peaks
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Table 2. Preferred 11 spectrum peaks
Characteristic element C I Mg II Mn I Ca II Na I H I K I
Wavelength /nm 247.86 279.55 279.83 393.37 589.00 656.29 766.49
280.27 396.85 589.59 769.90

Table 3. Comparison of classification model results for the cross-validation sets and test sets of Mt. Lushan fog tea

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Table 3. Comparison of classification model results for the cross-validation sets and test sets of Mt. Lushan fog tea

Mt.Lushan fog tea	Tea leaves	Tea infusion	Fusion date	Tea leaves	Tea infusion	Fusion date
Model	Cross-validation sets /%			Test sets /%
LDA	96.46（1.29）	91.31（1.86）	98.29（1.07）	96.78（1.98）	91.48（2.51）	98.60（1.37）
SVM	96.56（1.65）	89.30（2.30）	97.64（1.30）	97.23（2.02）	90.39（2.98）	98.05（1.52）
KNN	94.60（1.81）	87.41（2.53）	94.66（1.67）	94.70（2.12）	87.79（3.43）	95.25（2.11）
EML	97.41（1.15）	86.97（2.40）	97.66（1.08）	97.45（1.88）	87.66（4.12）	97.71（1.70）

Table 4. Comparison of classification model results for the cross-validation sets and test sets of Dog bull head tea

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Table 4. Comparison of classification model results for the cross-validation sets and test sets of Dog bull head tea

Dog bull head tea	Tea leaves	Tea infusion	Fusion date	Tea leaves	Tea infusion	Fusion date
Model	Cross-validation sets /%			Test sets /%
LDA	99.01（0.79）	94.63（1.66）	99.20（0.72）	99.09（0.89）	95.13（2.19）	99.38（0.77）
SVM	96.52（1.18）	95.20（1.58）	98.50（0.94）	96.81（1.92）	95.43（2.05）	98.70（1.13）
KNN	93.46（1.78）	92.72（2.01）	95.63（1.68）	94.10（2.66）	93.43（2.49）	96.11（2.09）
EML	97.05（1.07）	95.21（1.59）	99.37（0.51）	96.87（1.64）	95.48（2.28）	99.43（0.72）

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Lei Tao, Guangyuan Cai, Zhandong Cheng, Lin Huang, Xiuwen He, Jiang Xu, Mingyin Yao. Using Laser Induced Breakdown Spectroscopy and Machine Learning to Identify Jiangxi Spring Tea Harvesting Periods[J]. Laser & Optoelectronics Progress, 2024, 61(9): 0930004

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