Abstract
Fruit is not only delicious, but it also contains iron, potassium, magnesium, and other microelements necessary for the human body. Banana, pineapple and kiwifruit were selected as samples for testing. A laser with a wavelength of 532 nm was focused on the samples’ surface to generate a plasma. The emission spectrum of the atoms and ions in the plasma were collected by optical receivers, and the optimal condition was confirmed by analyzing the signal-to-noise ratio. The electronic temperature characteristics of the Fe plasma were studied under optimal experimental conditions. The maximum electron temperature of the Fe plasma occurred after a time delay of 300 ns in bananas, after 400 ns in pineapples and after 400 ns in kiwifruit. The electronic temperature of the Fe plasma increased with the time delay before the maximum point was reached. However, the temperature decreased after the maximum point was reached. At the beginning of the decline, the plasma decreased rapidly, but later decreased slowly. The range of the variation of the electron temperature of the Fe plasma in bananas, pineapples, and kiwifruits was 12388.29–19958.3 K, 11994.21–16856.4 K, and 13388.2–19607.32 K, respectively.
1 Introduction
Laser-induced plasma spectroscopy uses laser pulses as the energy sources and lenses to focus the laser on the surface of the sample [1]. The sample in the focus area undergoes multiphoton ionization to generate free electrons, and then avalanche ionization will occur to produce a large amount of plasma [1]. The specific manifestation is that sparks and noises are present on the surface of the sample. The sample is then analyzed according to the emission spectrum of the plasma. Solids, liquids, and gases, regardless of the shape of the object, can be analyzed by laser-induced plasma spectroscopy technology which can be operated in real time, online, and remotely and is convenient to operate. At present, this technology has been applied to the identification of historical and cultural artifacts, space exploration, industrial inspection, and chemical analysis. Numerous small online inspection systems based on this technology have also been developed [2, 3, 4, 5, 6, 7, 8].
In recent years, laser-induced plasma spectroscopy has been used to study trace elements, including qualitative and quantitative analyses of heavy metal elements, research of various processing algorithms, design of multi-functional experiments, and enhancement of experimental devices. Zhang et al. from the Institute of Modern Physics of Chinese Academy of Sciences analyzed the trace elements in apples, strawberries, and kiwifruit using laser-induced plasma spectroscopy [9]. Li (2011) of Jiangxi Agricultural University analyzed the metal elements in the pericarp and pulp of mandarin oranges and navel oranges through laser-induced plasma spectroscopy [10]. Zhang Xu et al. (2012) of Jiangxi Agricultural University used laser-induced plasma spectroscopy to quantitatively analyze the chromium content in apples quantitatively [11]. Kuoray et al. (2013) of Shanxi Agricultural University applied laser-induced plasma spectroscopy to determine the mineral content of three jujube species from different production areas [12]. Abdul Jabbar et al. (2019) of Milpur University of Science and Technology used laser-induced plasma spectroscopy to examine the elemental composition of roots, stems, seeds, and other parts of rice [13]. Given the inevitable interaction between a laser and matter, precise control cannot be carried out through the sample preparation. Consequently, the shock wave generated by the rapid collision between laser and plasma, plasma and plasma, and the interaction between plasma and ambient gas increased the signal uncertainty of the spectral measurement system and decreased the accuracy of repeatability. Under the influence of the matrix effect, the measurement error was relatively large. These factors have limited the large-scale commercial application of laser-induced plasma spectroscopy. In this paper, laser-induced plasma spectroscopy was used to study the electron temperature changes of the Fe plasma, with time delay, in three kinds of fruit, namely, banana, pineapple, and kiwi fruit are taken as research objects, and the electron temperature changes of Fe plasma in laser-induced fruits with time delay are studied. Plasma electron temperature is an important characteristic of plasma. The experimental results can help us to explore the mechanism and process of the interaction between the laser and matter. In addition, the results can also contribute to laser-induced plasma spectroscopy technology in the analysis of fruits and other crops.
2 Experimental setup
A Nd:YAG laser was focused on the surface of the sample through a lens, and plasma is formed on the sample. The emission spectrum of the plasma is received by an optical receiver and transmitted to a spectrometer through an optical fiber. The spectrometer splits the collected spectrum. Then, the ICCD (Intensified Charge-coupled Device) captures the spectrum and converts the collected optical signal into an electrical signal. Finally, it transmits the information to a computer for display. The experimental apparatus is shown in Figure 1. The exposure time was set to 0.2ms in the experiment, and each picture is obtained by averaging over 200 laser pulses.
3 Spectral analysis
3.1 Spectra of fruits with changing gate width
With a fixed delay and changing the acquisition gate width of ICCD, the 3D spectra of bananas, pineapples, and kiwifruit obtained are, shown in Figure 2, Figure 3, and Figure 4, respectively.
3.2 Spectra of fruits with changing delay
With a fixed the acquisition gate width and changing acquisition delay of ICCD, the spectral 3D images of bananas, pineapples, and kiwifruit are shown in Figure 5, Figure 6, and Figure 7, respectively.
3.3 Signal to noise ratio analysis
To calculate the signal-to-noise ratio, the 696.6 nm spectral line is selected, and the best optimization conditions of the three fruits can be obtained by analyzing their SNR charts with different delays and gate widths. Firstly, Figure 8 and Figure 9 show that the optimal banana optimization conditions are a delay of 500 ns and a gate width of 800 ns. Secondly, Figure 10 and Figure 11 demonstrate that the optimal optimization conditions for pineapple are a delay of 400 ns and a gate width of 400 ns. Finally, Figure 12 and Figure 13 indicate that the best optimization conditions for the kiwifruit are a delay of 400 ns of delay and a gate width of 600 ns.
Given that the exposure delay of ICCD is constant, the time-resolved spectra of different ICCD gate widths are explored. If the gate width is too large despite numerous spectral line signals, several background signals are present. However, if the gate width is too small, the detected signal is weak [13].
When the plasma is initially formed by laser induction, the bremsstrahlung from inside the plasma produces a continuous strong background spectrum, and the characteristic spectral lines of the sample are masked. Later, the background spectral lines decline faster than atomic spectral lines and ion spectral lines. Thus, the emission spectral lines of elements are displayed, and the signal-to-noise ratio of the spectral lines increases. If the delay is too small, the spectral lines generated by the laser cannot be filtered out, thus affecting the experimental analysis. When the exposure delay is too large, numerous interference signals enter the spectrometer; thus, choosing the correct exposure delay for spectrogram analysis is especially important [13].
3.4 Optimum spectrogram
By analyzing the signal-to-noise ratio of the three different fruits, changing the fixed gate width and delay, and determining the best optimization conditions, the best spectrograms of bananas, pineapples, and kiwifruit can be obtained.
4 Electron temperature analysis of the plasma
The Boltzmann oblique line method is used to calculate the electron temperature of the plasma.
In Eq. (1), Im is the intensity of the characteristic spectral line, Em is the energy of the upper level, Am is the transition probability of the corresponding spectral line, gm is the statistical weight of the upper levels, and kB is the Boltzmann constant. If Em is the abscissa and ln
4.1 Electron temperature of laser-induced Fe plasma in bananas
For the calculation of the electron temperature of the Fe plasma in fruits, four spectral lines of Fe with wavelengthsof 247.9nm, 279.6 nm, 393.3 nm, and 656.9 nmwere selected. Table 1 lists the relevant spectral constants of the four spectral lines.
Wavelength (nm) | Excitation energy (cm−1) | Excitation energy (eV) | gk | Ak(106s−1) |
---|---|---|---|---|
247.9 | 48304.643 | 5.978 | 5 | 21 |
279.6 | 77861.650 | 9.636 | 10 | 20.00 |
393.3 | 50186.834 | 6.211 | 5 | 5.92 |
656.9 | 53393.673 | 6.608 | 9 | 6.00 |
The Boltzmann oblique lines (ln(Iλ/gA) ∼ Ek) of three spectral lines are calculated. Then, the electron temperature of Fe plasma can be obtained by slope.
The relationship between the electron temperature characteristics of the laser-induced Fe plasma in a banana and the time delay is shown in Figure 18. In the time delay range of 200-300ns, the electron temperature of the Fe plasma increases as the delay increases. In the delay range of 300-1000ns, the electron temperature of the Fe plasma decreases as the delay increases, reaching a maximum value at 300ns, and the electron temperature varies between 12388.29K and 19958.3K.
4.2 Electron temperature of laser-induced Fe plasma in pineapples
For the calculation of the electron temperature of the Fe plasma in pineapples, three spectral lines with Fe wave-lengths of 279.6 nm, 393.3nm, and 656.9 nm were selected. Table 1 lists the relevant spectral constants of the three spectral lines. The Boltzmann oblique lines (ln(Iλ/gA) ∼ Ek) of the three spectral lines were calculated. Then, the electron temperature of the Fe plasma was obtained from the slope.
The relationship between the electron temperature characteristics of the laser-induced Fe plasma in pineapples and the time delay is shown in Figure 20. In the time delay range of 200–400 ns, the electron temperature of the Fe plasma decreases as time delay increases. In the time delay range of 400–1000 ns, the electron temperature of the Fe plasma decreases as time delay increases after reaching the maximum value at 400 ns. The electron temperature varies between 11994.21 K and 16856.4 K.
4.3 Electron temperature of laser-induced Fe plasma in kiwi fruit
For the calculation of the electron temperature of the Fe plasma in kiwifruit, three spectral lines with Fe wave-lengths of 247.9 nm, 279.6 nm, and 656.9 nm were selected. Table 1 lists the relevant spectral constants of the three spectral lines. The Boltzmann oblique lines (ln(Iλ/gA) ∼ Ek) of the three spectral lines are calculated. Then, the electron temperature of the Fe plasma was obtained from the slope.
The relationship between the electron temperature characteristics of the Fe plasma in a laser-induced kiwifruit and the time delay is shown in Figure 22. In the time delay range of 200-400 ns, the electron temperature of the Fe plasma decreases as time delay increases. In the time delay range of 400-1000 ns, the electron temperature decreases with the increase of the time delay after reaching the maximum value at 400 ns. Moreover, the electron temperature varies between 13388.2 K and 19607.54 K.
According to the analysis of the evolution characteristics of the plasma electron temperature of three fruits with time delay, the plasma electron temperature gradually increases. After rising to the maximum value, the plasma electron temperature then decreases with increasing time delay, and the speed decelerates. The plasma diffuses outward after it is formed, and its diffused kinetic energy is converted from thermal energy. Thus, the plasma electron temperature decreases with the expansion of volume. When the plasma electron temperature falls to a lower range, the efficiency of thermal energy conversion to kinetic energy decreases, and the downward trend of the plasma electron temperature slows down.
The time evolution trends are similar, but the electron temperatures are different at the same time delay. The highest electron temperatures are different, and the delay corresponding to the maximum value are also different.
5 Conclusion
In this paper, the spectra of bananas, pineapples, and kiwifruits are measured for a series of experiments, and the electron temperature characteristics of the Fe plasma induced by a laser are analyzed with time delay. The range of the electron temperatures of the Fe plasma in bananas, pineapples, and kiwi fruits was 12388.29–19958.3 K, 11994.21–16856.4 K, and 13388.2–19607.32 K, respectively.Laser-induced plasma spectroscopy has attracted much attention due to its unique advantages. For example, samples can be liquid, solid, or gaseous and it allows for long-range monitoring, especially under special circumstances. In addition, the analysis time is short, and the process can simultaneously detect multiple elements on line. It is possible to combine laser-induced plasma technology, Raman spectrum technology, and fluorescence spectrum technology to obtain comprehensive material composition information. Although certain problems in the practical application of laser-induced plasma spectroscopy still exist, the field of application of this technology is expected to expand and become popular in the future along with the development of science.
Acknowledgement
The National Natural Science Foundation of China(11604003), the Key Program of Natural Science Foundation of Anhui Province (KJ2019A085) and the Anhui Province Key Laboratory of Optoelectronic Materials Science and Technology (OMST201703)
References
[1] Lu TX. Principle and application of laser spectroscopy. Hefei: China University of Science and Technology Press; 2009. pp. 201–5.Search in Google Scholar
[2] Xu XB, Du CW, Ma F, Shen Y, Wu K, Liang D, et al. Detection of soil organic matter from laser-induced breakdown spectroscopy (LIBS) and mid-infrared spectroscopy (FTIR-ATR) coupled with multivariate techniques. Geoderma. 2019;355(1):113905.10.1016/j.geoderma.2019.113905Search in Google Scholar
[3] Tang HJ, Hao XJ, Hu XY, et al. Study on spectral time evolution of laser induced Cu plasma. Laser and Infrared. 2018;48(11):1341–5.Search in Google Scholar
[4] Ye TB. Experimental study on laser plasma shielding. Nanjing: Nanjing University of Technology; 2007.Search in Google Scholar
[5] Giorgio S. Recent advances and future trends in LIBS applications to agricultural materials and their food derivatives: an overview of developments in the last decade (2010–2019). Part II. Crop plants and their food derivatives. Trends Analyt Chem. 2019;118:453–69.10.1016/j.trac.2019.05.052Search in Google Scholar
[6] Hou GY, Wang P, Tong CZ. Progress in laser-induced breakdown spectroscopy and its applications. China Optics. 2013;6(4):491–2.Search in Google Scholar
[7] Zhang GY, Ji H, Li ST, Zheng HM. Characterization of plasma induced by laser effect on coal sample. Guang Pu Xue Yu Guang Pu Fen Xi. 2016 May;36(5):1323–7.Search in Google Scholar
[8] Meng DS, Zhao NJ,Ma MJ, Gu YH, Yu Y, Fang L, et al. Rapid soil classification with laser induced breakdown spectroscopy. Guang Pu Xue Yu Guang Pu Fen Xi. 2017 Jan;37(1):241–6.Search in Google Scholar
[9] Zhang DC, Ma XW, Zhu XL, et al. Application of laser-induced breakdown spectroscopy in analyzing microelements in three kinds of fruit samples. Wuli Xuebao. 2008;57(10):6348–9.Search in Google Scholar
[10] Li QL. Analysis and research on laser induced breakdown spectroscopy applied to determination of metal elements in citrus and soil. Nanchang: Jiangxi Agricultural University; 2011.Search in Google Scholar
[11] Zhang X, Yao MY, Liu MH, et al. Quantitative analysis of chromium in apples by laser-induced breakdown spectroscopy. Laser and Infrared. 2012;4(5):495–6.Search in Google Scholar
[12] Guo R, Wang XY. Determination of mineral elements in red jujube with laser-induced breakdown spectroscopy. Shanxi Nongye Daxue Xuebao. 2013;33(6):498–9.Search in Google Scholar
[13] Jabbar A, Akhtar M, Ali A, Mehmood S, Iftikhar S, Baig MA. Elemental composition of rice using calibration free laser induced breakdown spectroscopy. Optoelectron Lett. 2019;15(1):53–63.10.1007/s11801-019-8099-0Search in Google Scholar
[14] Fu YX, Tang YQ, Xu L, et al. Measurement on trace element composition of Chinese medicinal materials by laser induced breakdown spectroscopy. Journal of Bengbu University. 2017;6(3):20–4.Search in Google Scholar
[15] Wang L, Fu YX, Xu L, et al. The Effect of Sample temperature on characteristic parameters of the nanosecond laser-induced Cu Plasma. spectroscopy and spectral analysis. 2019; 39(4): 1247-1251.Search in Google Scholar
[16] Fu YX, Wang L, Ma LY, et al. An investigation on the laser - induced Cu plasma characteristics. Journal of Atomic and Molecular Physics. 2019;36(02):263–7.Search in Google Scholar
[17] Wang L, Zhou Y, Fu YX, Xu L, Gong H, Cheng R. Effect of sample temperature on radiation characteristics of nanosecond lase-induced soil plasma. Chin J Chem Phys. 2019;32(06):760–4.10.1063/1674-0068/cjcp1901015Search in Google Scholar
[18] Yu JL, Li C, Yao GX, et al. Spatial Evolution Characteristics of Laser-induced Plasma in Liquid Matrix. Chin J Lasers. 2019;46(8):0802001.10.3788/CJL201946.0802001Search in Google Scholar
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