# Current Status of Optical Systems for Measuring Lycopene Content in Fruits: Review
## 4 Current Systems for Estimating Lycopene
### Ultraviolet-Visible (UV-Vis) and Infrared (NIR) Spectroscopy  
Spectroscopy is used to identify maturity states and the internal composition of some fruits and vegetables. It uses optical properties, such as the reflectance and absorbance, in a range of 780-2526 nm [66]. An important aspect in spectroscopy is that absorption causes fundamental vibrations. They are related to the functional groups -CH, -NH, -OH, and -SH [67; 68]. The (NIR) spectroscopy consists of irradiating the study element with a light that can be reflected, absorbed, or transmitted. Once the measurement of the sample is made, the composition is established, as well as the structure, depending on the amount of light measured and the wavelength [69; 70; 71]. Figure 7 shows the elements integrating the \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{3}{*}{**Factor**} & **[PERSON] et al.** & **[PERSON]** & **[PERSON] et al.** & **[PERSON] and [PERSON]** \\  & **(2000)** & **et al. (2013)** & **(2018)** & **(2018)** \\ \cline{2-5}  & **Linear Regression** & **Linear Regression** & **Linear Regression** & **Linear Regression** \\  & **R\({}^{2}\)** & **R\({}^{2}\)** & **Linear Regression** & **Linear Regression** & **R\({}^{2}\)** \\ \hline L\({}^{*}\) & 0.90 & 0.908 & 0.49 & 0.83 \\ \hline a\({}^{*}\) & 0.87 & 0.909 & 0.92 & 0.78 \\ \hline a\({}^{2*}\) & X & X & X & 0.72 \\ \hline b\({}^{*}\) & 0.09 & 0.02 & 0.52 & 0.50 \\ \hline b\({}^{2*}\) & x & X & x & 0.48 \\ \hline (a*/b*)\({}^{2}\) & 0.90 & 0.980 & 0.94 & 0.76 \\ \hline Hue & & & & \\ Tan \(-\)\({}^{1}\) (b*/a*) & 0.44 & X & X & X \\ \hline Chroma & & & & \\ C* = ((a*)\({}^{2}\) + (b*)\({}^{2}\))\({}^{1/2}\) & 0.67 & X & X & 0.36 \\ \hline Lycopene mg/100 g wet weight & 0.91 & 0.586 & X & X \\ \hline \end{tabular} \(X\) = Descriptor not reported by the author.  
\end{table} 
Table 3: Comparison of lycopene measurement systems using color. optical system of the type of (NIR) spectroscopy: light source of the halogen or tungsten type, a monochromator, a sample holder, and detectors. [PERSON] et al. [57] identified the maturity stages of the tomato using spectroscopy (Vis-Nir). Through this, the reflectance spectra were obtained in the range 380 to 2500 nm; these present changes in the region of 400-700 nm and allow the fruits to be classified as shown in Figure 8. Similar studies allow the measurement of lycopene, as in the case of [PERSON] et al. [73], who developed an online spectroscopy (NIR) system. For this, they selected the range of 900 to 1700 nm with the intention of measuring lycopene, \(\beta\)-carotene, and total soluble solids in watermelon (Citrullus lanatus). This system used the NIR On-Line RX-One (Buchi, Flawil, Switzerland), which is made up of a diode array detector (DAD) and a dual tungsten-halogen lamp. In 2013, they performed tests with watermelons on a conveyor belt without movement. From these, two spectra were obtained from two selected regions. By 2014, the four-sided spectra with the moving band were obtained. Three speeds were used for the band, which were 2100, 2400, and 2700 rpm, to obtain a total of 720 spectra. Finally, in 2015, they obtained 35 spectra randomly, using new fruits. The spectra obtained during the study were treated by the standard normal variance (SNV) and the first derivative for the reduction of noise and unwanted information. With the use of principal component analysis (PCA), they identified three groups of data that offer significant information. These groups are the year of sampling, the climate that is associated with the frequency of rains, extreme temperatures, and the physical-chemical characteristics. One aspect to highlight is that these factors together with the radiation modify the lycopene content in the fruits. The reported correlations for lycopene in the case of \(\mathrm{R^{2}}_{\mathrm{cal}}\) calibration were 0.877; for the validation \(\mathrm{R^{2}}_{\mathrm{cv}}\), 0.756; and finally, for the external validation, \(\mathrm{R^{2}}_{\mathrm{Ext}}\), the result obtained was 0.805.