# 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
#### 4.3.2 Multispectral (MSI) and Hyperspectral (HSI) Imaging Systems  
The optical systems of multispectral and hyperspectral images are used to acquire both the spatial and spectral information of a product by combining traditional methods of imaging and spectroscopy. With them, internal and external information is obtained from the study matrix [86]. [PERSON] et al. [87] performed the measurement of the optical properties of fruits and vegetables. The multispectral system shown in Figure 11 is made up of a light source and a hyperspectral image unit. The unit contains a focusing lens and a spectrograph. The broadband light was coupled to an optical fiber and a micro lens to generate a 1.0 mm diameter beam, which impinges on the sample at 15\({}^{\circ}\) from the vertical direction. The images were captured in online scan mode covering a spectral range between 200 and 1100 nm. The difference between the traditional UV-VIS and NIR spectroscopy techniques is based on the regional study of the  
Figure 10: Raman spectroscopy system for lycopene measurement [86]. Figure 9: Spectra of tomato maturity behavior using Raman spectroscopy [84]. matrix. In the case of multispectral and hyperspectral images, they evaluate the entire surface of the element of study, and provide spatial and spectral information [85]. [PERSON] et al. [9] developed a system using multispectral images with chemo-metric methods to measure lycopene and the phenolic compounds in tomato. This system operated with 19 wavelengths from 405 to 970 nm. The total samples used for calibration and validation were 162 fruits in different stages of maturity. When calibrating, they used two-thirds of the total of fruits and the rest during validation. The proposed models to measure lycopene are partial least squares regression (PLS), the least squares support vector machine (LS-SVM), and the backpropagation neural network (BPNN). According to its results, BPNN obtained the best results for its R\({}^{2}\)C calibration of 0.957 and the R\({}^{2}\)P prediction of 0.938. The research by [PERSON] et al. [7] measured the superficial distribution of carotenes and chlorophyll in mature tomatoes using imaging spectrometry and PLS. The recorded range was 400 to 700 nm with a resolution of 1 nm. The images were recorded using two illuminators Dolan-Jenner PL900 (Andover St. Lawrence, Massachusetts, USA), with quartz halogen lamps of 150 W in the range of 380 and 2000 nm. The root mean square error of the lycopene concentration in one pixel was 0.95 and for the base tomato it was 0.96. Here, 500 mg samples of the fruit were milled with liquid nitrogen and 4 mL of acetone with 50 mg of CaCO\({}_{3}\). To the granules obtained after centrifugation, lycopene was extracted with 4 mL of acetone, 2 mL of hexane, and 5 mL of acetone: hexane (4:1). All solvents contained 0.1% (_w/v_) butylated hydroxytoluene (BHT). Table 4 summarizes the application of different optical systems for the estimation of the lycopene content. The correlation coefficients are reported with the lycopene, instrumentation, wavelengths for the estimation of the same, treatment of the matrix, type of vegetable and fruit, acquisition method, and range of measurement. In the same table, the use of spectroscopy is highlighted, which allows a good correlation with tomato lycopene of R = 0.996 to be obtained. The proposed system uses the spectrum regions 4000 to 6000 cm\({}^{-1}\) and 6000 to 8000 cm\({}^{-1}\), together with an MSC treatment. Another optical system that has a good correlation with the lycopene content in tomato is vegetable color measurement using the correlation a\({}^{\star}\)/b\({}^{\star}\). It should be noted that high-performance liquid chromatography is commonly used for the validation of lycopene measurement systems. The relevance is that it allows quantification of the correlation between the states of maturity of the fruits when using the absorbance.