Sharma Arun, Tiwari Akshat Dutt, Kumari Monika, Kumar Nishant, Saxena Vikas, Kumar Ritesh
Council of Scientific and Industrial Research - Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh-160030, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-201002, India.
Phytochem Anal. 2023 Oct;34(7):729-744. doi: 10.1002/pca.3185. Epub 2022 Nov 11.
Lycopene consumption reduces risk and incidence of cancer and cardiovascular diseases. Tomatoes are a rich source of phytochemical compounds including lycopene as a major constituent. Lycopene estimation using high-performance liquid chromatography is time-consuming and expensive.
To develop artificial intelligence models for prediction of lycopene in raw tomatoes using 14 different physicochemical parameters including salinity, total dissolved solids (TDS), electrical conductivity (EC), firmness, pH, total soluble solids (TSS), titratable acidity (TA), colour values on Hunter scale (L, a, b), total phenolic content (TPC), total flavonoid content (TFC) and antioxidant activity (AOA).
The post-harvest data acquisition was collected through investigation for more than 100 raw tomatoes stored for 15 days. Linear multivariate regression (LMVR), principal component regression (PCR) and partial least squares regression (PLSR) models were developed by splitting data set into train and test datasets. The training of models was performed using 10-fold cross validation (CV).
Principal component analysis showed strong positive association between lycopene, colour value 'a', TPC, TFC and AOA. The R (CV), root mean square error (RMSE) (CV) and RMSE (Test) for best LMVR model was observed to be at 0.70, 8.48 and 9.69 respectively. The PCR model revealed R (CV) at 0.59, RMSE (CV) at 8.91 and RMSE (Test) at 10.17 while PLSR model revealed R (CV) at 0.60, RMSE (CV) at 9.10 and RMSE (Test) at 10.11.
Results of the present study show that epidemiological studies suggest fully ripened tomatoes are most beneficial for consumption to ensure recommended daily intake of lycopene content.
食用番茄红素可降低癌症和心血管疾病的风险及发病率。番茄是包括番茄红素作为主要成分在内的植物化学化合物的丰富来源。使用高效液相色谱法测定番茄红素既耗时又昂贵。
利用14种不同的理化参数，包括盐度、总溶解固体（TDS）、电导率（EC）、硬度、pH值、总可溶性固体（TSS）、可滴定酸度（TA）、亨特色度值（L、a、b）、总酚含量（TPC）、总黄酮含量（TFC）和抗氧化活性（AOA），开发人工智能模型来预测生番茄中的番茄红素。
通过对100多个储存15天的生番茄进行调查收集收获后的数据。通过将数据集拆分为训练集和测试集，建立线性多元回归（LMVR）、主成分回归（PCR）和偏最小二乘回归（PLSR）模型。模型训练采用10折交叉验证（CV）。
主成分分析表明番茄红素、色度值“a”、TPC、TFC和AOA之间存在强正相关。最佳LMVR模型的R（CV）、均方根误差（RMSE）（CV）和RMSE（测试）分别为0.70、8.48和9.69。PCR模型的R（CV）为0.59，RMSE（CV）为8.91，RMSE（测试）为10.17，而PLSR模型的R（CV）为0.60，RMSE（CV）为9.10，RMSE（测试）为10.11。
本研究结果表明，流行病学研究表明，完全成熟的番茄最有利于食用，以确保每日摄入推荐量的番茄红素含量。
