Artificial neural network modeling of the antioxidant activity of lettuce submitted to different postharvest conditions

Abstract

Using novel ebb and flow hydroponic system lettuce (Lactuca sativa L.) samples were grown and then stored under different postharvest conditions (greenhouse with a cube, refrigerator with a cube, and refrigerator without a cube). The effect of the postharvest conditions on bioactive compounds profile and antioxidant activity was studied. All samples were subjected to the bioactive compounds composition analysis as well as to the antioxidant activity determination in order to reveal how the postharvest conditions affect them. The experimental data were used for the antioxidant activity modeling by artificial neural network (ANN) approach. The antioxidant activity was determined by DPPH assay and expressed as IC50. According to the standard statistical parameters, comparison of the experimentally observed and predicted data, and residuals analysis, generated ANNs could be used for the prediction of the antioxidant activity. Practical applications Lettuce (Lactuca sativa L.) samples were grown using novel Ebb and Flow hydroponic system. Different postharvest conditions were used for samples storage. Generated models for the prediction of antioxidant activity were obtained using artificial neural network (ANN) modeling.

Artificial Neural Network Predictive Modelling of luffa cylindrica Seed Oil Antioxidant Yield

“…The hidden layer comprises ten neurons; the coefficient of determination (R 2 ) value at training, validation and testing is 1 for terpineol yield, while the polyphenol yield prediction gave 1 for training and testing, and 0.99996 for confirmation, as shown in Figure 2 and 3; these indicate the level of variability of the experimental results captured by the predicted. As shown in Table 3 and 4, the Bayesian regularization was the best of the algorithms for terpineol and polyphenol yield, having the smallest MSE of 2.25766E-9 and 4.42588E-10, respectively; the optimal results were obtained at epoch 901 and 701 for terpineol and polyphenol yield as shown in Figure 4 and 5, these comparisons indicate that the model predicted antioxidants yield from luffa oil appropriately; The effectiveness of the expected ANN model results is in agreement with reports from (Uzuner & Cekmecelioglu, 2016;Karadžić Banjac et al, 2018;Oke et al, 2020;Adeniyi et al, 2021). Table 5 shows the antioxidant yield of luffa oil compared to guava plant, lemon plant, Sorghum Moench and apple pomace; the yield of 2657mg/l for terpineol compared to the result of 348ml/g and 97ml/g for guava and lemon plant respectively and, 609.37ml/g of polyphenol compared to 313ml/g and 775 ml/g for sorghum Moench and apple pomace, respectively, indicates that luffa oil contains plenty of antioxidants that can be harnessed to proper use.…”

“…Antioxidants occur naturally in vegetables and fruits, prevents free radical attack and reduce carcinogenic disease risk (Karadžić Banjac et al, 2018). In addition, studies have revealed that food rich in antioxidants (flavonoids, polyphenols, vitamins and minerals) has positive health impacts.…”

“…ANN modeling approach has been proven as a reliable technique in antioxidant yield estimation of plants, thus, the antioxidant properties of bananas (Guiné et al, 2015), beet-root (Kovacević et al, 2015), tea (Cimpoiu et al, 2011), polyphenols from green tea (Xi et al, 2013), essential oils (Cabrera & Prieto, 2010), polyphenols from pine fallen foliage (Vats & Negi, 2013), blueberries (Guiné et al, 2018) and lettuce (Karadžić Banjac et al, 2018) have been predicted successfully by ANN. However, there is sparse literature on antioxidant yield from vegetable seed oil.…”

Changes in Metabolite Patterns During Refrigerated Storage of Lamb's lettuce (Valerianella locusta L. Betcke)

“…Valerianella locusta is known for its balanced mineral and chemical composition resulting in high nutritional value and favorable taste qualities (3). The rosettes contain many bioactive compounds, such as vitamin C, carotenoids, phenols, folic acid, sterols and omega-3 fatty acids similar to other salads (4)(5)(6)(7). Długosz-Grochowska et al (8) performed a detailed compositional study on lamb's lettuce and reported the presence of three folate forms and seven phenolic compounds.…”

Artificial Neural Network Modeling of Greenhouse Tomato Yield and Aerial Dry Matter

“…ANNs allow us to develop models based on the intrinsic relations among the variables, without prior knowledge of their functional relationships [9]. Soft computing for ANN techniques has been widely used to develop models to predict different crop indicators, such as growth, yield, and other biophysical processes, and also because of the commercial importance of tomato [10][11][12][13][14][15][16][17][18][19][20][21][22][23] and other vegetables, such as lettuce [24][25][26][27][28][29][30], pepper [31][32][33][34], cucumber [35][36][37][38], wheat [39][40][41][42][43][44][45], rice [46][47][48], oat [49], maize [50,51], corn [52][53][54], corn and soybean [55], soybean…”