Less is more: Vital roles of bioactive equivalency in assessing food quality

Food quality is a dominating factor influencing public health and affecting people, irrespective of age, race, gender, income, has raised concerns worldwide. It known to all that food influenced by many factors, such as climate change, harvesting, processing, drying, packaging. To be specific, with increasing temperatures atmospheric carbon dioxide levels, results in yield losses the reduction protein essential micronutrients (Agrimonti et al., 2021). The contents primary secondary metabolites were related harvest time significantly (Akhatou & Fernández-Recamales, 2014). Appropriate processing including washing (e.g., water or adding chemicals water) (Subramaniam 2021) drying high-temperature-based, dielectric-based, low-temperature, radiation, hybrid techniques) (Fathi 2022) can reduce postharvest nutrients. Intelligent packaging, informative corrective responsive could continuously monitor status, enable safety remediation, convey users (Zhang Ultimately, nutrients people eat every day have most direct influence on human health. There are countless nutritional constituents existing food, fats, amino acids, proteins, flavonoids, carbohydrates, vitamins, minerals. Many them been identified functional, flavonoids (Xiao, 2017). However, information not conveyed consumers properly through nutrition facts labels using current control (QC) methods. recommended daily intake was updated US Drug Administration (2022) follows: 275 g total carbohydrate, 78 fat, 50 protein, added sugars, 28 dietary fiber, 20 saturated microelements, vitamins. Of list, fat (saturated trans fat), cholesterol, sodium, well vitamin D, calcium, iron, potassium, listed label packaged (US Administration, 2022). Noteworthily, fatty acids determined official methods analysis published AOAC International (Latimer, 2019), ultimately value label. According method 972.28 (first adopted 1972 revised 1985), calculated after continuous extraction hexane. In contrast, acid, monounsaturated acid sum respective from limited list GC methyl esterification based 996.06 1996 2001). observed there transition measuring content individual more precisely. still some shortcomings. One shortcoming these making scientists manufacturers focus high-content phytochemicals. other various their derivatives bioactive compounds neglected even high activities. Given contributions active especially low-level ones ignored QC methods, sensitive precise warranted provide better coverage functions avoid limitation level. Accordingly, aim this commentary introduce two new concepts, equivalency (BEF) (BEQ), assess big-data era, established databases record predict compounds, BIOPEP-UWM database peptides (Minkiewicz 2019) AOD: antioxidant (Feng Meanwhile, bioactivities predicted quantitative structure–activity relationships (QSARs) modeling uses wide variety statistical machine learning techniques (Cherkasov Therefore, combined bioassays (Xiao 2020), it easy obtain activity compounds. With determined, an attempt made establish standard precisely quality. Thus, BEQ BEF, proposed evaluate considering both compound levels bioactivities. Equation (1), number thus meet needs assessing (2), BEF specific inversely proportional IC50 i. Noteworthy, product insignificant multiplied extremely large one will sizable. Consequently, lower would generate larger (3), low those IC50s should emphasized, following “less more” hypothesis. After defining deducing theoretically, put into action? different situations. First, tens thousands studies indicated feasibility calculating BEF. reported gallic VC, caffeic 0.67, 2.28, 1.96 μg/ml, respectively (Spagnol 2019); chlorogenic VC 40.8 11.2 (Hwang 2018). ABTS radical scavenging activities cysteine 96.77% 91.78%, respectively, at 100 whereas methionine did exhibit any (Kim 2020). BEFgallic = 2.28/0.67 3.40, BEFcaffeic 2.28/1.96 1.16, BEFchlorogenic 11.2/40.8 0.27, BEFCysteine 96.77%/91.78% 1.05, BEFMethionine 0. Second, while percentage inhibition preferred for data obtained literature. Luckily, approaches, QSAR model (Ahmadi 2021), antibacterial (Bouarab-Chibane antihypertensive (Wang 2020) capacities. note, also applicable bioactivities: when activity) linearly concentration within range, set same above mentioned; extending functions, calculation BEFs consider proper dose-effect relationships. estimated chemical feasible calculate according then further precision. For example, if mentioned except detected 1 2, C1 0.5, 0.8, 2.0, 0.9, methiLonine 2.5, C2 1.3, 1.2, 1.0 μg/100 mg dry weight. Obviously, sum1 AAs (=3.4) > sum2 (=2.2), PAs (=3.3) (=3.0), (=6.7) (=5.2). conclude “better” than 2 comparing contents. BEQ1 (=4.1) < BEQ2 (=5.7) (1) reveals source. From theoretical example calculation, interesting findings. Low highly class little, which produce pseudo-low result. Albeit, concept BEQ, result reversed, real clarifying necessity normalization assessment. general workflow evaluation shown Figure 1. Bioactive life benefits body. cannot reflect contribution functional Fortunately, application makes precisely, although discussion scientific data, vivo, needed We call attention toward low-content but hope future, officially national government, included consumers. conclusion, emphasis we closer improving considers quantity. This work supported Science Technology Development Fund, Macau SAR [grant FDCT 0025/2021/A1]. authors declare no conflict interest.