Increasing urbanization, rising per capita incomes and affordability are shaping the way our food is produced and consumed globally. The associated changes in lifestyle are influencing the composition of food baskets, food consumption patterns and behaviors [1,2,3,4]. With the advent of digitalization and increased access to information, consumers are becoming more cognizant about food and its sources [5]. There is increasing focus on well-being and shifts in consumer preferences toward foods that are grown sustainably. Consequently, plant-based diets (PBDs) are gaining popularity owing to their numerous environmental and human health benefits [6].

日益加劇的城市化、人均收入的增加以及消費(fèi)能力的提升正在全球范圍內(nèi)重塑食品的生產(chǎn)和消費(fèi)方式。伴隨而來的生活方式變化正影響著食品籃子的構(gòu)成、食品消費(fèi)模式和行為習(xí)慣[1,2,3,4]。隨著數(shù)字化時(shí)代的到來和信息獲取的便捷性提高，消費(fèi)者對(duì)食品及其來源的認(rèn)知度也在不斷增強(qiáng)[5]。人們?cè)絹碓疥P(guān)注健康福祉，消費(fèi)偏好也逐漸轉(zhuǎn)向可持續(xù)種植的食品。因此，植物性飲食（PBDs）因其眾多的環(huán)境和人類健康益處而日益受到歡迎[6]。

1.2. Plant-Based Diets: What Do We Know?

1.2. 植物性飲食：我們了解什么？

Diet refers to a lifestyle adopted by an individual, and largely relates to an eating plan and regimen for habitual nourishment. With PBD, an individual relies on plant-based products (PBPs) for his/her daily nutritional needs. Typical PBDs maximize the consumption of nutrient-rich plant foods while minimizing processed foods, oils, and animal foods (including dairy products and eggs) [7]. It is pertinent to note that at present, there are varying opinions in the scientific community about idealistic PBDs. However, there is a general cognizance that PBDs are associated with a multitude of human and environmental health benefits. Some epidemiological and interventional human studies have suggested that PBDs exert beneficial health effects against obesity-related metabolic dysfunction, type 2 diabetes mellitus and chronic low-grade inflammation [8,9,10]. Furthermore, the production of PBDs tend to be less resource-intensive and more environmentally friendly for various reasons, including lowered levels of greenhouse gas emissions (GHGEs), in comparison to raising animals for human consumption [11].

飲食是指個(gè)人所采取的生活方式，主要與日常飲食計(jì)劃和習(xí)慣營養(yǎng)有關(guān)。在植物性飲食（PBD）中，個(gè)體依賴植物性產(chǎn)品（PBPs）來滿足其日常營養(yǎng)需求。典型的植物性飲食會(huì)最大化營養(yǎng)豐富的植物性食物的攝入量，同時(shí)盡量減少加工食品、油脂和動(dòng)物性食物（包括乳制品和雞蛋）的攝入量[7]。值得注意的是，目前科學(xué)界對(duì)于理想化的植物性飲食存在不同意見。然而，普遍認(rèn)識(shí)到的是，植物性飲食與人類和環(huán)境的健康益處息息相關(guān)。一些流行病學(xué)和干預(yù)性人體研究表明，植物性飲食對(duì)與肥胖相關(guān)的代謝功能障礙、2型糖尿病和慢性低度炎癥具有有益的健康影響[8,9,10]。此外，與飼養(yǎng)動(dòng)物供人類食用相比，植物性飲食的生產(chǎn)往往資源消耗較少且更加環(huán)保，包括溫室氣體排放量較低[11]。

As most PBDs rely heavily on plant-based products (PBPs), there will be an increased global demand for PBPs to meet the changing consumer preferences. For the purpose of this review, the scope will be limited to fresh PBPs at the post-harvest stage, where the produce makes its first entry for quality assessments.

由于大多數(shù)植物性飲食嚴(yán)重依賴植物性產(chǎn)品（PBPs），因此為了滿足不斷變化的消費(fèi)者偏好，全球?qū)BPs的需求將會(huì)增加。為了本綜述的目的，其范圍將僅限于收獲后階段的新鮮PBPs，即這些產(chǎn)品在首次進(jìn)行質(zhì)量評(píng)估時(shí)所處的階段。

1.3. PBPs: Nutritional and Sensory Properties

1.3. 植物性產(chǎn)品：營養(yǎng)和感官特性

PBPs comprise of vegetables, fruits, lentils, grains, legumes, nuts and seeds. They offer a myriad of nutritional and functional benefits for human health promotion. Apart from macronutrients and micronutrients, many of these PBPs provide a range of bioactive compounds to combat inflammation, strengthen antioxidant defenses, and general immune system [12,13,14].

植物性產(chǎn)品（PBPs）包括蔬菜、水果、扁豆、谷物、豆類、堅(jiān)果和種子。它們?yōu)槿祟惤】荡龠M(jìn)提供了眾多的營養(yǎng)和功能益處。除了宏量營養(yǎng)素和微量營養(yǎng)素外，許多PBPs還提供了一系列生物活性化合物，以對(duì)抗炎癥、增強(qiáng)抗氧化防御和整體免疫系統(tǒng)[12,13,14]。

A considerable fraction of bioactive compounds/metabolites in PBPs, such as pigments, phytochemicals and other secondary metabolites, contribute to the sensory properties of fresh PBPs. Flavor, color and texture together contribute to the overall eating experience associated with PBPs, and are often a deterministic factor in influencing consumer acceptance. Among these three sensory properties, flavor often has the highest influence on consumer acceptance and behavior. Apart from being a critical quality attribute, flavor also provides valuable information about the nutritional quality of the food [15]. While consumers generally recognize flavor as the most dominant quality attribute for certain PBPs such as fruits and vegetables, it is the interaction of flavor and texture that has a significant effect on consumer acceptance of PBPs [16]. However, for the purpose of this review, we will focus on flavor-related attributes of fresh PBPs.?

在植物性產(chǎn)品（PBPs）中，相當(dāng)大一部分的生物活性化合物/代謝物，如色素、植物化學(xué)物質(zhì)和其他次級(jí)代謝物，對(duì)新鮮PBPs的感官特性有所貢獻(xiàn)。風(fēng)味、顏色和質(zhì)地共同構(gòu)成了與PBPs相關(guān)的整體食用體驗(yàn)，并且通常是影響消費(fèi)者接受度的決定性因素。在這三種感官特性中，風(fēng)味往往對(duì)消費(fèi)者的接受度和行為有最大的影響。除了是關(guān)鍵的質(zhì)量屬性外，風(fēng)味還提供了關(guān)于食物營養(yǎng)質(zhì)量的有價(jià)值信息[15]。雖然消費(fèi)者通常認(rèn)為風(fēng)味是某些PBPs（如水果和蔬菜）最顯著的質(zhì)量屬性，但風(fēng)味和質(zhì)地的相互作用對(duì)消費(fèi)者接受PBPs有顯著影響[16]。然而，為了本綜述的目的，我們將重點(diǎn)關(guān)注新鮮PBPs與風(fēng)味相關(guān)的屬性。

Flavor is perceived primarily by the sense of taste and olfaction (aromatics/aroma) [17]. Aroma and taste receptors, located in the nose and mouth, respectively, are responsible for distinct flavor recognition. It is generally accepted that olfactory stimuli (aroma metabolites) contribute significantly to the flavor experience of most food products. The unique taste sensations and aroma associated with PBPs come from a complex mixture of compounds that belong to different chemical classes. They originate from the primary and secondary metabolism in PBPs and are generally bioactive, with aroma metabolites being volatile in nature while, the taste metabolites often being non-volatile. Both the volatile and non-volatile bioactive fraction in PBPs, such as phenols, flavonoids, isoflavones, terpenes, and glucosinolates, contribute to bitter, acidic, or astringent flavor profiles [18,19]. The presence of these bioactive compounds is an intrinsic property of PBPs, and their synthesis is often influenced by multiple genetic and environmental factors [20,21,22]. Considering the diverse nature of these bioactive compounds and their contribution to the flavor of fresh PBPs, an inclusive approach for their quality assessment at the post-harvest stage is valuable for entire supply chain management. The significance of including a detailed characterization of bioactive compounds for quality assessment has received considerable attention for certain processed food products [23,24,25]. However, quality assessment for fresh PBPs at the post-harvest stage mainly relies on conventional techniques, as discussed in the next section.

風(fēng)味主要通過味覺和嗅覺（即香氣）來感知[17]。分別位于鼻子和口中的香氣和味覺受體負(fù)責(zé)不同的風(fēng)味識(shí)別。通常認(rèn)為，嗅覺刺激（香氣代謝產(chǎn)物）對(duì)大多數(shù)食品的風(fēng)味體驗(yàn)有著顯著的貢獻(xiàn)。與PBPs相關(guān)的獨(dú)特味覺感受和香氣來自于屬于不同化學(xué)類別的復(fù)雜化合物混合物。這些化合物來源于PBPs的初級(jí)和次級(jí)代謝，并且通常具有生物活性，其中香氣代謝產(chǎn)物具有揮發(fā)性，而味覺代謝產(chǎn)物則通常不具有揮發(fā)性。PBPs中的揮發(fā)性和非揮發(fā)性生物活性成分，如酚類、黃酮類、異黃酮類、萜烯類和硫代葡萄糖苷等，都會(huì)給風(fēng)味帶來苦、酸或澀的特征[18,19]。這些生物活性化合物的存在是PBPs的內(nèi)在特性，并且它們的合成往往受到多種遺傳和環(huán)境因素的影響[20,21,22]。考慮到這些生物活性化合物的多樣性和它們對(duì)新鮮PBPs風(fēng)味的貢獻(xiàn)，在收獲后對(duì)它們進(jìn)行質(zhì)量評(píng)估的全面方法對(duì)于整個(gè)供應(yīng)鏈的管理具有重要意義。對(duì)于某些加工食品產(chǎn)品，在質(zhì)量評(píng)估中包括生物活性化合物的詳細(xì)表征已受到相當(dāng)大的關(guān)注[23,24,25]。然而，對(duì)于新鮮PBPs在收獲后的質(zhì)量評(píng)估，主要還是依賴于傳統(tǒng)技術(shù)，這將在接下來的部分中討論。

2.1. Post Harvest Handling: Current State-of-Art Technologies for Flavor Related Attributes

2.1. 收獲后處理：與風(fēng)味相關(guān)屬性的當(dāng)前先進(jìn)技術(shù)

At present, the post-harvest quality assessment of fresh PBPs is effectively regulated for attributes related to food safety/human health risk (heavy metals, chemical contamination, microbiological), but loosely regulated for attributes associated with consumer acceptance and eating experience. These regulations are imposed both at international and national levels, as well as within the individual supply chains [26]. Current quality assessment parameters do not effectively inform on the kind of metabolites or chemical compounds that are responsible for the unique flavor profiles of fresh PBPs. However, this could be particularly important for formulating new products in this domain, keeping in mind the changing consumption trends and evolving flavor preferences.

目前，新鮮PBPs的收獲后質(zhì)量評(píng)估在食品安全/人類健康風(fēng)險(xiǎn)（重金屬、化學(xué)污染、微生物）相關(guān)的屬性上得到了有效的監(jiān)管，但在與消費(fèi)者接受度和食用體驗(yàn)相關(guān)的屬性上監(jiān)管較為寬松。這些監(jiān)管措施在國際、國家層面以及各個(gè)供應(yīng)鏈內(nèi)部都得到了實(shí)施[26]。然而，當(dāng)前的質(zhì)量評(píng)估參數(shù)并未有效地提供關(guān)于哪種代謝物或化學(xué)化合物負(fù)責(zé)新鮮PBPs獨(dú)特風(fēng)味特征的信息。但是，這對(duì)于該領(lǐng)域新產(chǎn)品的配方制定可能尤為重要，特別是考慮到不斷變化的消費(fèi)趨勢(shì)和不斷演變的風(fēng)味偏好。

For any PBP, the relative importance of a quality attribute depends on the commodity and its end-use [27]. In general, the post-harvest handling steps for PBPs include identification of the key quality attributes from food safety/human health-related risks (minimum statutory requirements), followed by establishing quality control/quality assurance (QA/QC) procedures to (i) maintain acceptable quality level for the consumer; and (ii) ensure that minimum quality standards are met.

對(duì)于任何PBP，一個(gè)質(zhì)量屬性的相對(duì)重要性取決于該商品及其最終用途[27]。一般來說，PBPs的收獲后處理步驟包括首先識(shí)別與食品安全/人類健康風(fēng)險(xiǎn)相關(guān)的關(guān)鍵質(zhì)量屬性（法定最低要求），然后建立質(zhì)量控制/質(zhì)量保證（QA/QC）程序，以（i）保持消費(fèi)者可接受的質(zhì)量水平；（ii）確保達(dá)到最低質(zhì)量標(biāo)準(zhǔn)。

The quality assessment of fresh PBPs routinely involves sensory and instrumental methods. In general, sensory methods are used for developing new products and determining product standards, while instrumental methods fare better in assessing the quality of the fresh PBPs on a routine basis [28]. Sensory evaluation is usually performed by a trained sensory panel, and it has two components: the analytical component, which is used to detect differences in products, and affective measurements, which determine preference. Instrumental measurements, on the other hand, focus on the chemical and physical characteristics of PBPs, and encompass a wide range of techniques to determine flavor attributes. For example, a hydrometer that can detect total soluble solids is often used to determine sugar levels while, pH meter is used to measure the level of sourness in food products [28].

新鮮PBPs（植物性產(chǎn)品）的質(zhì)量評(píng)估通常涉及感官方法和儀器方法。一般來說，感官方法用于開發(fā)新產(chǎn)品和確定產(chǎn)品標(biāo)準(zhǔn)，而儀器方法在日常評(píng)估新鮮PBPs的質(zhì)量方面表現(xiàn)更佳[28]。感官評(píng)價(jià)通常由經(jīng)過培訓(xùn)的感官評(píng)估小組進(jìn)行，包括兩個(gè)組成部分：分析性成分，用于檢測產(chǎn)品之間的差異；以及情感測量，用于確定偏好。另一方面，儀器測量則側(cè)重于PBPs的化學(xué)和物理特性，并采用多種技術(shù)來確定風(fēng)味屬性。例如，檢測總可溶性固體的比重計(jì)常用于確定糖分水平，而pH計(jì)則用于測量食品產(chǎn)品的酸度水平[28]。

2.2. Gaps in Current Technologies and Need for Complementary Approaches

2.2 當(dāng)前技術(shù)的不足與互補(bǔ)方法的需求

Instrumental techniques aimed at evaluating the physical and chemical characteristics of PBPs are advantageous as they: (i) provide high accuracy and great precision; (ii) are often more sensitive to small differences between samples, which assist in determining quality trends; and (iii) they are high-throughput and are often available in semi-automated and automated formats [29]. However, the physicochemical characteristics of PBPs have little relevance to consumer acceptability and thus, the results can be used in a limited way to define the quality attributes of PBPs [30]. For this purpose, sensory evaluation is often recommended to accurately assess the quality attributes of fresh PBPs. Sensory evaluation also has certain disadvantages as it requires a trained sensory panel and it is often time consuming, laborious and challenging.

旨在評(píng)估PBPs物理和化學(xué)特性的儀器技術(shù)具有優(yōu)勢(shì)，因?yàn)樗鼈儯海╥）提供高精度和高準(zhǔn)確性；（ii）通常對(duì)樣品之間的小差異更敏感，有助于確定質(zhì)量趨勢(shì)；（iii）具有高通量，并且通常以半自動(dòng)和自動(dòng)格式提供[29]。然而，PBPs的物理化學(xué)特性與消費(fèi)者接受度之間的相關(guān)性很小，因此這些結(jié)果只能以有限的方式用于定義PBPs的質(zhì)量屬性[30]。為此，通常建議采用感官評(píng)價(jià)來準(zhǔn)確評(píng)估新鮮PBPs的質(zhì)量屬性。然而，感官評(píng)價(jià)也存在一些缺點(diǎn)，如需要訓(xùn)練有素的感官評(píng)估小組，且往往耗時(shí)、費(fèi)力且具有挑戰(zhàn)性。

To complement and extend the repertoire of the existing methodologies, detailed and quantitative analyses to measure flavor-associated metabolites are warranted. Integrating such technologies in current quality assessment of fresh PBPs will (i) ensure product uniformity; (ii) strengthen consumer acceptability for PBDs and PBPs in general; (iii) complement current assessment platforms for quality and food safety of fresh PBPs; and (iv) aid in determining maturity and degree of ripening of PBPs at the post-harvest stage.

為了補(bǔ)充和擴(kuò)展現(xiàn)有方法體系，對(duì)與風(fēng)味相關(guān)的代謝產(chǎn)物進(jìn)行詳細(xì)和定量的分析是必要的。將此類技術(shù)整合到新鮮PBPs（植物性產(chǎn)品）的當(dāng)前質(zhì)量評(píng)估中，將（i）確保產(chǎn)品的一致性；（ii）增強(qiáng)消費(fèi)者對(duì)PBDs（可能是指植物基產(chǎn)品或其他相關(guān)術(shù)語，但在此上下文中可能指的是廣義上的植物性產(chǎn)品）和PBPs的總體接受度；（iii）補(bǔ)充當(dāng)前對(duì)新鮮PBPs質(zhì)量和食品安全的評(píng)估平臺(tái)；（iv）有助于確定收獲后PBPs的成熟度和成熟程度。

3. Metabolite Fingerprinting for Quality Assessment of PBPs

3. PBPs質(zhì)量評(píng)估的代謝物指紋圖譜

3.1. Metabolomics in Agri-Food Sector: Current Practices

3.1 農(nóng)食領(lǐng)域的代謝組學(xué)：當(dāng)前實(shí)踐

Metabolomics allows for studying multiple small molecules or metabolites in a cell, tissue or organism. It is defined as the comprehensive characterization of small molecules present in a biological sample [31,32,33]. Metabolomics routinely utilizes sophisticated and high-throughput analytical platforms such as gas chromatography and liquid chromatography–mass spectrometry (GC–MS and LC–MS) and nuclear magnetic resonance (NMR) spectroscopy [34]. With the advent of chemometrics and advanced analytical platforms, metabolomics has greatly facilitated our understanding of the global metabolome and pathway networks [35]. Metabolomics approaches involve untargeted or targeted analyses, and the selection of the approach is largely dependent on the experimental question and expected outcomes [36]. Untargeted analyses utilize an unbiased profiling or metabolic fingerprinting approach focused on uncovering the global metabolome to evaluate diverse chemical classes of metabolites associated with different pathways. On the other hand, targeted analyses rely on a priori knowledge of the class of metabolites or pathways that are of interest [37]. However, the combination of these analyses is often required to obtain complete information of interest.

代謝組學(xué)允許研究細(xì)胞、組織或生物體中的多種小分子或代謝產(chǎn)物。它被定義為對(duì)生物樣品中存在的小分子進(jìn)行全面表征[31,32,33]。代謝組學(xué)通常使用復(fù)雜且高通量的分析平臺(tái)，如氣相色譜和液相色譜-質(zhì)譜聯(lián)用（GC-MS和LC-MS）以及核磁共振（NMR）光譜[34]。隨著化學(xué)計(jì)量學(xué)和先進(jìn)分析平臺(tái)的出現(xiàn)，代謝組學(xué)極大地促進(jìn)了我們對(duì)全局代謝組和代謝途徑網(wǎng)絡(luò)的理解[35]。代謝組學(xué)方法包括非靶向或靶向分析，方法的選擇很大程度上取決于實(shí)驗(yàn)問題和預(yù)期結(jié)果[36]。非靶向分析采用無偏見的輪廓分析或代謝指紋圖譜方法，專注于揭示全局代謝組，以評(píng)估與不同途徑相關(guān)的多種化學(xué)類別的代謝產(chǎn)物。另一方面，靶向分析依賴于對(duì)感興趣的代謝產(chǎn)物類別或途徑的先驗(yàn)知識(shí)[37]。然而，為了獲得完整的感興趣信息，通常需要將這兩種分析方法結(jié)合起來。

Over the past few decades, metabolomics has been extensively applied to various fields of science owing to new developments in analytical instrumentation and data-analytics platforms [38,39,40,41]. Although still in their infancy, metabolomics-based approaches have gained significant interest in the agri-food sector for a diversity of applications including food processing, quality control, plant breeding for improved crop varieties and product development [42,43]. However, at present, metabolomics-based approaches have not been adopted by the regulatory agencies for food quality assessment, although in some cases they have been found to be efficient, with clear benefits over conventional methods. For instance, metabolomics-based approaches have proved valuable to the food industry for the aroma analysis of fresh and processed PBPs [44,45,46,47]. It is pertinent to note that most of the current research in food metabolomics is focused on evaluating various quality attributes of processed/semi-processed food products. Efforts in the area of fresh produce are mostly restricted to economically important PBPs or PBPs grown for specific end-use [45].

在過去的幾十年里，由于分析儀器和數(shù)據(jù)分析平臺(tái)的新發(fā)展，代謝組學(xué)已被廣泛應(yīng)用于科學(xué)的各個(gè)領(lǐng)域[38,39,40,41]。盡管仍處于起步階段，但基于代謝組學(xué)的方法在農(nóng)食行業(yè)已經(jīng)引起了廣泛關(guān)注，并應(yīng)用于多種領(lǐng)域，包括食品加工、質(zhì)量控制、作物品種改良和產(chǎn)品開發(fā)[42,43]。然而，目前監(jiān)管機(jī)構(gòu)尚未將基于代謝組學(xué)的方法用于食品質(zhì)量評(píng)估，盡管在某些情況下，這些方法已被證明是有效的，并且相對(duì)于傳統(tǒng)方法具有明顯優(yōu)勢(shì)。例如，基于代謝組學(xué)的方法在新鮮和加工PBPs的香氣分析方面對(duì)食品工業(yè)具有重要價(jià)值[44,45,46,47]。值得注意的是，目前食品代謝組學(xué)的大部分研究都集中在評(píng)估加工/半加工食品產(chǎn)品的各種質(zhì)量屬性上。而在新鮮農(nóng)產(chǎn)品領(lǐng)域的研究大多局限于經(jīng)濟(jì)上重要的PBPs或特定最終用途的PBPs[45]。

3.2. Metabolomics for Evaluating Flavor Associated Metabolites in Fresh PBPs

3.2 基于代謝組學(xué)評(píng)估新鮮PBPs中的風(fēng)味相關(guān)代謝產(chǎn)物

Within the agri-food sector, several diverse areas utilize metabolomics approaches for a variety of applications, as discussed in the previous?Section 3.1. One such application involves evaluating the flavor-associated metabolites in fresh PBPs, which are determined by their biochemical composition. As stated in earlier?Section 3.1, flavor has the largest influence on consumer behavior and consumption pattern [15], and consequently, most of the research efforts in this domain are catered towards determining the flavor-related metabolites in PBPs. Perception of flavor involves both volatile aroma metabolites as well as non-volatile taste metabolites which belong to different classes.

在農(nóng)食行業(yè)中，如第3.1節(jié)所述，代謝組學(xué)方法被用于多種應(yīng)用。其中一項(xiàng)應(yīng)用就是評(píng)估新鮮PBPs中的風(fēng)味相關(guān)代謝產(chǎn)物，這些代謝產(chǎn)物由其生化成分決定。正如第3.1節(jié)所述，風(fēng)味對(duì)消費(fèi)者行為和消費(fèi)模式有最大影響[15]，因此該領(lǐng)域的大部分研究都致力于確定PBPs中的風(fēng)味相關(guān)代謝產(chǎn)物。風(fēng)味的感知既涉及揮發(fā)性香氣代謝產(chǎn)物，也涉及屬于不同類別的非揮發(fā)性味覺代謝產(chǎn)物。

To summarize, reliable and credible estimations of metabolites corresponding to flavor-related sensory attributes in PBPs require careful sampling strategies, thorough pre-processing and extraction procedures followed by robust analytical platforms.

總結(jié)來說，為了對(duì)植物性生物產(chǎn)品（PBPs）中與風(fēng)味相關(guān)的感官屬性進(jìn)行可靠且可信的代謝物估算，需要精心的采樣策略、徹底的預(yù)處理和提取程序，以及強(qiáng)大的分析平臺(tái)。

3.4. Metabolomics and Quality Assessment of PBPs

3.4 植物性生物產(chǎn)品的代謝組學(xué)與質(zhì)量評(píng)估

The quality of the fresh PBPs in terms of their nutritive value and flavor profiles is essentially driven by their biochemical composition. Biochemical composition is also a key factor in determining other important properties of fresh PBPs such as shelf life, nutritional stability, and economic value. New tools are required to define “quality” to include more quantitative information about the biochemical composition of food, as consumers’ expectations continue to grow with respect to food quality and safety [114]. Meanwhile, current quality assessment relies heavily on classical methodologies which can largely inform general consumer acceptability, but they lack the ability to provide detailed information on biochemical composition or metabolites that correspond to unique flavors of fresh PBPs.?

新鮮PBPs的營養(yǎng)價(jià)值和風(fēng)味特征主要由其生化組成決定。生化組成也是決定新鮮PBPs其他重要屬性（如保質(zhì)期、營養(yǎng)穩(wěn)定性和經(jīng)濟(jì)價(jià)值）的關(guān)鍵因素。隨著消費(fèi)者對(duì)食品質(zhì)量和安全性的期望不斷提高，需要新的工具來定義“質(zhì)量”，以包含更多關(guān)于食品生化組成的定量信息[114]。然而，目前的質(zhì)量評(píng)估主要依賴于傳統(tǒng)方法，這些方法雖然能在很大程度上反映一般消費(fèi)者的接受度，但缺乏提供關(guān)于新鮮PBPs獨(dú)特風(fēng)味對(duì)應(yīng)生化組成或代謝物的詳細(xì)信息的能力。

To this end, metabolomics can pave the way for decoding the composition and nature of flavor-associated metabolites in fresh PBPs, which can open avenues for further improvements of PBPs [115,116]. As such, the scope of metabolomics in this domain extends beyond just quality assessment for flavor-associated metabolites; it can be further utilized for (i) biomarker-detection related to food safety; (ii) development of new crops with better genetic traits; (iii) determination of food contaminants/adulterants; and (iv) new investigations on food bioactivities [117,118,119].

為此，代謝組學(xué)可以為解碼新鮮PBPs中風(fēng)味相關(guān)代謝物的組成和性質(zhì)鋪平道路，從而為PBPs的進(jìn)一步改進(jìn)開辟途徑[115,116]。因此，代謝組學(xué)在這一領(lǐng)域的范圍不僅限于風(fēng)味相關(guān)代謝物的質(zhì)量評(píng)估；它還可以進(jìn)一步用于（i）食品安全相關(guān)的生物標(biāo)志物檢測；（ii）開發(fā)具有更好遺傳性狀的新作物；（iii）確定食品污染物/摻假物；以及（iv）對(duì)食品生物活性的新研究[117,118,119]。這些應(yīng)用展示了代謝組學(xué)在提升PBPs質(zhì)量、安全性和市場價(jià)值方面的巨大潛力。

Although a distinct research area on food metabolomics has been established in the scientific community in relation to the application of metabolomics in food system processes [119,120] from farm to consumers, its widespread adoption comes with certain unparalleled challenges (as discussed in?Section 3.3). These challenges are often compounded by the nature of the food metabolome, which is complex and variable in nature as thousands of metabolites are present in fresh PBPs with varying polarities and chemistries [121]. Measuring and quantifying the metabolome that best represents the flavor profiles of fresh PBPs can pose analytical challenges as it may not be possible to detect all of them in a single analysis. To this end, utilizing multiple analytical techniques and approaches is often recommended in food metabolomics which can complement each other and provide a wider coverage [122,123].

盡管在科學(xué)界中已經(jīng)建立了與食品系統(tǒng)中從農(nóng)場到消費(fèi)者過程中代謝組學(xué)應(yīng)用相關(guān)的食品代謝組學(xué)這一獨(dú)特研究領(lǐng)域[119,120]，但其廣泛應(yīng)用仍面臨一些無與倫比的挑戰(zhàn)（如第3.3節(jié)所述）。這些挑戰(zhàn)往往因食品代謝組的復(fù)雜性和可變性而加劇，因?yàn)樾迈rPBPs中存在數(shù)以千計(jì)的代謝產(chǎn)物，它們具有不同的極性和化學(xué)性質(zhì)[121]。測量和量化最能代表新鮮PBPs風(fēng)味特征的代謝組可能會(huì)帶來分析挑戰(zhàn)，因?yàn)榭赡軣o法在一次分析中檢測到所有代謝物。為此，在食品代謝組學(xué)中通常推薦使用多種分析技術(shù)和方法，它們可以相互補(bǔ)充，提供更廣泛的覆蓋范圍[122,123]。

In addition to this, the food matrix of PBPs will also affect the detection and quantification of compounds that are present at very low concentrations in fresh PBPs or are present in bound forms and unstable forms (as discussed in?Section 3.3). Apart from these analytical and sampling-related hurdles, there are certain challenges at downstream data processing and integration with current quality assessment methodologies, and these will be discussed in the next section.

除了這一點(diǎn)外，PBPs的食品基質(zhì)也會(huì)影響在新鮮PBPs中以極低濃度存在或以結(jié)合形式和不穩(wěn)定形式存在的化合物的檢測和量化（如第3.3節(jié)所述）。除了這些分析和采樣相關(guān)的障礙外，在下游數(shù)據(jù)處理和與當(dāng)前質(zhì)量評(píng)估方法的集成方面也存在某些挑戰(zhàn)，這些將在下一節(jié)中討論。

Figure 2.?Framework for integrating metabolomics with current state-of-the-art technologies for the organoleptic evaluation of fresh PBPs. While physicochemical measurements are coarse-scale estimations, metabolomics and sensory-based tests serve as fine-scale estimations to achieve a holistic flavor profiling of fresh PBPs. Data integration platforms would play a crucial role to achieve seamless data stitching for meaningful insights.

圖2。將代謝組學(xué)與當(dāng)前最先進(jìn)的技術(shù)相結(jié)合的框架，用于新鮮PBPs的感官評(píng)估。雖然物理化學(xué)測量是粗略的估計(jì)，但代謝組學(xué)和基于感官的測試可以作為精細(xì)的估計(jì)，以實(shí)現(xiàn)新鮮PBPs的整體風(fēng)味分析。數(shù)據(jù)集成平臺(tái)將在實(shí)現(xiàn)無縫數(shù)據(jù)拼接以獲得有意義的見解方面發(fā)揮關(guān)鍵作用。

Integrating metabolomics with the current state-of-the-art technologies for quality assessment will require synchronized efforts at several points—all the way from data collection to data analyses. To maximize the potential of metabolomics approaches, data collation from various platforms along with careful data interpretation will undoubtedly play a key role. This can lead to several other technical challenges, depending upon the category of PBPs in question, and the nature of information required. Some of the technical challenges could be related to the availability of (i) the right instrumental platform or extraction protocols for metabolites of interest; (ii) reference databases and spectral libraries for matching interesting metabolic features in PBPs; and (iii) the complete metabolome or databank for the plant source in question.

將代謝組學(xué)與當(dāng)前最先進(jìn)的質(zhì)量評(píng)估技術(shù)相結(jié)合，需要在從數(shù)據(jù)收集到數(shù)據(jù)分析的各個(gè)方面同步努力。為了最大限度地發(fā)揮代謝組學(xué)方法的潛力，來自各個(gè)平臺(tái)的數(shù)據(jù)整理以及仔細(xì)的數(shù)據(jù)解釋無疑將發(fā)揮關(guān)鍵作用。這可能會(huì)導(dǎo)致其他一些技術(shù)挑戰(zhàn)，這取決于所討論的pbp的類別和所需信息的性質(zhì)。一些技術(shù)挑戰(zhàn)可能與(i)合適的儀器平臺(tái)或感興趣的代謝物提取方案的可用性有關(guān);(ii)參考數(shù)據(jù)庫和譜庫，用于匹配PBPs中有趣的代謝特征;(iii)有關(guān)植物來源的完整代謝組或數(shù)據(jù)庫。

Owing to the rapid developments in extraction and analytical methodologies, several options are available to analyze metabolites with varying chemistries, thereby increasing the global metabolite coverage. With these developments, the first technical hurdle can be conquered with few rounds of trials and optimization. However, the second and third technical challenges pose the greatest difficulty, not just for the agri-food domain, but also for other scientific domains, as a lack of reference databases and metabolome information makes it difficult to interpret the data and obtain meaningful insights. Lately, several curated databases have been made available in the plant domain specifically for diverse phytochemicals and bioactive metabolites to help the research community [127,128]. As the plant metabolome is highly diverse, with thousands of metabolites, it presents a laborious and technically challenging task to annotate every single metabolite. To overcome this challenge, efforts can be strategized towards the identification of candidate/marker metabolic members from different classes that can best represent the specific PBPs. This would eliminate the need to identify each metabolite and, at the same time, will serve as reference for rapid screening of PBPs based on presence of certain key metabolite classes. The choice and selection of such metabolite classes would depend upon the type of PBPs and their ultimate end-use. Monitoring glucosinolates (sulphur containing metabolites) in members from?Brassica?genus can be a classical example for this, as these metabolites are (i) unique to?Brassica?family members; (ii) associated with the flavor attributes of these plant types; and (iii) known for their human health benefits. Similarly, eucalyptols (cyclic ether, monoterpenoids) are unique to members of the?Myrtaceae?family and they are known for imparting a mint-like aroma and spicy taste notes. Other examples include PBPs from?Amaryllidaceae?that contain S-alk(en)yl-l-cysteine sulfoxides. Another way to approach this challenge will be to generate reference metabolic fingerprints of PBPs and utilize machine learning-based algorithms for pattern recognitions and high-throughput screening. This approach relies on the premise that if sampling, extraction and analytical conditions are kept the same, metabolic fingerprint from two PBPs samples of same type would be identical or similar to a large extent. However, this approach should be utilized as a fast screen and for more quantitative information, in-depth analyses are recommended. Apart from these technical challenges, a systematic method to integrate and collate the data from various platforms is warranted to maximize the potential of multi-platforms in the sensory evaluation of fresh PBPs.

由于提取和分析方法的迅速發(fā)展，有幾種選擇可用于分析具有不同化學(xué)性質(zhì)的代謝物，從而增加了全球代謝物的覆蓋率。有了這些發(fā)展，第一個(gè)技術(shù)障礙可以通過幾輪試驗(yàn)和優(yōu)化來克服。然而，第二和第三個(gè)技術(shù)挑戰(zhàn)帶來了最大的困難，不僅對(duì)農(nóng)業(yè)食品領(lǐng)域，而且對(duì)其他科學(xué)領(lǐng)域也是如此，因?yàn)槿狈⒖紨?shù)據(jù)庫和代謝組信息使得難以解釋數(shù)據(jù)并獲得有意義的見解。最近，在植物領(lǐng)域?qū)ｉT為各種植物化學(xué)物質(zhì)和生物活性代謝物建立了幾個(gè)數(shù)據(jù)庫，以幫助研究界[127,128]。由于植物代謝組具有高度多樣性，有數(shù)千種代謝物，因此對(duì)每一種代謝物進(jìn)行注釋是一項(xiàng)艱苦且具有技術(shù)挑戰(zhàn)性的任務(wù)。為了克服這一挑戰(zhàn)，可以從不同的類別中確定最能代表特定PBPs的候選/標(biāo)記代謝成員。這將消除識(shí)別每種代謝物的需要，同時(shí)，將作為基于某些關(guān)鍵代謝物類別的PBPs快速篩選的參考。這些代謝物類別的選擇將取決于PBPs的類型及其最終用途。監(jiān)測來自蕓苔屬成員的硫代葡萄糖苷(含硫代謝物)可能是一個(gè)典型的例子，因?yàn)檫@些代謝物是(i)蕓苔屬成員所特有的;(ii)與這些植物類型的風(fēng)味屬性有關(guān);(三)以對(duì)人體健康有益而聞名。類似地，桉樹精油(環(huán)醚，單萜類)是桃金娘科成員所特有的，它們以賦予薄荷般的香氣和辛辣的味道而聞名。其他的例子包括來自Amaryllidaceae的PBPs，它含有S-alk(en)yl-l-半胱氨酸亞砜。解決這一挑戰(zhàn)的另一種方法是生成PBPs的參考代謝指紋，并利用基于機(jī)器學(xué)習(xí)的算法進(jìn)行模式識(shí)別和高通量篩選。該方法的前提是，在取樣、提取和分析條件相同的情況下，同一類型的兩個(gè)PBPs樣品的代謝指紋在很大程度上是相同或相似的。但是，這種方法應(yīng)該用作快速篩選，并建議進(jìn)行深入分析以獲得更多定量信息。除了這些技術(shù)挑戰(zhàn)之外，需要一種系統(tǒng)的方法來整合和整理來自不同平臺(tái)的數(shù)據(jù)，以最大限度地發(fā)揮多平臺(tái)在新鮮PBPs感官評(píng)估中的潛力。

A significant improvement has been achieved in recent years in data integration and chemometrics pipelines, making it easier to obtain integrated biological outputs from different platforms. In recent years, numerous tools have been developed, written in most used programming languages such as Python, R, and Matlab??to aid in metabolomics data curation and management [127]. Additionally, several platforms are being made available for sharing scripts and workflows through open-access repositories (Github, StackOverflow). Interactive and intuitive data integration workflows are being developed that have adopted artificial intelligence (AI) and machine learning (ML) approaches [129,130]. Data integration platforms that combine e-noses and e-tongues with high resolution MS and analytical instrumentation could be a way to logically bridge current gaps between human-based sensory tests and metabolic estimations. Although these artificial sensory techniques cannot integrate taste and smell as can be done by the human sensory system, they can generate reliably consistent data in a high-throughput format. With the availability of the requisite computational power, it is possible to integrate such modular information from these artificial sensors to obtain meaningful insights [131,132].

近年來，在數(shù)據(jù)集成和化學(xué)計(jì)量學(xué)管道方面取得了重大進(jìn)展，使得從不同平臺(tái)獲得綜合生物輸出變得更加容易。近年來，已經(jīng)開發(fā)了許多工具，用最常用的編程語言(如Python、R和Matlab?)編寫，以幫助代謝組學(xué)數(shù)據(jù)的管理和管理[127]。此外，有幾個(gè)平臺(tái)可以通過開放訪問存儲(chǔ)庫(Github, StackOverflow)共享腳本和工作流。采用人工智能(AI)和機(jī)器學(xué)習(xí)(ML)方法的交互式和直觀的數(shù)據(jù)集成工作流程正在開發(fā)[129,130]。將電子鼻和電子舌與高分辨率質(zhì)譜和分析儀器相結(jié)合的數(shù)據(jù)集成平臺(tái)可能是一種從邏輯上彌合目前基于人類的感官測試和代謝估計(jì)之間差距的方法。雖然這些人工感官技術(shù)不能像人類感官系統(tǒng)那樣整合味覺和嗅覺，但它們可以以高通量格式生成可靠一致的數(shù)據(jù)。有了必要的計(jì)算能力，就有可能整合這些人工傳感器的模塊化信息，以獲得有意義的見解[131,132]。

This will be particularly resourceful for innovations and new product developments in this domain as we continue to witness intense reformation and diversification of food palates globally. In addition, integrating these platforms with trained artificial intelligence can further uplift them to smart sensing platforms that can, to an extent, also predict emerging food safety threats in terms of adulterants and/or pathogens. To make this a real scenario, coordinated efforts and synchronized response will be required from several stakeholders working in this evolving domain.

隨著我們繼續(xù)見證全球食品口味的激烈改革和多樣化，這將為該領(lǐng)域的創(chuàng)新和新產(chǎn)品開發(fā)提供特別豐富的資源。此外，將這些平臺(tái)與訓(xùn)練有素的人工智能相結(jié)合，可以進(jìn)一步將其提升為智能傳感平臺(tái)，在某種程度上，還可以預(yù)測摻假和/或病原體方面出現(xiàn)的食品安全威脅。為了使這成為一個(gè)真實(shí)的場景，將需要在這個(gè)不斷發(fā)展的領(lǐng)域中工作的幾個(gè)利益相關(guān)者協(xié)調(diào)努力和同步響應(yīng)。

5. Conclusions

5. 結(jié)論

To conclude, utilizing metabolomics for evaluating flavor-associated metabolites in PBPs would likely become a necessity in coming years and it will see multiple applications from product authenticity, quality assessment, new product development and enhanced food safety.

利用代謝組學(xué)來評(píng)估植物基產(chǎn)品（PBPs）中與風(fēng)味相關(guān)的代謝物，在未來幾年內(nèi)很可能會(huì)成為一種必然需求，并且將在產(chǎn)品真實(shí)性驗(yàn)證、質(zhì)量評(píng)估、新產(chǎn)品開發(fā)和增強(qiáng)的食品安全等多個(gè)方面展現(xiàn)出廣泛的應(yīng)用。

原文鏈接：

Pavagadhi S, Swarup S. Metabolomics for Evaluating Flavor-Associated Metabolites in Plant-Based Products.?Metabolites. 2020; 10(5):197. https://doi.org/10.3390/metabo10050197