Keywords: SCN: Suprachiasmatic Nuclei 2D-DIGE: 2-Dimensional-DIfference Gel Electrophoresis MS: Mass Spectrometry LC: Liquid Chromatography HPLC: High Performance Liquid Chromatography SILAC: Stable-Isotope Labelling by Amino acids in Cell culture circadian clock, proteomics, post-translational modifications, signaling

The circadian clock is an endogenous molecular timekeeping system that allows organisms to adjust their physiology and behavior to the time of day in an anticipatory fashion. In different organisms, the circadian clock coordinates physiology and metabolism through regulation of gene expression at the transcriptional and post-transcriptional levels. Until now, circadian gene expression studies have mostly focused primarily on transcriptomics approaches. This type of analyses revealed that most of protein-encoding genes show circadian expression in a tissue specific manner. During the last three decades, a long way has been travelled since the pioneering work on dinoflagellates and new advances in mass spectrometry offered new perspectives in the characterization of the circadian dynamics of the proteome. Altogether, these efforts highlighted that rhythmic protein oscillation is driven equally by gene transcription, post-transcriptional and post-translational regulations. The determination of the role of the circadian clock in these two levels of regulation appears to be the next major challenge in the field.

Introduction

The rotation of the earth around its own axis creates daily environmental changes such as fluctuation of light and temperature. To anticipate these variations, organisms developed a self-sustained timekeeping system, called the circadian clock (a word coined from Latin for circa and diem meaning "about a day"). This circadian clock controls metabolism and physiology through the coordination of behavioral and biochemical mechanisms including sleep, feeding rhythms, hormone release and digestive tract activity [START_REF] Reinke | Crosstalk between metabolism and circadian clocks[END_REF]. Because of the central role of the circadian clock in physiology, circadian dysfunction is associated with a broad range of pathologies including obesity, type 2 diabetes, non-alcoholic fatty liver disease (NAFLD) and neurological disorders [START_REF] Leng | Association between circadian rhythms and neurodegenerative diseases[END_REF][START_REF] Logan | Rhythms of life: circadian disruption and brain disorders across the lifespan[END_REF][START_REF] Mukherji | The Circadian Clock and Liver Function in Health and Disease[END_REF][START_REF] Stenvers | Circadian clocks and insulin resistance[END_REF][START_REF] Weger | At the Intersection of Microbiota and Circadian Clock: Are Sexual Dimorphism and Growth Hormones the Missing Link to Pathology?[END_REF]. It therefore appears of high importance to understand the mechanisms that are involved in the regulation of physiology by the circadian clock and the consequences of their disruption. The circadian clock system in mammals is organized in a hierarchical manner, with a central "master" clock located in the bilateral SCN of the hypothalamus. The SCN receive light input via photosensitive melanopsincontaining retinal ganglion cells and communicate with "slave" peripheral oscillators via humoral (e.g. glucocorticoids), neuronal (e.g. innervation by the autonomous nervous system) or systemic (e.g. timing of food intake or temperature changes) signals [START_REF] Hastings | Generation of circadian rhythms in the suprachiasmatic nucleus[END_REF] (Fig. 1).

The molecular circadian clock

Cell-autonomous circadian rhythms rely on a network of interlocked transcriptional-translational negative feedback loops. As a basic principle, the activation of a gene encoding a transcriptional repressor results in its later repression by its own protein product, whose instability allows the cycle to reinitiate. The activating loop is composed by a dimer of basic helix-loop-helix-Per-Arnt-Sim domain (bHLH-PAS) transcription factors composed of Brain and Muscle Arnt-Like protein-1 (BMAL1) and its partners Circadian Locomotor Output Cycles Kaput (CLOCK) and Neuronal PAS domain protein 2 (NPAS2). The first negative feedback loop includes Period (PER) and Cryptochome (CRY) whose expression is, in part, regulated by BMAL1 via binding to specific DNA elements called E-box-related motifs in their promoters. These proteins assemble into large macromolecular complexes that translocate into the nucleus and inhibit BMAL1 transcriptional activity. In parallel, a second feedback loop, sometimes called stabilizing loop, involves the nuclear receptors Retinoic acid-related Orphan Receptors (RORα, β and γ) and Reverse Erythroblastosis virus (REV-ERBα and β or NR1D1 and NR1D2), that respectively activate and repress Bmal1 expression by binding to response elements (RORE) present in the Bmal1 promoter. In addition, the circadian clock controls the rhythmic expression of the PARbZip transcription factors albumin D box-Binding Protein (DBP), Hepatic Leukemia Factor (HLF) and Thyrotroph Embryonic Factor (TEF), as well as their repressive and antiphasic counterpart E4 promoter-binding protein 4 (E4BP4) (also known as Nuclear factor interleukin 3 regulated (NFIL3)).

These factors binds to D-box elements in the promoter of their target genes and play an important role in the regulation of clock output genes involved in metabolism and physiology [START_REF] Gachon | Physiological function of PARbZip circadian clock-controlled transcription factors[END_REF]. Nevertheless, the simultaneous presence of BMAL1, REV-ERB/ROR and PARbZip binding sites in most of clock genes suggests a more complex regulation involving the three loops and the PARbZip factors simultaneously [START_REF] Bugge | Rev-erbα and Rev-erbβ coordinately protect the circadian clock and normal metabolic function[END_REF][START_REF] Cho | Regulation of circadian behaviour and metabolism by REV-ERB-α and REV-ERB-β[END_REF][START_REF] Koike | Transcriptional Architecture and Chromatin Landscape of the Core Circadian Clock in Mammals[END_REF][START_REF] Fang | Circadian Enhancers Coordinate Multiple Phases of Rhythmic Gene Transcription In Vivo[END_REF][START_REF] Yoshitane | Functional D-box sequences reset the circadian clock and drive mRNA rhythms[END_REF]. In addition, their combination is required for the generation of multiple phases of coherent rhythmic gene expression allowing the temporal transcriptional regulation of thousands of clock-controlled genes [START_REF] Takahashi | Transcriptional architecture of the mammalian circadian clock[END_REF] (Fig. 1).

Post-translational regulation in the regulation of the circadian clock

In response to daily changes in physiology, metabolism-controlled signaling pathways maintain homeostasis through feedback on the circadian clock [START_REF] Reinke | Crosstalk between metabolism and circadian clocks[END_REF]. This additional level of regulation involves the post-translational modifications of circadian clock proteins such as phosphorylation, ubiquitination, acetylation, O-GlcNacylation and SUMOylation. For example, the NAD + -dependent deacetylase SIRT1 interacts with CLOCK/BMAL1 and mediates BMAL1 deacetylation to modulate its transcriptional activity [START_REF] Nakahata | The NAD + -Dependent Deacetylase SIRT1 Modulates CLOCK-Mediated Chromatin Remodeling and Circadian Control[END_REF]. SIRT1 also promotes PER2 degradation via its deacetylation [START_REF] Asher | SIRT1 Regulates Circadian Clock Gene Expression through PER2 Deacetylation[END_REF]. CLOCK and BMAL1 are also regulated by ubiquination and SUMOylation [START_REF] Cardone | Circadian Clock Control by SUMOylation of BMAL1[END_REF][START_REF] Lee | Dual Modification of BMAL1 by SUMO2/3 and Ubiquitin Promotes Circadian Activation of the CLOCK/BMAL1 Complex[END_REF][START_REF] Li | O-GlcNAc Signaling Entrains the Circadian Clock by Inhibiting BMAL1/CLOCK Ubiquitination[END_REF].

Moreover, most of the core clock proteins are phosphoproteins and phosphorylation/dephosphorylation events play a key role in the regulation and fine-tuning of circadian rhythms. For instance, the phosphorylation of CLOCK and BMAL1 by insulin-regulated AKT kinase controls their nuclear accumulation and transcriptional activity [START_REF] Dang | Insulin post-transcriptionally modulates Bmal1 protein to affect the hepatic circadian clock[END_REF][START_REF] Luciano | CLOCK phosphorylation by AKT regulates its nuclear accumulation and circadian gene expression in peripheral tissues[END_REF]. Another example is the energy sensor 5'-AMP-activated protein kinase (AMPK) which directly phosphorylates CRY1 [START_REF] Lamia | AMPK Regulates the Circadian Clock by Cryptochrome Phosphorylation and Degradation[END_REF] and indirectly PER2 [START_REF] Um | Activation of 5′-AMP-activated Kinase with Diabetes Drug Metformin Induces Casein Kinase Iϵ (CKIϵ)-dependent Degradation of Clock Protein mPer2[END_REF]. In this way, AMPK promotes the degradation of the negative feedback loop components. PER2 degradation has also been shown to be regulated via coordinated phosphorylation by Casein Kinase 2 (CK2) and CK1ε [START_REF] Tsuchiya | Involvement of the Protein Kinase CK2 in the Regulation of Mammalian Circadian Rhythms[END_REF]. More details about the role of posttranscriptional and post-translational regulations in the circadian clock can be found in distinct reviews in the same issue.

Development of proteomics techniques: influence on circadian biology

During almost three decades, because of the amazing progress in transcriptomic techniques and the limits of proteomics technologies, most of the large-scale circadian gene expression studies focused on mRNA. These studies showed that the proportion of rhythmically expressed genes is estimated to span from 6% to 50% [START_REF] Koike | Transcriptional Architecture and Chromatin Landscape of the Core Circadian Clock in Mammals[END_REF][START_REF] Atger | Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver[END_REF][START_REF] Hughes | Harmonics of Circadian Gene Transcription in Mammals[END_REF][START_REF] Hughes | Deep sequencing the circadian and diurnal transcriptome of Drosophila brain[END_REF][START_REF] Panda | Coordinated Transcription of Key Pathways in the Mouse by the Circadian Clock[END_REF][START_REF] Storch | Extensive and divergent circadian gene expression in liver and heart[END_REF][START_REF] Ueda | A transcription factor response element for gene expression during circadian night[END_REF][START_REF] Yeung | Transcription factor activity rhythms and tissue-specific chromatin interactions explain circadian gene expression across organs[END_REF][START_REF] Zhang | A circadian gene expression atlas in mammals: Implications for biology and medicine[END_REF]. The different model organisms, tissues or cell types used in these different studies explained this high variability, as well asthe numerous statistical methods and cut-offs values used for the analysis of the data.

Altogether, it is estimated that around half of the protein coding genes are oscillating in at least one tissue in mouse, a statement confirmed by a recent study [START_REF] Zhang | A circadian gene expression atlas in mammals: Implications for biology and medicine[END_REF]. Both feeding rhythms and the circadian clock contribute to the rhythmic regulation of gene expression [START_REF] Atger | Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver[END_REF][START_REF] Greenwell | Rhythmic Food Intake Drives Rhythmic Gene Expression More Potently than the Hepatic Circadian Clock in Mice[END_REF]. Nevertheless, until recently, the knowledge about rhythmic regulation at the protein level remained scarce.

The pioneering circadian proteomic studies were based on 2D-DIGE followed by MS. This method separates proteins first by isoelectric focusing and then by the molecular mass. 2D-DIGE can enable the detection of 1000 to 2000 protein spots with high sensitivity but suffers from high technical variability. Albeit its limitations, 2D electrophoresis was nevertheless successful in describing the circadian translational control of protein synthesis in the luminescent unicellular dinoflagellates Gonyaulax [START_REF] Milos | Circadian control over synthesis of many Gonyaulax proteins is at a translational level[END_REF] and Lingulodinium polyedrum [START_REF] Akimoto | Biological rhythmicity in expressed proteins of the marine dinoflagellate Lingulodinium polyedrum demonstrated by chronological proteomics[END_REF], as well as other studies, including pioneering works from the Michael Hastings' laboratory [START_REF] Deery | Proteomic Analysis Reveals the Role of Synaptic Vesicle Cycling in Sustaining the Suprachiasmatic Circadian Clock[END_REF][START_REF] Reddy | Circadian Orchestration of the Hepatic Proteome[END_REF]. The more recent advances in shotgun proteomics using LC or HPLC allowed large-scale and more accurate protein identification and quantification. As a result, the development of high-throughput proteomics technologies provided a more extensive picture of the circadian and diurnally rhythmic proteome. These more comprehensive datasets combined with appropriate comparison with rhythmic transcriptomics data collected in similar conditions allowed the identification of new mechanisms underlying the regulation of rhythmic protein abundance that is dependent of protein synthesis, degradation and transport. The development of in vivo SILAC offered the most accurate technique particularly suitable for assessing low changes in amplitude [START_REF] Krüger | SILAC Mouse for Quantitative Proteomics Uncovers Kindlin-3 as an Essential Factor for Red Blood Cell Function[END_REF]. This technique allowed the characterization of the rhythmic proteome of mouse liver and SCN with an unprecedented coverage [START_REF] Chiang | The Proteomic Landscape of the Suprachiasmatic Nucleus Clock Reveals Large-Scale Coordination of Key Biological Processes[END_REF][START_REF] Mauvoisin | Circadian clock-dependent andindependent rhythmic proteomes implement distinct diurnal functions in mouse liver[END_REF][START_REF] Robles | In-Vivo Quantitative Proteomics Reveals a Key Contribution of Post-Transcriptional Mechanisms to the Circadian Regulation of Liver Metabolism[END_REF]. Other post-extraction protein labeling methods like TMT and iTRAQ have been also successfully used, as well as label free quantitative proteomics [START_REF] Ahmad | A perspective on proteomics in cell biology[END_REF] (Fig 2 ).

A retrospective of circadian proteomics in the central nervous system

Because of the importance of the SCN in the central regulation of circadian physiology, many efforts have been made to characterize the regulation of protein fluctuations in that tissue, as well as the changes caused by light. A first study examined the effect of light stimulation on the mouse SCN proteome using 2D-DIGE [START_REF] Fahrenkrug | Altered calmodulin response to light in the suprachiasmatic nucleus of PAC1 receptor knockout mice revealed by proteomic analysis[END_REF] (Fig. 3). Within the five protein spots showing a decreased expression after light stimulation, the authors identified Calmodulin, from which transcript expression levels were unaffected, suggesting a posttranscriptional regulation of this protein. The list of light-regulated SCN proteins was later extended to 387 [START_REF] Tian | Uncovering the Proteome Response of the Master Circadian Clock to Light Using an AutoProteome System[END_REF]. A deeper exploration of the mouse SCN rhythmic proteome was published in 2009 [START_REF] Deery | Proteomic Analysis Reveals the Role of Synaptic Vesicle Cycling in Sustaining the Suprachiasmatic Circadian Clock[END_REF]. Among the 871 protein spots consistently quantified across four time points, 115 (13%) displayed significant rhythmicity, the majority (72%) of them being encoded by non-rhythmic mRNA. The rhythmic SCN proteome was highly enriched in proteins implicated in vesicle trafficking and recycling, a process demonstrated by the authors to be important for circadian gene expression within the SCN [START_REF] Deery | Proteomic Analysis Reveals the Role of Synaptic Vesicle Cycling in Sustaining the Suprachiasmatic Circadian Clock[END_REF]. A recent SILAC-based high-throughput quantitative proteomic approach moved the characterization of the SCN rhythmic proteome to another dimension, enabling the quantification of 3275 proteins, 421 (one more time 13%) of them displaying a timeof-day dependent profile, with enrichment for proteins involved in mitochondrial oxidative phosphorylation [START_REF] Chiang | The Proteomic Landscape of the Suprachiasmatic Nucleus Clock Reveals Large-Scale Coordination of Key Biological Processes[END_REF]. As in previous studies, the majority (60%) of these rhythmic proteins were not encoded by rhythmic mRNAs. Additional analyses suggested the implication of miRNA (in particular miR-133a) in the regulation of the SCN proteome rhythmicity [START_REF] Chiang | The Proteomic Landscape of the Suprachiasmatic Nucleus Clock Reveals Large-Scale Coordination of Key Biological Processes[END_REF]. Of interest, another SILAC-based proteomic experiment performed on the SCN highlighted the implication of miR-132 and miR-122 in seasonal adaptation [START_REF] Mendoza-Viveros | miR-132/212 Modulates Seasonal Adaptation and Dendritic Morphology of the Central Circadian Clock[END_REF]. In addition to these studies, important efforts led to the characterization of peptides rhythmically expressed and released by the rat SCN [START_REF] Hatcher | Mass spectrometrybased discovery of circadian peptides[END_REF][START_REF] Lee | Endogenous Peptide Discovery of the Rat Circadian Clock: A FOCUSED STUDY OF THE SUPRACHIASMATIC NUCLEUS BY ULTRAHIGH PERFORMANCE TANDEM MASS SPECTROMETRY[END_REF][START_REF] Lee | Quantitative Peptidomics for Discovery of Circadian-Related Peptides from the Rat Suprachiasmatic Nucleus[END_REF]. While several of these secreted peptides have been shown to play an important role in the synchronization of central and peripheral clocks [START_REF] Hastings | Generation of circadian rhythms in the suprachiasmatic nucleus[END_REF], the circadian function of many of them remains unknown.

Because of its direct link with the SCN, the rhythmic proteome of the retina also attracted the interest of chronobiologists. Accordingly, a 2D-DIGE-based study characterized 415 retinal proteins, 11 of them showing a circadian profile [START_REF] Tsuji | Circadian proteomics of the mouse retina[END_REF]. These proteins were involved in vesicular transport, calcium-binding, protein degradation, RNA-binding and protein folding suggesting the implication of the circadian clock in neurotransmitter release and protein transport. More recently, the 2D-DIGE diurnal retinal proteome in wildtype (WT) and Crx knockout (KO) mice, which lack rods and cones, has been described [START_REF] Møller | Diurnal expression of proteins in the retina of the blind cone-rod homeobox (Crx -/-) mouse and the 129/Sv mouse: a proteomic study[END_REF]. Despite the deficiency in key proteins involved in phototransduction, Crx KO retina retained diurnal protein expression in enzymes involved in glucose metabolism, mitochondrial activity and in anti-oxidative functions. This rhythmic differential expression is likely generated by direct light input to the retina or by neighboring cells that kept a functional circadian clock. This observation suggests that the circadian clock is not present only in rods and cones but also in other cells of the retina [START_REF] Møller | Diurnal expression of proteins in the retina of the blind cone-rod homeobox (Crx -/-) mouse and the 129/Sv mouse: a proteomic study[END_REF].

A LC-MS approach was used to characterize the circadian murine hippocampal proteome and phosphoproteome [START_REF] Chiang | Phosphoproteome Profiling Reveals Circadian Clock Regulation of Posttranslational Modifications in the Murine Hippocampus[END_REF]. Among the detected phospho-sites, 5% oscillated in a circadian manner, with an enrichment at the end of the subjective day (CT10). Like in the SCN, most of these proteins were involved in synaptic function and cytoskeletal organization, which pointed out the role of the circadian clock in mediating anticipatory structural changes occurring in the hippocampus shortly after awakening [START_REF] Chiang | Phosphoproteome Profiling Reveals Circadian Clock Regulation of Posttranslational Modifications in the Murine Hippocampus[END_REF]. Elsewhere, a 2D-DIGE study of the rat superficial pineal gland showed significant differences in 60 protein spots between two time points: ZT6 and ZT18 [START_REF] Møller | Proteomic analysis of day-night variations in protein levels in the rat pineal gland[END_REF]. More recently, a similar approach in mouse cerebellum also revealed an important rhythmicity of proteins involved in mitochondrial metabolism and cytoskeletal organization [START_REF] Plumel | Circadian Analysis of the Mouse Cerebellum Proteome[END_REF].

In non-vertebrate models, a recent circadian study using HPLC-MS proteomics helped identifying new clock modifiers. Indeed, the description of the rhythmic proteome of the Drosophila head highlighted α-Catenin as a potential new player in the regulation of circadian rhythms [START_REF] Du | Diurnal protein oscillation profiles in Drosophila head[END_REF]. Moreover, targeted proteomics analysis in the antenna of Anopheles gambiae characterized the rhythmic expression of olfactory receptors in these sensatory organs that are associated with the rhythmic olfactory sensitivity of these insects [START_REF] Rund | Daily rhythms in antennal protein and olfactory sensitivity in the malaria mosquito Anopheles gambiae[END_REF].

Circadian proteomics in peripheral tissues

Circadian proteomics in peripheral organs mainly focused on mouse liver and was also spurred by the refinement of the technology, switching from 2D-DIGE to large-scale quantitative proteomics approaches.

The first breakthrough came from a 2D-DIGE study that allowed the quantification of 642 protein spots, of which 60 (9%) showed significant rhythmicity [START_REF] Reddy | Circadian Orchestration of the Hepatic Proteome[END_REF]. As observed in the SCN [START_REF] Deery | Proteomic Analysis Reveals the Role of Synaptic Vesicle Cycling in Sustaining the Suprachiasmatic Circadian Clock[END_REF], only a small fraction (43%) of rhythmic proteins are encoded by rhythmic mRNA, highlighting the importance of post-transcriptional regulation [START_REF] Reddy | Circadian Orchestration of the Hepatic Proteome[END_REF]. Following this pioneering work, in vivo SILAC high-throughput proteomics was used to characterize the diurnal mouse liver proteome at a larger scale. Two paralleled studies showed that among the 3000 quantified proteins, 6% presented a rhythmic accumulation pattern [START_REF] Mauvoisin | Circadian clock-dependent andindependent rhythmic proteomes implement distinct diurnal functions in mouse liver[END_REF][START_REF] Robles | In-Vivo Quantitative Proteomics Reveals a Key Contribution of Post-Transcriptional Mechanisms to the Circadian Regulation of Liver Metabolism[END_REF]. These rhythmic proteins preferentially accumulated in the middle of the light and dark phases. Again, only a part of the rhythmic proteome (50% in [START_REF] Mauvoisin | Circadian clock-dependent andindependent rhythmic proteomes implement distinct diurnal functions in mouse liver[END_REF] and 80% in [START_REF] Robles | In-Vivo Quantitative Proteomics Reveals a Key Contribution of Post-Transcriptional Mechanisms to the Circadian Regulation of Liver Metabolism[END_REF]) was encoded by rhythmic mRNA. Among these rhythmic proteins, those peaking during the light phase are mostly associated with lipid metabolism and fatty acid oxidation, whereas rhythmic proteins peaking during the dark phase were involved in glucose metabolism and liver detoxification. This rhythmic landscape illustrates the metabolic flexibility of the liver, being able to switch from fat to carbohydrates as carbon fuels between the light (fasting period) and dark phase (feeding period) transition. This metabolic flexibility is driven by the circadian clock since the rhythmicity is abolished in clock-deficient animals [START_REF] Mauvoisin | Circadian clock-dependent andindependent rhythmic proteomes implement distinct diurnal functions in mouse liver[END_REF]. In addition, metabolic flexibility is also effective in other peripheral organs like the heart. Indeed, the cardiac proteome of cardiomyocytes clock-mutant mice displays altered diurnal protein expression profiles of key metabolic enzymes [START_REF] Podobed | The Day/Night Proteome in the Murine Heart[END_REF].

In contrast, a second group of rhythmic proteins encoded by non-rhythmic mRNA is enriched in secreted proteins whose rhythms are highly correlated in clock-deficient animals [START_REF] Mauvoisin | Circadian clock-dependent andindependent rhythmic proteomes implement distinct diurnal functions in mouse liver[END_REF]. Additional experiments showed that feeding rhythms likely pace liver protein secretion, confirming the previously observed rhythmicity of circulating proteins with no connection with the corresponding transcript expression [START_REF] Martino | Diurnal protein expression in blood revealed by high throughput mass spectrometry proteomics and implications for translational medicine and body time of day[END_REF][START_REF] Scheving | Circadian fluctuation in plasma proteins of the rat[END_REF]. Of note, the impact of feeding/sleeping rhythms on rhythmic plasma proteins has also been shown in human [START_REF] Depner | Mistimed food intake and sleep alters 24-hour timeof-day patterns of the human plasma proteome[END_REF]. These observations implicate that around half of the rhythmic proteome is regulated at the post-transcriptional level.

In plants, a first iTRAQ-MS-based experiment in Arabidopsis leaves with only two time points showed that the correlation of mRNA and protein levels is limited. Indeed, most of the rhythmic transcripts encoded for non-rhythmic proteins [START_REF] Baerenfaller | Systems-based analysis of Arabidopsis leaf growth reveals adaptation to water deficit[END_REF]. A larger-scale LC-MS-based study in seeds corroborated this observation showing that only 35% of the rhythmic proteome, enriched for proteins involved in photosynthesis and chaperone activity, was encoded by rhythmic mRNA [START_REF] Choudhary | Circadian Profiling of the Arabidopsis Proteome Using 2D-DIGE[END_REF]. The significance of the circadian clock [START_REF] Graf | Parallel analysis of Arabidopsis circadian clock mutants reveals different scales of transcriptome and proteome regulation[END_REF]and post-transcriptional regulation, in particular mRNA translation [START_REF] Seaton | Photoperiodic control of the Arabidopsis proteome reveals a translational coincidence mechanism[END_REF], was later confirmed in the generation of the circadian proteome [START_REF] Graf | Parallel analysis of Arabidopsis circadian clock mutants reveals different scales of transcriptome and proteome regulation[END_REF][START_REF] Seaton | Photoperiodic control of the Arabidopsis proteome reveals a translational coincidence mechanism[END_REF]. More recently, interaction proteomics was used to characterize the circadian clock regulator GIGANTEA interactome, providing more insights into the importance of post-transcriptional regulation in the regulation of plant circadian clock [START_REF] Krahmer | Time-resolved interaction proteomics of the GIGANTEA protein under diurnal cycles in Arabidopsis[END_REF]. The key role of post-transcriptional regulation, notably mRNA translation, in driving proteome rhythmicity was also confirmed in Neurospora [START_REF] Hurley | Circadian Proteomic Analysis Uncovers Mechanisms of Post-Transcriptional Regulation in Metabolic Pathways[END_REF]. Finally, rhythmic proteomes of whole insect were characterized by 2D-DIGE in Drosophila [START_REF] Subramanian | Temporal regulation of proteome profile in the fruit fly, Drosophila melanogaster[END_REF] and by HPLC-MS in Anopheles Gambia [START_REF] Imrie | Genome annotation improvements from cross-phyla proteogenomics and time-of-day differences in malaria mosquito proteins using untargeted quantitative proteomics[END_REF] emphasizing the role of circadian rhythm in metabolism and muscular activity in insects.

Circadian proteomics at the sub-cellular level

Total protein extracts from plant or animal tissues constitute extremely complex protein mixtures. This high complexity makes difficult to achieve the detection and the quantification of proteins expressed at low level.

It is the case for example for transcription factors, including the core clock proteins, and other organellespecific proteins. A strategy to circumvent this problem and enhance mass spectrometry resolution is to perform organelle-specific quantitative proteomics. This approach was successfully applied to quantify the rhythmic mitochondrial proteome using LC-MS label-free quantitative proteomics. 38% of the mitochondrial proteins accumulated in a rhythmic fashion, most of them peaking during the early light phase [START_REF] Neufeld-Cohen | Circadian control of oscillations in mitochondrial rate-limiting enzymes and nutrient utilization by PERIOD proteins[END_REF]. 86% of these rhythmic mitochondrial proteins are encoded by rhythmic mRNA, however with very low phase correlation between proteins and transcripts. Among the mechanisms that could explain these rhythms, temporal regulation of mitochondrial protein transport via the TIM/TOM complex was suggested. This work highlighted the role of post-translational regulation orchestrated by the circadian clock and feeding rhythms in the regulation of key mitochondrial functions such as fatty acid oxidation important for metabolic flexibility [START_REF] Neufeld-Cohen | Circadian control of oscillations in mitochondrial rate-limiting enzymes and nutrient utilization by PERIOD proteins[END_REF]. Interestingly, similar observation were made with the 2D-DIGE analysis of mitochondria extracted from Arabidopsis shoots [START_REF] Lee | Diurnal Changes in Mitochondrial Function Reveal Daily Optimization of Light and Dark Respiratory Metabolism in Arabidopsis[END_REF]. This diurnal metabolic flexibility is also allowed by circadian clock-orchestrated mitochondrial dynamics that might contribute to the rhythmicity of the mitochondrial proteome [START_REF] Jacobi | Hepatic Bmal1 Regulates Rhythmic Mitochondrial Dynamics and Promotes Metabolic Fitness[END_REF][START_REF] Schmitt | Circadian Control of DRP1 Activity Regulates Mitochondrial Dynamics and Bioenergetics[END_REF].

An organelle purification approach was also used to characterize the nuclear proteome. Among the 4000 nuclear proteins quantified in mouse liver nuclei, more than 500 were highly rhythmic, including all the coreclock components and the clock-controlled transcription factors [START_REF] Wang | Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver[END_REF]. Of note, these values were very similar to those obtained later by another group that used absolute quantification to monitor the temporal dynamics of circadian clock proteins [START_REF] Narumi | Mass spectrometrybased absolute quantification reveals rhythmic variation of mouse circadian clock proteins[END_REF], confirming the robustness of the in vivo SILAC LC-MS method. These rhythmic nuclear proteins were mainly controlled at the post-transcriptional level, a vast majority of them encoded by non-rhythmic mRNAs. Rhythmic nuclear transport of proteins complexes appeared to be the main regulator of the rhythmic nuclear proteome. These rhythmic proteins were involved in ribosome biogenesis and assembly [START_REF] Jouffe | The Circadian Clock Coordinates Ribosome Biogenesis[END_REF][START_REF] Sinturel | Diurnal Oscillations in Liver Mass and Cell Size Accompany Ribosome Assembly Cycles[END_REF], as well as DNA repair [START_REF] Sancar | Circadian clock control of the cellular response to DNA damage[END_REF] and transcriptional regulation. The quantification of the rhythmic nuclear accumulation of around 200 transcription factors and transcriptional co-regulators provided new insights into the diurnal regulation of transcription and its regulation by the circadian clock and feeding rhythms [START_REF] Wang | Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver[END_REF]. Moreover, these results were recently corroborated and extended by a similar label free LC-MS nuclear proteomic study associated with a transcription factor DNA-binding activity-based proteomic analysis [START_REF] Wang | A proteomics landscape of circadian clock in mouse liver[END_REF]. A recent report assessing the rhythmic forebrain synaptic proteome by label free LC-MS confirmed the importance of post-transcriptional regulation. The rhythmic synaptic transcriptome and proteome rely on a functional circadian clock that post-transcriptionally control the localization of mRNA and protein [START_REF] Noya | The forebrain synaptic transcriptome is organized by clocks but its proteome is driven by sleep[END_REF].

Nevertheless, 22% of the rhythmic proteins are encoded by non-rhythmic mRNA. Surprisingly, while sleep deprivation has limited impact on the rhythmic mRNA accumulation, it completely disrupts the rhythmic proteome, showing the importance of the environment (e.g. ZT and sleep) in its regulation [START_REF] Noya | The forebrain synaptic transcriptome is organized by clocks but its proteome is driven by sleep[END_REF].

Rhythmic proteome at the cell-autonomous level

To date, most proteome dynamic analyses have been performed in animal tissues. However, the rhythmic proteome has also been studied at the cellular level. It is, of course, the case for unicellular models like green algae. A first 2D-DIGE study in Chlamydomonas reinhardtii allowed the characterization of two circadian proteins in this model [START_REF] Wagner | Functional proteomics of circadian expressed proteins from Chlamydomonas reinhardtii[END_REF]. More recent HPLC-MS analyses in Ostreococcus tauri allowed the characterization of more rhythmic proteins involved in starch metabolism but also in cell cycle and ribosome biogenesis [START_REF] Bihan | Shotgun proteomic analysis of the unicellular alga Ostreococcus tauri[END_REF]. A similar approach was used to study the time-dependent impact of Casein Kinase 2 (CK2) overexpression on the global proteome and phosphoproteome, giving new information about the role of CK2 in circadian physiology [START_REF] Bihan | Label-free quantitative analysis of the casein kinase 2-responsive phosphoproteome of the marine minimal model species Ostreococcus tauri[END_REF].

In addition to unicellular species, a few studies reported the use of cultured cells. A first TMT LC-MS study compared the proteomes of primary fibroblasts originating from WT and Bmal1 KO mice at two different time points. It allows the characterization of differentially expressed proteins involved in protein synthesis, vesicle trafficking and cytoskeletal organization that could explain the higher infectivity predisposition of Bmal1 KO cells by both Herpes and Influenza viruses [START_REF] Edgar | Cell autonomous regulation of herpes and influenza virus infection by the circadian clock[END_REF]. Using mouse primary fibroblasts and a higher time-resolution, an additional SILAC LC-MS study improved the description of the cell-intrinsic circadian proteome. This study also allowed the description of the circadian clock-controlled actin dynamics that impact wound healing including burn healing in human [START_REF] Hoyle | Circadian actin dynamics drive rhythmic fibroblast mobilization during wound healing[END_REF]. While the relationship between mRNA and protein levels were not analyzed in the aforementioned studies, more recent TMT HPLC-MC proteomics analysis in Drosophila, showing that 93% of the rhythmic proteome in circadian clock-deficient S2 cells was not encoded by rhythmic transcripts, reinforced the idea that transcriptional regulation has a limited impact on the rhythmic proteome [START_REF] Rey | Metabolic oscillations on the circadian time scale in Drosophila cells lacking clock genes[END_REF].

Regulation at the post-translational level

Phosphorylation is the best studied post-translational modifications to date and plays a major role in the regulation of molecular circadian clocks [START_REF] Hirano | The intricate dance of post-translational modifications in the rhythm of life[END_REF]. Therefore, chronobiologists were early attracted by the characterization of rhythmic phosphorylation using proteomics. Pioneering work applied SILAC proteomic to monitor the circadian phosphorylation dynamics of FREQUENCY (FRQ) in Neurospora crassa. This study enabled the characterization of the role of phosphorylation in the stability of FRQ and also its capacity to interact with its partners [START_REF] Baker | Quantitative Proteomics Reveals a Dynamic Interactome and Phase-Specific Phosphorylation in the Neurospora Circadian Clock[END_REF]. A similar approach recently mapped and described the role of phosphorylation in the regulation of White Collar-1 and 2 (WC-1 and WC-2), as well as their role in regulating the Neurospora circadian clock [START_REF] Wang | The Phospho-Code Determining Circadian Feedback Loop Closure and Output in Neurospora[END_REF].

The first large scale quantitative circadian LC-MS-based phospho-proteomic study was later performed in Arabidopsis thaliana. It shows that phosphorylation cycles were partly coordinated by the circadian clock and strongly influenced by environmental factors such as light [START_REF] Choudhary | Quantitative Circadian Phosphoproteomic Analysis of Arabidopsis Reveals Extensive Clock Control of Key Components in Physiological, Metabolic, and Signaling Pathways[END_REF]. This observation was exemplified by a second label free LC-MS study showing the importance of concerted protein phosphorylation and acetylation involved in key plant processes [START_REF] Uhrig | Diurnal changes in concerted plant protein phosphorylation and acetylation in Arabidopsis organs and seedlings[END_REF]. In the mouse liver, several signaling pathways were shown to be rhythmically activated by the circadian clock and feeding fasting cycles. Among them, the AMPK and Extracellular signal-Regulated Kinase (ERK) pathways are activated during the light phase (fasting period) [START_REF] Lamia | AMPK Regulates the Circadian Clock by Cryptochrome Phosphorylation and Degradation[END_REF][START_REF] Jouffe | The Circadian Clock Coordinates Ribosome Biogenesis[END_REF] whereas the AKT-mTOR pathway is activated during the dark phase (feeding period) [START_REF] Atger | Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver[END_REF][START_REF] Jouffe | The Circadian Clock Coordinates Ribosome Biogenesis[END_REF]. The first label free LC-MS high-throughput phospho-proteomics characterization of rhythmic phosphorylation revealed that 25% of the liver phosphorylome was rhythmic [START_REF] Robles | Phosphorylation Is a Central Mechanism for Circadian Control of Metabolism and Physiology[END_REF]. These data confirmed the rhythmic activation of the aforementioned pathways and provided a global view on their impact on rhythmic liver metabolism and physiology. In addition, this study identified rhythmic phosphorylation sites on circadian clock proteins showing, for example, that CLOCK phosphorylation at Ser 446 and Ser 440/441 regulates its transcriptional activity [START_REF] Robles | Phosphorylation Is a Central Mechanism for Circadian Control of Metabolism and Physiology[END_REF]. A paralleled SILAC LC-MS nuclear phospho-proteomic experiment allowed the characterization of additional rhythmically activated kinases, mostly involved in cell cycle regulation. This rhythmic activation of cell cycle kinases could likely explain the observed rhythmic ploidy in mouse liver, with a peak of diploid bi-nucleated cells at the end of the light period [START_REF] Wang | Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver[END_REF]. Finally, a recent circadian LC-MS phosphoproteome study focused on the murine synaptosome. Half of the synaptosomal phosphorylated proteins show at least one rhythmic phosphorylation site. The rhythms of these phosphorylated sites are almost completely disrupted during sleep deprivation, with the exception of phosphoproteins associated with synaptic integrity and function [START_REF] Brüning | Sleep-wake cycles drive daily dynamics of synaptic phosphorylation[END_REF]. This result emphasizes the importance systemic signals as the ones orchestrated by sleep in the regulation of rhythmic signaling pathways regulating the rhythmic synaptosomal phosphoproteome.

Besides phosphorylation, other protein modifications like lysine-acetylation show also a rhythmic pattern.

Protein deacetylation, in particular through the SIRT1 deacetylase, plays a critical role in circadian clock regulation in both SCN and peripheral tissues [START_REF] Nakahata | The NAD + -Dependent Deacetylase SIRT1 Modulates CLOCK-Mediated Chromatin Remodeling and Circadian Control[END_REF][START_REF] Asher | SIRT1 Regulates Circadian Clock Gene Expression through PER2 Deacetylation[END_REF][START_REF] Chang | SIRT1 Mediates Central Circadian Control in the SCN by a Mechanism that Decays with Aging[END_REF]. In addition, protein acetylation plays a key role in metabolism, in particular in mitochondria [START_REF] Menzies | Protein acetylation in metabolism -metabolites and cofactors[END_REF]. Characterization of the rhythmic acetylome appeared therefore of great interest and a first HPLC-MS circadian acetylo-proteomic study looked at the circadian acetylome in WT and Clock∆19-mutant animals. The 306 quantified acetylation sites present in 179 proteins were highly enriched in mitochondrial proteins. Moreover, 19 and 15 of these acetylation sites displayed a rhythmic pattern in WT and Clock∆19 mutant mice, respectively, with impact on liver metabolism [START_REF] Masri | Circadian acetylome reveals regulation of mitochondrial metabolic pathways[END_REF]. A more recent highthroughput SILAC LC-MS analysis quantified more than 1000 acetylated sites, of which 13% present a rhythmic pattern. Interestingly, rhythmically acetylated proteins showed subcellular localization-specific phases. Indeed, mitochondrial proteins were more acetylated during the day whereas cytoplasmic and nuclear proteins were more acetylated during the night [START_REF] Mauvoisin | Circadian and Feeding Rhythms Orchestrate the Diurnal Liver Acetylome[END_REF]. Mitochondrial protein were over-represented among the rhythmically acetylated proteins and their acetylations correlated with the activity of SIRT3, a mitochondrial NAD + dependent deacetylase [START_REF] Hebert | Calorie Restriction and SIRT3 Trigger Global Reprogramming of the Mitochondrial Protein Acetylome[END_REF][START_REF] Lombard | Mammalian Sir2 Homolog SIRT3 Regulates Global Mitochondrial Lysine Acetylation[END_REF]. NAD + synthesis is orchestrated by both feeding rhythms and the circadian clock through the NAD + salvage pathway and the nicotinamide riboside pathway [START_REF] Mauvoisin | Circadian and Feeding Rhythms Orchestrate the Diurnal Liver Acetylome[END_REF][START_REF] Nakahata | Circadian Control of the NAD + Salvage Pathway by CLOCK-SIRT1[END_REF][START_REF] Ramsey | Circadian Clock Feedback Cycle Through NAMPT-Mediated NAD + Biosynthesis[END_REF]. As a consequence, the diurnal acetylome relies on a functional circadian clock and affects important diurnal metabolic pathways in the mouse liver.

In addition to phosphorylation and acetylation, ubiquitination plays also a crucial role in the regulation of circadian physiology [START_REF] Hirano | The intricate dance of post-translational modifications in the rhythm of life[END_REF]. A recent LC-MS characterization of the ubiquitinome in clock-expressing cells of Drosophila heads gave new insights about the role of protein ubiquitination in the circadian clock regulation [START_REF] Szabó | Ubiquitylation Dynamics of the Clock Cell Proteome and TIMELESS during a Circadian Cycle[END_REF]. In mouse liver, rhythmic ubiquitination appeared to play an important role in the rhythmicity of several signaling pathways and transcription factors [START_REF] Wang | A proteomics landscape of circadian clock in mouse liver[END_REF]. Although not directly associated with ubiquitination, a recent LC-MS analysis of the rhythmic macroautophagic flux revealed a specific rhythmic degradation of proteasomal proteins, implicating a rhythmic proteasomal degradation of ubiquitinated proteins [START_REF] Ryzhikov | Diurnal Rhythms Spatially and Temporally Organize Autophagy[END_REF].

The repertoire of post-translational modifications is still growing and its temporal dynamics remains far from being fully characterized. For instance, besides acetylation, other metabolic-link lysine acylations also deserve temporal exploration because of their importance in metabolic sensing and regulation [START_REF] Ringel | Chemical and Physiological Features of Mitochondrial Acylation[END_REF] as well as their regulation by the molecular circadian clock [START_REF] Mauvoisin | Circadian and Feeding Rhythms Orchestrate the Diurnal Liver Acetylome[END_REF].

Discussion

Because of recent technical progress such as the possibility of multiplexing and getting a higher resolution, the interest in proteomics has increased in the last years in many research areas including chronobiology. A regular observation from the pioneering 2D-DIGE studies to the more recent high-throughput analyses has been the key implication of post-transcriptional and post-translational regulations in generating proteome rhythmicity. Indeed, in all studied models, rhythmic transcriptional regulation appeared to drive only a part (from 3% [START_REF] Rey | Metabolic oscillations on the circadian time scale in Drosophila cells lacking clock genes[END_REF] to 80% [START_REF] Robles | In-Vivo Quantitative Proteomics Reveals a Key Contribution of Post-Transcriptional Mechanisms to the Circadian Regulation of Liver Metabolism[END_REF]) of the rhythmic proteome. Rhythmic mRNA translation, protein degradation, protein transport and secretion appeared to be the main regulators of the rhythmic proteome.

One major caveat of the experiments described in the present review is the fact that only a few of them fulfilled the recommendations for the analysis of rhythmic data series and the optimization statistical power, namely at least 12 time points per cycle across 2 full cycles [START_REF] Hughes | Guidelines for Genome-Scale Analysis of Biological Rhythms[END_REF]. In addition, most of the time-resolved proteomic studies used only WT plant or animal models and there is a lack of similar data in clock-deficient models. This lack of data contributes to the difficulty to fully characterize the contribution of the circadian clock in these temporal regulations. Transcriptomics analyses of gene expression in clock-deficient animals improved significantly our understanding of the relative roles of feeding rhythm and the circadian clock in the generation of rhythmicity in peripheral organs such as the mouse liver [START_REF] Atger | Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver[END_REF][START_REF] Greenwell | Rhythmic Food Intake Drives Rhythmic Gene Expression More Potently than the Hepatic Circadian Clock in Mice[END_REF][START_REF] Vollmers | Time of feeding and the intrinsic circadian clock drive rhythms in hepatic gene expression[END_REF]. Similar proteomics approaches will potentially identify new circadian clock and/or metabolism-associated pathways implicated in the rhythmic post-transcriptional regulation of the proteome. Only limited proteomic data is currently available in challenged conditions such as KO of clock genes or irregular light or feeding schedules. The available data indicate, for example, that liver protein secretion is controlled by feeding rhythms, with only little influence of the molecular circadian clock [START_REF] Mauvoisin | Circadian clock-dependent andindependent rhythmic proteomes implement distinct diurnal functions in mouse liver[END_REF]. The same observation is true for the part of the nuclear rhythmic proteome that is conserved in clock-deficient animals [START_REF] Wang | Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver[END_REF]. Nonetheless, the low temporal resolution of KO data in these studies did not allow for a comprehensive evaluation of the circadian clock in the regulation of post-transcriptional processes that are involved in generating rhythms of protein abundance in the liver. To refine this assessment and get a clearer picture of the circadian regulation of physiology, future proteomic studies will be necessary, in the same way as transcriptomics works allowed the identification of the role of the clock in the generation of the rhythmic transcriptome in Drosophila [START_REF] Hughes | Deep sequencing the circadian and diurnal transcriptome of Drosophila brain[END_REF], mouse [START_REF] Vollmers | Time of feeding and the intrinsic circadian clock drive rhythms in hepatic gene expression[END_REF] and even human [START_REF] Perrin | Transcriptomic analyses reveal rhythmic and CLOCK-driven pathways in human skeletal muscle[END_REF]. The majority of the rhythmic genes are associated with diseases and are considered to be potential drug targets for precision chronotherapy in human [START_REF] Zhang | A circadian gene expression atlas in mammals: Implications for biology and medicine[END_REF]. Given the discrepancy between protein and mRNA rhythms, it is of utmost importance to precisely associate rhythmic gene expression with the corresponding dynamics of the proteome to develop efficient chronotherapeutic approaches [START_REF] Cederroth | Medicine in the Fourth Dimension[END_REF].

Figure 1 :

 1 Figure 1: Hierarchical and molecular organization of the mammalian circadian clock Left: Hierarchical organization of the mammalian circadian clock: a "master" clock present in the SCN of the hypothalamus communicates timing with "slave" oscillators in peripheral organs via humoral, neuronal and systemic signals. Center and right: The mammalian molecular circadian clock: the activating loop composed of BMAL1 heterodimers activate the transcription of the negative feedback loop components encoded by the Per1-3 and Cry1-2 genes. PER and CRY assemble into large macromolecular complexes, translocate into the nucleus, remove BMAL1 heterodimers from the chromatin and, as a result, inhibit BMAL1 transcriptional activity. The stabilizing loop involves REV-ERB's and ROR nuclear receptors that compete for ROR elements located within the promoters of clock genes. Besides core circadian clock regulators, the clock-regulated PARbZip transcription factors DBP, HLF and TEF, and their repressive counterpart E4BP4, play key roles in clockregulated metabolic regulation. These interconnected loops generate multiple coordinated phases of rhythmic gene expression, allowing the temporal regulation of thousands of clock-controlled genes.

Figure 2 :

 2 Figure 2: Quantitative MS approaches used in circadian proteomics studies Colors represent different experimental conditions. Stars indicate the steps of protein labelling. Combination of the samples allows the quantification of relative protein abundance in the different experimental conditions. Earlier labelling and samples combination diminish the risk of quantification errors due to inherent technical variations. **In the case of label free, the combination is performed post-data acquisition by computational treatment of the MS data.

Figure 3 :

 3 Figure 3: Timeline of circadian/diurnal proteomic studies

Acknowledgments

We thank Meltem Weger and Benjamin Weger for insightful comments on the manuscript. D.M. receives support from the French National Research Agency under the "Programme Investissement d'Avenir" (NExT (I-SITE); ANR-16-IDEX-0007) and financial support from "Pays de la Loire" regional council and "Nantes Métropole". F.G. receives support from the Institute for Molecular Bioscience, The University of Queensland.


Weijie Lan
email: weijie.lan@inrae.fr

Catherine M G C Renard
email: catherine.renard@inrae.fr

Benoit Jaillais
email: benoit.jaillais@inrae.fr

Alexandre Leca
email: alexandre.leca@inrae.fr

Sylvie Bureau
email: sylvie.bureau@inrae.fr

Fresh, Freeze-dried or Cell Wall Samples: Which is the Most Appropriate to Determine Chemical, Structural and Rheological Variations During Apple Processing Using ATR-FTIR Spectroscopy?

Keywords: Malus domestica Borkh., Mid infrared spectroscopy, apple processing, Partial Least-Squares Regression (PLSR), discrimination

Proposition of puree sample preparation according to the expected quality traits.

Similar spectral fingerprints due to processing in fresh and freeze-dried samples.

ATR-FTIR on fresh purees could predict particle size and volume affecting texture.

ATR-FTIR on freeze-dried purees could assess viscosity and viscoelasticity.

ATR-FTIR on cell walls could highlight their changes during processing.

Introduction

Sample preparation is a key point for quality of analytical data. Infrared spectroscopy (near or mid-infrared), because of its integrative nature, is one of the main candidates for a rapid qualification of agricultural commodities and processed food, especially in the view of process analytical technology (PAT). Advanced techniques based on infrared spectroscopy offer the advantages of a minimal sample preparation and a rapid data acquisition. However, this questions the balance between data intensity and required sample preparation hence man-power: are the data acquired on "raw" samples sufficient for process monitoring, quality control or process comprehension? A specific point is also that foods are frequently highly hydrated and not stable, so that appropriate steps must be taken to preserve samples for later quality control. As the time consumption and cost of sample preparation are generally barriers to a rapid and precise determination by spectroscopy, knowing the most efficient sample pretreatments could contribute to improve analytical results as well as to provide informative options at both, laboratory and industrial scales.

Different methods for the reference data acquisition such as HPLC, GC-MS or NMR [START_REF] Bureau | Determination of the Composition in Sugars and Organic Acids in Peach Using Mid Infrared Spectroscopy: Comparison of Prediction Results According to Data Sets and Different Reference Methods[END_REF], types of spectroscopy or related hyperspectral images (NIR, MIR, Raman) [START_REF] Baranska | Determination of Lycopene and β-Carotene Content in Tomato Fruits and Related Products: Comparison of FT-Raman, ATR-IR, and NIR Spectroscopy[END_REF] and modeling algorithms [START_REF] Van Boekel | Kinetic Modeling of Food Quality: A Critical Review[END_REF] have been intensively compared on fruits. It seems also crucial to compare and determine the optimal sample form (fresh, freeze-dried or cell wall extracts) and the associated changes occurring during fruit processing, notably using infrared spectroscopy which has the potential to be applied both, on-line and off-line.

Direct ATR-FTIR estimations on fruit fresh homogenates have obtained good results to predict soluble solids content, dry matter content, titratable acidity, some individual sugars and organic acids [START_REF] Bureau | Effect of Sample Preparation on the Measurement of Sugars, Organic Acids, and Polyphenols in Apple Fruit by Mid-infrared Spectroscopy[END_REF][START_REF] Ayvaz | Monitoring multicomponent quality traits in tomato juice using portable mid-infrared (MIR) spectroscopy and multivariate analysis[END_REF]. As infrared spectroscopy is extremely sensitive to changes of hydrogen bonding [START_REF] Jackson | The use and misuse of FTIR spectroscopy in the determination of protein structure[END_REF], the main drawback of spectral measurements is the low sensitivity and limited specific signals of chemical compositions under strong water interactions in fresh fruit suspensions, such as citric acid in apples [START_REF] Bureau | Effect of Sample Preparation on the Measurement of Sugars, Organic Acids, and Polyphenols in Apple Fruit by Mid-infrared Spectroscopy[END_REF], lycopene and β-carotene in tomato [START_REF] Baranska | Determination of Lycopene and β-Carotene Content in Tomato Fruits and Related Products: Comparison of FT-Raman, ATR-IR, and NIR Spectroscopy[END_REF]. Moreover, classical measurements of rheological properties and particle size distribution of fruit products require costly rheometer, particle sizing equipment and experienced staffs. Therefore, one of the challenging works is to investigate the possibility of ATR-FTIR to estimate the specific rheological modifications (viscosity and viscoelastic parameters) and then to monitor textural changes (particle size and volume) for both, accurate determinations in scientific research or rapid and direct assessment in industrial processing.

Much more information can be extracted from dry food commodities, such as the structural changes of cereals [START_REF] Georget | Effects of Temperature and Water Content on the Secondary Structure of Wheat Gluten Studied by FTIR Spectroscopy[END_REF], micronutrients in fruits [START_REF] Lu | Determination of total phenolic content and antioxidant capacity of onion (Allium cepa) and shallot (Allium oschaninii) using infrared spectroscopy[END_REF] and even cell wall content variations [START_REF] Canteri | ATR-FTIR spectroscopy to determine cell wall composition: Application on a large diversity of fruits and vegetables[END_REF]. To overcome the limitations observed on highly hydrated products, such as fruits, drying methods with as limited as possible alteration of composition and structure are needed. Thus, freeze-drying prevents evolution of samples under the action of endogenous enzymes (notably oxidation and hydrolysis). It also carries out a concentration due to water elimination, so that specific components present in low concentrations can have significant spectral absorptions. But freeze-drying is expensive and time-consuming, needing at least 24-48 hours. It allowed to obtain similar predictions of chemical compositions than those in fresh samples (de Oliveira, de Castilhos, [START_REF] De Oliveira | Comparison of NIR and MIR spectroscopic methods for determination of individual sugars, organic acids and carotenoids in passion fruit[END_REF][START_REF] Oliveira-Folador | Quality traits prediction of the passion fruit pulp using NIR and MIR spectroscopy[END_REF]. Few detailed studies compared the differences and limitations of ATR-FTIR fingerprint regions on fresh and corresponding freeze-dried plant leaves [START_REF] Durak | Effect of plant sample preparation and measuring methods on ATR-FTIR spectra results[END_REF]. ATR-FTIR applications to assess fruit textural properties (mainly focus on cell wall compositions) are always performed on their cell wall materials (AIS) [START_REF] Canteri | ATR-FTIR spectroscopy to determine cell wall composition: Application on a large diversity of fruits and vegetables[END_REF][START_REF] Szymanska-Chargot | Combining FT-IR spectroscopy and multivariate analysis for qualitative and quantitative analysis of the cell wall composition changes during apples development[END_REF]. However, extracting the cell wall requires a large consumption of chemical solvents if starting from fresh samples (up to 1 L ethanol and 0.4 L acetone/ 1.0 -1.5 g cell wall). The accelerated or pressurized solvent extractors (ASE, PSE) can allow multiplexing and thus a faster and less solvent-consuming cell wall preparation, but only from already freeze-dried samples. After removing all soluble components (mainly sugars and acids), specific signals related to pectins, cellulose and hemicelluloses have proven to be useful for the fast evaluation of cell wall polysaccharides during fruit growth and subsequent storage [START_REF] Szymanska-Chargot | Combining FT-IR spectroscopy and multivariate analysis for qualitative and quantitative analysis of the cell wall composition changes during apples development[END_REF]. Although some cell wall modifications in plants [START_REF] Femenia | Effects of heat treatment and dehydration on bioactive polysaccharide acemannan and cell wall polymers from Aloe barbadensis Miller[END_REF] and fruits [START_REF] Cardoso | Traditional and industrial oven-dry processing of olive fruits: influence on textural properties, cell wall polysaccharide composition, and enzymatic activity[END_REF] under heating and dehydration have been investigated by ATR-FTIR. However, for fruit processed purees, little work has been done on ATR-FTIR to detect their cell wall changes during processing and monitor rheological and mechanical properties [START_REF] Ferreira | Use of FT-IR spectroscopy to follow the effect of processing in cell wall polysaccharide extracts of a sun-dried pear[END_REF].

In this study, ATR-FTIR spectroscopy was applied on the corresponding raw apples and processed purees. Spectra were acquired on different kinds of homogeneous samples such as fresh (NF for non-freeze-dried), freeze-dried (FD) and cell wall extracts (AIS for alcohol insoluble solids) in order to: i) evaluate how much sample preparation improved the prediction of chemical, textural and rheological characteristics of purees (number of quality traits and their precision) and ii) identify signals specific of the variations which occur during apple processing.

Materials and methods

Plant Material

Apples of two cultivars: 'Golden Delicious' (GD) and 'Granny Smith' (GS) were harvested at commercial maturity in 2017 in an experimental orchard named La Pugère (Mallemort, Bouches-du-Rhône, France). Standard commercial fruit thinning practices (Th+ to 50 to 100 fruits/tree) and no thinning (Th-to 150-200 fruits/tree) were compared during the ripening of 'Golden Delicious'. The three obtained apple groups (Th+ GD, Th-GD and GS) were stored in a cold chamber at 4°C and at around 90% of humidity during one, three and six months (respectively T1, T3 and T6), except the first batch (T0) were analyzed and processed the day after harvest without any storage time.

Each apple batch (T0, T1, T3 and T6) was divided into two subsets (Figure 1): i) the first subset was dedicated to apples characterization: 3 replicates of 10 apples were selected and separated into two aggregate samples as described by Bureau [START_REF] Bureau | Effect of Sample Preparation on the Measurement of Sugars, Organic Acids, and Polyphenols in Apple Fruit by Mid-infrared Spectroscopy[END_REF]. One sample corresponding to the NF sample was stored at -80°C and then homogenized at 11000 rpm with an Ultraturrax T-25 (IKA, Labortechnik, GmbH, Staufen, Germany) after 1.5 h of thawing at 22.5 °C for biochemical and spectral characterizations. The other sample corresponding to the freeze-dried (FD) was used to extract cell wall materials (AIS).

Finally, 36 NF, FD and AIS samples (3 apple groups × 4 storage times × 3 biological replicates) of raw apple fruits were obtained.

ii) the second sub-set was dedicated to puree processing: 3 replicates of apples (4 kg each) were used to produce three puree lots. After sorting and washing, apples were cored and cut in 8 portions, then processed in a multi-functional processing system (Roboqbo, Qb8-3, Bentivoglio, Italy). Half of the each puree (2 kg) was refined with a 0.5 mm (Ra) sieve (Robot Coupe C80 automatic refiner, Robot Coupe SNC, Vincennes, France) whereas the other half was not refined (NR). Finally, fresh puree samples (NF) were conditioned in two hermetically sealing cans: one was cooled at room temperature (22.5 °C) before the next-day measurements of rheological, textual and some chemical (soluble solids and titratable acidity) properties, while the other was freeze-dried (FD) and stored at -20 °C for AIS extraction. Thus, in total 72 NF, FD and AIS samples of purees were prepared and characterized, corresponding to 3 apple groups × 4 storage times × 2 refining levels × 3 biological replicates.

Biochemical Analyses

Soluble solids content (SSC) was determined with a digital refractometer (PR-101 ATAGO, Norfolk, VA, USA) and expressed in °Brix at 20°C. Titratable acidity (TA) was determined by titration up to pH 8.1 with 0.1 mol/L NaOH and expressed in mmol H + /kg of fresh weight (FW) using an autotitrator (Methrom, Herisau, Switzerland). Sugars (glucose, fructose and sucrose) and malic acid were quantified using an enzymatic method with kits for food analysis (Sigma-Aldrich, Deisenhofen, Germany) and expressed in g/kg FW. These measurements were performed with a SAFAS flx-Xenius XM spectrofluorimeter (SAFAS, Monaco). The dry matter content (DMC) was estimated with the weight of freeze-dried samples upon reaching a constant weight (freeze-dryer, 5 days). Cell wall materials (AIS) were isolated using the method proposed by Renard [START_REF] Renard | Variability in cell wall preparations: quantification and comparison of common methods[END_REF]. and the cell wall contents (AIS contents) were expressed in both, fresh weight (FW) and dry matter weight (DW). Three biological replicates were characterized for each biochemical trait and each sample.

Rheological Analyses

The puree rheological measurements consisted in one rotational (flow curve) and two oscillatory (amplitude and frequency sweeps) tests, carried out using a Physica MCR-301 controlled stress rheometer (Anton Paar, Graz, Austria) at 22.5 °C. 50 mL of each puree sample was placed in a C-CC27 with an inner radius of 14.46 mm measuring cup (Anton Paar, Graz, Austria). All tests were performed by a six blade vane geometry FL 100/6W with a radius of 11 mm (Anton Paar, Graz, Austria). The flow curves were performed after a pre-shearing period of 1 minute at 50/s followed by 5 minutes at rest. The viscosity was then measured at a controlled shear rate range of [10; 250]/s on a logarithmic ramp, at a rate of 1 point every 15 seconds. The values of the viscosity at 50/s and 100/s (η50 and η100 respectively) were kept as indicators of the sensorial puree texture [START_REF] Engelen | Oral Processing and Texture Perception[END_REF][START_REF] Espinosa-Muñoz | The significance of structural properties for the development of innovative apple puree textures[END_REF] during consumption. Amplitude Sweep (AS) tests were performed at an angular frequency of 10 rad./s in the deformation range of [0.01; 100] %, in order to determine the linear viscoelastic range of the purees and the yield stress, defined as the crossing point between the storage modulus (AS-G') and the loss modulus (AS-G'') curves. Frequency Sweep (FS) measurements were operated within the linear viscoelastic region as determined by the AS test (0.05%) in the angular frequency range of [0.1; 100] rad./s. For means of comparison the storage and loss moduli (FS-G' and FS-G'') were taken at 1 rad./s to evaluate the viscoelastic properties of the studied purees. Puree samples were diluted in distilled water to separate particles and stained with calcofluor white at 0.1 g/L and highlighted with a 365 nm UV lamp [START_REF] Soukup | Selected Simple Methods of Plant Cell Wall Histochemistry and Staining for Light Microscopy[END_REF]. A high-resolution digital video camera (Baumer VCXU31C, Baumer SAS, France) with a macro lens (VSTech 0513, VS Technology Corporation, Japan.) was used to visualize the distribution and dispersion of puree particles. The particle sizes averaged over volume d(4:3) (de Brouckere mean) and over surface area d(3:2) (Sauter mean) were measured with a laser granulometer [START_REF] Rawle | Basic of principles of particle-size analysis[END_REF] (Mastersizer 2000, Malvern Instruments, Malvern, UK).

ATR-FTIR spectrum acquisition

ATR-FTIR spectra were collected at room temperature using a Tensor 27 FTIR spectrometer (Bruker Optics, Wissembourg, France) equipped with a horizontal attenuated total reflectance (ATR) sampling accessory and a deuterated triglycine sulphate (DTGS) detector. Three replications of spectral measurement were performed on all raw and processed apples for fresh (NF for non freeze-dried), freeze-dried (FD) and cell wall (AIS) samples. The spectra of all samples were acquired in random order. The instrument adjustment and spectral acquisition were controlled by OPUS software Version 5.0 (Bruker Optics®). The spectra of raw and processed apples were acquired using two different crystals. A big zinc selenide (ATR-ZnSe) crystal with dimensions of 6 cm x 1 cm and six internal reflections was used for fresh samples (apple homogenates and purees) containing water. For the freeze-dried and cell wall samples, a small crystal was used characterized by a single-reflectance horizontal ATR-Diamond Cell (Golden Gate Bruker Optics) equipped with a press tip flap system to press sample on the crystal always in the same way. Spectra (32 scans for ATR-ZnSe and 16 scans for ATR-Diamond) were collected from 4000 cm -1 to 650 cm -1 and were corrected against the background spectrum of air.

Statistical Analyses and Chemometrics

After ensuring normal distribution with a Shapiro-Wilk test (α=0.05), the reference data were presented as mean values and the data dispersion within our experimental dataset expressed as standard deviation values (SD). Analysis of variance (ANOVA) was carried out to determine the significant differences due to the controlled factors (thinning, storage and puree mechanical refining) on both apples (Table S-1) andpurees of each variety (Table S-2 andTable S-3 Spectral pre-processing and multivariate data analysis were performed with Matlab 7.5 (Mathworks Inc. Natick, MA) software using the SAISIR package [START_REF] Bertrand | SAISIR package. Free toolbox for chemometrics in the Matlab[END_REF]. The absorption band between 2400-2300 cm -1 , due to carbon dioxide, was discarded prior to the calculation. All FT-IR data were pre-processed with baseline correction, standard normal variate (SNV) and a derivative transform calculation Savitzky-Golay method, gap size = 11, 21, 31) of first or second order. After pretests of these pre-processing treatments applied on several different spectral regions, the best results of prediction and discrimination were obtained on the range 1800-900 cm -1 , which has been already highlighted [START_REF] Bureau | Application of ATR-FTIR for a rapid and simultaneous determination of sugars and organic acids in apricot fruit[END_REF]. Particularly, Principal Component Analysis (PCA) and Factorial Discriminant Analysis (FDA) were applied on SNV pre-treated spectra (in Part 3.1 and Part 3.2). The specificity and sensitivity values of FDA discriminations were calculated by the already reported method of Nargis [START_REF] Nargis | Raman spectroscopy of blood plasma samples from breast cancer patients at different stages[END_REF], in order to better evaluate sample differentation. For PLS (Partial least square) modelling (in Part 3.3), the baseline correction coupled with SNV pre-processing had the best performances to correct multiplicative interferences and variations in baseline shift, and reached the best prediction results.

Leave-one-out PLS models were developed using spectra of fresh (NF), freeze-dried (FD) and AIS of puree samples, for which the three spectral matrices (NF, FD and AIS) corresponded to the same reference dataset. A total number of 72 averaged spectra for each puree form (NF, FD and AIS) corresponding to 3 apple groups (GS, GD Th+ and GD Th-) × 4 storage times × 2 puree refining modalities × 3 biological replicates was used as modelling dataset. PLS model performance was assessed using the determination coefficient of cross-validation (Rcv 2 ), the root-mean-square error of cross-validation (RMSECv), the number of latent variables (LVs), the ratio of the standard deviation values (RPD) and the linkable spectral regions (Tables 1 and2). The linearity correlation plots between measured and predicted values of all PLS models were showed in supplementary materials (Figure

Results and discussions

Spectral characterization of NF (non-freeze-dried) apple purees

PCA and FDA applied on the spectra of NF puree samples successfully allowed to detect puree differences coming from the raw apple variabilities (cultivar, fruit thinning and storage period) (Figure 2). They also highlighted the modifications of puree structure by the mechanical refining over several months of apple storage (Figure 3).

In Figure 2, the first principal component (PC1) clearly discriminated the two varieties ('Golden Delicious' and 'Granny Smith') and thinning practices for Golden delicious (Th-and Th+), in relation with the fructose variation followed at 1061 cm -1 [START_REF] Bureau | Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review[END_REF]. Moreover, the peak at 1022 cm -1 , reported as a peak specific to sucrose in apple juices [START_REF] Leopold | Quantification of carbohydrates in fruit juices using FTIR spectroscopy and multivariate analysis[END_REF], appeared to be the main contributor of the second principal component (PC2), which distinguished the storage times. Along the PC2 axis, the discrimination of storage durations from T0 at the top to T6 at the bottom was in relation with the decrease of sucrose (1022 cm -1 ) and the increase of fructose (1065 cm -1 ) in purees, in accordance with the reference chemical dataset (Table S-2). Consequently, factors such as cultivar, thinning practice and storage duration affecting raw apple characteristics induced changes in the corresponding purees after processing. ATR-FTIR applied directly on processed purees could then be useful for traceability of these effects impacting raw fruits based on the specific C-C and C-O-C bonds of carbohydrates, such as 1022 cm -1 , 1061 cm -1 , 1065 cm -1 .

According to the reference data (Table S- (4:3) andd(3:2)) in T0 purees prepared with apples at harvest (T0). However, gradually over apple storage, less differences were detected between the non-refined (NR) and refined (Ra) purees. The non-refined (NR) 'Golden Delicious' and'Granny Smith'purees were characterized by large apple particles and only few small separated cells at the beginning of cold storage (T0) (Figure 3a). The refining treatments mainly led to lower particle size by removing the big puree particles (Figure 3a). However, at the end of storage (T6), both non-refined (NR) and refined (Ra) purees were mostly composed of single cells and no clear difference was observed between them (Figure 3d). This similar structure of NR and Ra purees at T6 could be due to an increase in cell separability linked to a decrease of the intermolecular bonding between cell wall polymers and a notable increase of pectin solubility during apple storage [START_REF] Varela | Changes in apple tissue with storage time: Rheological, textural and microstructural analyses[END_REF].

FDA performed on the spectra of all NR and Ra purees (NF samples) at each apple storage time gave highly consistent observations with the reference data and macroscopic images showed above (Figure 3). According to the third factorial components (F3) (F1 and F2 for cultivar and thinning discriminations, Figure S-2), the two puree refining levels were well separated at T0, then appeared progressively overlapped at T3 and T6 (Figure 3). Especially along the F3 axis, at T0, intensive spectral variations were related to the decrease of soluble organic acids (1718 cm -1 and 1709 cm -1 ), soluble polysaccharides, pectins and absorbed water (1740 cm -1 , 1695 cm -1 , 1682 cm -1 , 1668 cm -1 , 1655 cm -1 and 1468 cm -1 ) between the two refining conditions (Figure S-3). Although the peaks of carbohydrates at 1019 cm -1 and 1049 cm -1 (glucose/fructose) and 1155 cm -1 (the glycosidic linkage) are known to successfully monitor the consistency of tomato juice [START_REF] Ayvaz | Monitoring multicomponent quality traits in tomato juice using portable mid-infrared (MIR) spectroscopy and multivariate analysis[END_REF], the region between 1750 and 1450 cm -1 highly contributed to the discrimination of apple purees according to their particle size and their rheological behavior after mechanical refining treatments. These differences between tomato and apple might be due to the nature of the datasets and in particular the impact of post-harvest storage on chemical compositions (sugars and acids) and textural properties (pectins degradations) as confounding factors in this apple processing experiment.

Spectral evaluation of the link between fresh and processed apples

FDA results showed a good ability to discriminate puree processing changes (Figure 4) and cultivar differences (Figure S-4), according to the first two discriminant factors (F1 and F2). Whatever the sample preparation (NF, FD and AIS), a clear separation was observed between raw apples (homogenates) and processed purees (Figures 4 a,c,e). The changes occurring during processing between raw (homogenates) and processed (purees) products were illustrated on the first factorial axis (F1) for the NF samples (with 97.2% specificity and 98.6% sensitivity) and AIS materials (100% specificity and sensitivity), and on the second factorial axis (F2) for FD samples (100% specificity and sensitivity).

Combining the main discriminant coefficients of the FDA models separating raw and processed materials (F2 for NF and FD samples, F1 for AIS samples) (Figures 4 b,d,f) and using the absorption band assignments described in literature, allowed to identify phenomena occurring during apple processing. In both NF and FD samples, highly consistent variations of spectral intensity were commonly found between 1800 and 1500 cm -1 , this region giving overlapped information related to pectins, proteins, phenolics and absorbed water [START_REF] Kačuráková | Characterisation of xylan-type polysaccharides and associated cell wall components by FT-IR and FT-Raman spectroscopies[END_REF], detailed in the following section:

-The increase of the bands at 1750 cm -1 in NF (Figure 4b), 1788 cm -1 and 949 cm -1 in FD (Figure 4d) were specific of C=O, C-O and C-C stretching vibrations of carboxylic acids and polysaccharides [START_REF] Canteri | ATR-FTIR spectroscopy to determine cell wall composition: Application on a large diversity of fruits and vegetables[END_REF][START_REF] Kyomugasho | FT-IR spectroscopy, a reliable method for routine analysis of the degree of methylesterification of pectin in different fruit-and vegetable-based matrices[END_REF]. These observations were in accordance with the increase of soluble fiber fractions and total polysaccharide contents after apple cooking [START_REF] Colin-Henrion | From apple to applesauce: Processing effects on dietary fibres and cell wall polysaccharides[END_REF].

-The bands at 1610-1620 cm -1 (1614 cm -1 in NF; 1618 cm -1 in FD) have been reported to correspond to the vibration of C=O from protein or pectic acid ester [START_REF] Abidi | Changes in the cell wall and cellulose content of developing cotton fibers investigated by FTIR spectroscopy[END_REF]. These peaks were consistent with the aforementioned pectic absorption peaks (1750 cm -1 and 1788 cm -1 ), in accordance with the increase of pectin content in purees. In the same way, this absorbance displays the same variations in a simplified experiment of apple cell wall (mainly soluble pectins) submitted to similar puree processing conditions (100°C for 20 min at pH 3.0) [START_REF] Liu | Modification of cell walls of apple, red beet and kiwifruit by heating in acid conditions: common and specific responses. 15th Cell wall meeting[END_REF]. In addition, the negligible concentration of proteins in fresh and processed apples (0.17-0.57 g/100 g FW) limited the hypothesis concerning the protein change during apple processing (U.S. Department of Agriculture, Agricultural Research Service , 2019).

-the strong decrease of bands near 1630 cm -1 and 1560 cm -1 could be attributed to the degradation of phenolic compounds during processing. These bands have been already identified to quantify the polyphenol contents in freeze-dried apples [START_REF] Bureau | Effect of Sample Preparation on the Measurement of Sugars, Organic Acids, and Polyphenols in Apple Fruit by Mid-infrared Spectroscopy[END_REF].

-the specific bands of soluble acids (1712 cm -1 in NF, 1718 cm -1 in FD) [START_REF] Clark | Fast determination by Fourier-transform infrared spectroscopy of sugar-acid composition of citrus juices for determination of industry maturity standards[END_REF] and of sugars (fructose at 1084 cm -1 and 1061 cm -1 ; sucrose at 1113 cm -1 ) [START_REF] Bureau | Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review[END_REF], which have been validated with standard chemicals in ATR-FTIR, could partially contribute to the dynamics of puree changes.

These spectral variations relating the decreases of acid contents and increases of fructose at 1712 cm -1 were also in line with the results of chemical measurements (Table S1 andTable S2).

In cell wall materials (AIS), two negative peaks at 1100 cm -1 and 984 cm -1 (Figure 4f), could be attributed to the solubilization of the cell wall pectins after thermal processing [START_REF] Coimbra | Multivariate analysis of uronic acid and neutral sugars in whole pectic samples by FT-IR spectroscopy[END_REF][START_REF] Kacurakova | FT-IR study of plant cell wall model compounds: pectic polysaccharides and hemicelluloses[END_REF], consistent with the acid hydrolysis and β-elimination of pectins depolymerization while apple processing [START_REF] Bourvellec | Phenolic and polysaccharidic composition of applesauce is close to that of apple flesh[END_REF]. Conversely, two positive peaks at 1595 cm -1 and 1030 cm -1 could be linked to the increase of lignin [START_REF] Garside | Identification of cellulosic fibres by FTIR spectroscopy-thread and single fibre analysis by attenuated total reflectance[END_REF] and cellulose contents [START_REF] Fasoli | Pectins, Hemicelluloses and Celluloses Show Specific Dynamics in the Internal and External Surfaces of Grape Berry Skin During Ripening[END_REF][START_REF] Schulz | Identification and quantification of valuable plant substances by IR and Raman spectroscopy[END_REF] in cell wall materials. A possible explanation is the depolymerization of cell wall polysaccharides (mainly pectins) during maturation resulting in a relative enrichment of lignin and cellulose in comparison with pectins after apple processing. ATR-FTIR detected the processing changes from raw apples to purees by scanning fresh, freeze-dried and cell wall samples. Particularly, spectra of fresh and freeze-dried samples, i.e. with or without water, provided highly consistent information on internal soluble matters (sugars, acids, pectins and phenolics).

Concerning the cell wall depolymerization (mainly pectin solubilization and galactose loss), these change could be detected only by scanning the cell wall materials (AIS), thus highlighting the solubilization of pectins diffusing from pulp to serum [START_REF] Burgy | Molecular size of soluble pectins in apple fruits is not affected by heat processing into puree[END_REF][START_REF] Sila | Pectins in processed fruits and vegetables: Part II Structure function relationships[END_REF].

Prediction of quality traits: comparison according to sample forms

Acceptable to good predictions of SSC, TA. DMC, fructose and malic acid could be obtained on fresh (NF) and/or freeze-dried (FD) purees by ATR-FTIR, giving RPD from 3.1 to 5.2 (NF) and from 3.6 to 7.6 (FD) (Table 1).

The prediction of global fruit quality traits, such as SSC and DMC, depended on two major spectral peaks, respectively, related to the sugars in NF (1061 cm -1 ) [START_REF] Bureau | Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables: A review[END_REF] and to the acids in FD (1724 cm -1 ) [START_REF] Clark | Fast determination by Fourier-transform infrared spectroscopy of sugar-acid composition of citrus juices for determination of industry maturity standards[END_REF].

In purees, the prediction accuracy of these two quality traits was similar in NF and FD samples with a Rcv 2 higher than 0.94 for SSC and higher than 0.89 for DMC. A good correlation between SSC and DMC in purees (R 2 =0.78) and the similar related spectral signals used in models (mainly 1724 cm -1 and 1061 cm -1 ) explained the good prediction of both SSC and DMC in NF and FD samples. For the third global quality trait, TA, its prediction was excellent with RPD higher than 6 in NF and FD samples.

A particularly strong absorption at 1718 cm -1 was used in the TA models in both NF and FD samples.

Concerning the main individual sugars and acids (sucrose, fructose and malic acid), ATR-FTIR on FD samples provided more accurate prediction results (Rcv 2 >0.87 and RPD>3.2) than on NF samples (Rcv 2 >0.79 and RPD>2.3). For fructose and sucrose, the regression coefficients of the models showed numerous characteristic peaks in the region 1150-900 cm -1 in FD samples. But, despite the similar typical peaks, specific peaks such as 1034 cm -1 for sucrose and 1084 cm -1 for fructose were detected and used in their respective models. The lower RPD and the higher RMSECv in NF than in FD samples were due to the presence of water leading to a lower concentration of components and then a lower sensitivity to their variations. Moreover, to obtain the best prediction of sugars in fresh samples, the spectral region 1700-1550 cm -1 specific to soluble substances, was useful. In fresh samples, the linear models for TA, SSC, DMC and malic acid prediction depended foremost on the sugar absorption (fructose and sucrose), because of their relatively higher total concentrations (99.4-228.9 g/kg FW) than those of acids (TA: 25-109.1 meq H + /kg FW). After freeze-drying, the specific spectral area (1725-1710 cm -1 ) corresponding to acidity [START_REF] Clark | Fast determination by Fourier-transform infrared spectroscopy of sugar-acid composition of citrus juices for determination of industry maturity standards[END_REF] became the main area of PLS models, due to their larger variations during storage than those of individual sugars.

Another quality trait of interest is the AIS contents, which contributes to the rheological properties of the processed apple purees products [START_REF] Espinosa-Muñoz | The significance of structural properties for the development of innovative apple puree textures[END_REF]. The prediction of AIS contents is acceptable with RPD of 3.3 on FD purees, when expressed in dry matter (DW). Its prediction was not possible directly on NF purees. The significant signals at 985 cm -1 corresponding to CH stretching of cellulose [START_REF] Fahey | Predicting the cell-wall compositions of Pinus radiata (radiata pine) wood using ATR and transmission FTIR spectroscopies[END_REF] and at 1147 cm -1 for C-O-C vibration of glycosidic bound between uronic acids [START_REF] Coimbra | Multivariate analysis of uronic acid and neutral sugars in whole pectic samples by FT-IR spectroscopy[END_REF] were in line with the previous PLS models built to predict AIS yield in freeze-dried fruit and vegetables [START_REF] Canteri | ATR-FTIR spectroscopy to determine cell wall composition: Application on a large diversity of fruits and vegetables[END_REF].

Briefly, ATR-FTIR technique worked well to evaluate global quality traits of interest in apple purees: SSC, TA and DMC. The prediction of cell wall contents (AIS) was possibility only on freeze-dried apple purees. Concerning the detailed composition including the individual components, the prediction was possible directly on fresh puree for malic acid whereas the prediction of the main individual sugars (fructose and sucrose) required the puree freeze-drying. The prediction of glucose was not acceptable in apple purees whatever the tested conditions. Surprisingly, prediction was acceptable (Rcv 2 >0.87, RPD >3.1) for rheological parameters such as puree viscosity (η50 or η100) and visco-elasticity (G', G'' in both amplitude and frequency sweep tests and yield stress) on FD samples with less than 10 LVs and was better than on NF and AIS samples (Table 2). The single shear rate value at 50/s (η50) has been described to be the best correlated with the in-mouth texture perception of fluid foods (Chen & Engelen, 2012). For the two parameters measured at η50 and η100, predictions were better in FD samples than in NF and AIS samples. Particularly, two main spectral areas (1718 cm -1 and 1620-1595 cm -1 ) in NF and FD samples appeared to be highly relevant to predict the puree viscosity.

Differently, in AIS samples, the two major peaks (1018 cm -1 and 1110 cm -1 ) linked to the viscosity prediction have been conventionally attributed to the pectin changes in fruit cell walls [START_REF] Coimbra | Multivariate analysis of uronic acid and neutral sugars in whole pectic samples by FT-IR spectroscopy[END_REF]. For the specific viscoelastic parameters of purees (AS-G', AS-G'' and yield stress) by amplitude sweep tests, their prediction by ATR-FTIR was excellent in FD samples with RPD values higher than 3.4. The yield stress, corresponding to the moment when the puree starts to flow at the macroscopic level, could be predicted directly on NF purees with the better RPD and RMSECv than on FD samples. From frequency sweep tests (FS), the gel-like behaviors (FS-G' > FS-G'') of all purees could be well estimated in FD samples (Rcv 2 > 0.90), even with a large variation of FS-G' and FS-G'' (Table S-3). Surprisingly, fresh NF samples were the suitable sample type to evaluate the particle size, both d(4:3) and d(3:2), with a good performance of the PLS models (RPD>3.0).

Although acceptable results of PLS regression were obtained on the three sample types for the prediction of puree rheological properties (viscosity and viscoelasticity) and particle information (sizes and volume), it is worth signaling the differences of their fingerprint peaks: i) for fresh NF samples, the major region between 1750 and 1500 cm -1 was attributed to the absorbed water and complex soluble substances (pectins, polyphenols and proteins); ii) for cell wall AIS extracts, the typical peaks (1018 cm -1 , 1083 cm -1 ) were mainly related to their pectic and phenolic variations; iii) for freeze-dried FD samples, the specific peaks, 1500-1750 cm -1 and 1200-900 cm -1 , combining with those observed separately in NF and AIS samples were used. The limited spectral sensitivity for the fresh suspensions (NF) and the restricted variations for the cell wall extracts (AIS) resulted in a less accurate prediction of the rheological behaviors than for freeze-dried FD samples. These results demonstrated the possibility of ATR-FTIR technique to accurately estimate viscosity, elasticity and the particle distributions directly on freeze-dried purees (FD). However, ATR-FTIR on fresh purees (FD) had a good ability to directly evaluate the particle size and properties (RPD>3.0), and also can probably to be used to evaluate the rheological behaviors (viscosity and viscoelasticity) according the results of RPD values over 2.5 [START_REF] Nicolai | Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review[END_REF].

Conclusion

As far as we know, this is the first report concerning the assessment of quality variations in fruit products during processing depending on ATR-FTIR spectral information of the same samples but characterized as fresh, freeze-dried and cell wall extracts. Direct spectral measurements on fresh samples could provide a reliable assessment of texture and major composition characteristics of purees. Thus, ATR-FTIR technique can be adapted to routine analysis in fruit industries, a simple method, using few steps for manufacturers. Long-time freeze-drying preparations still keep the stability and consistency of the ATR-FTIR signals in comparison with those of fresh samples, and provided more detailed assessments of rheological properties and cell wall contents. ATR-FTIR on cell wall materials was the only way to identify the variations of cell wall compositions, but not enough to overview the changes during fruit processing.

Briefly, ATR-FTIR associated with suitable sample pre-treatments in fruit processing could offer sufficient information for the industrial and research demands.

Balancing the pre-treated methods to stabilize samples and knowing the potential ability of infrared spectroscopy are both crucial for rapid and accurate analyses in fruit processing. Based on our results, future works could be extended to a wide span of complex processing strategies (drying, juicing, fermentation etc.) and/or operational units. 1. Prediction of apple processed purees composition using the leave-one-out PLS regression based on the fresh ('NF') and freeze-dried ('FD') ATR-FTIR spectra and reference data. -1065, 985-995, 1030-1035, 1142-1150, 1165-1193, 1096-1101 Puree spectra and reference data from two varieties ('Granny Smith', 'Golden Delicious') with different thinning conditions, a cold storage (during 0, 1, 3 and 6 months) and two puree refining conditions. Spectral area: 1800-900 cm -1 and spectrum pre-processing: baseline-correction and SNV.

  ) using XLSTAT(version 2018.5.52037, Addtionsoft SARL, Paris, France) data analysis toolbox.

  2) and their PCA results (Figure S-1), the mechanical refining resulted a clear reduction of cell wall contents (AIS in DW and FW), viscosity (η50 and η100), viscoelasticity (yield stress, G' and G'' in both oscillatory tests), particle size (d

Figure captions Figure 1 .

 captions1 Figure captions

Figure 2 .

 2 Figure 2. PCA on the SNV pre-treated ATR-FTIR spectra (900-1800 cm -1 )of purees

Figure 3 .

 3 Figure 3. FDA on the SNV pre-treated ATR-FTIR spectra (900-1800 cm -1 ) of

Figure 4 .

 4 Figure 4. Maps of Factorial Discriminant Analysis (FDA) performed on the

  Figures

  649

  Figure 2

Acknowledgements

The authors thank Patrice Reling, Barbara Gouble, Line Touloumet, Marielle Bogé, Caroline Garcia, Gisèle Riqueau and Xuwei Liu (INRAE, SQPOV group) for their technical help. The 'Interfaces' project is an Agropolis Fondation Flashship project publicly funded through the ANR (French Research Agency) under "Investissements d'Avenir" programme (ANR-10-LABX-01-001 Labex Agro, coordinated by Agropolis Fondation). Weijie Lan was supported by a doctoral grant from Chinese Scholarship Council.

Table 2 Prediction of apple processed purees rheological parameters and textural properties using the leave-one-out PLS regression based on the 659 fresh (NF), freeze-dried (FD) and cell wall (AIS) ATR-FTIR spectra and reference data.