Method for evaluating latex composition

Abstract

To provide a method for evaluating a latex and an obtained rubber product utilizing comprehensive analysis of the latex.SOLUTION: A method for evaluating a latex composition includes a step A of performing comprehensive mass spectrometry of constituent molecules of the latex composition to obtain an analysis result, and a step B of analyzing the relationship between the analysis result obtained in the step A and information on the latex composition. A method for predicting the qualities and / or properties of a rubber composition includes a step a1 of analyzing a latex composition as a reference material by the evaluation method to obtain an analysis result on the relationship between the analysis result and information on the latex composition, and a step b1 of comprehensively analyzing a latex composition as a test material to predict the qualities and / or properties of a rubber composition obtained from the latex composition as the test material by comparison with the analysis result obtained in the step a1.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a method for evaluating a latex composition, and more particularly to a method for evaluating a latex composition using comprehensive mass analysis of constituent molecules of the latex composition, a method for selecting evaluation markers, and a method for predicting the quality and / or properties of a rubber composition using these evaluations. [Background technology]

[0002] Natural rubber is a rubber material produced primarily from the sap of the rubber tree (Hevea brasiliensis), known as latex (Non-Patent Document 1). Natural rubber is known to have superior mechanical properties compared to petroleum-derived synthetic rubber, and is used in a wide range of industries, including transportation equipment and medical care (Non-Patent Document 2). For example, natural rubber is used in the tires of large trucks and aircraft due to its excellent abrasion resistance and elasticity.

[0003] Natural rubber contains the main component cis-polyisoprene and non-rubber components such as proteins, sugars, lipids, etc. It has been reported that the non-rubber components include allergens (Non-Patent Document 3) and components that affect the viscosity and stability of solid natural rubber (Non-Patent Document 4). [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Mooibroek, H.; Cornish, K. Alternative Sources of Natural Rubber. Applied Microbiology and Biotechnology 2000,53(4),355-365.https: / / doi.org / 10.1007 / s002530051627. [Non-patent document 2] Toki, S.; Che, J.; Rong, L.; Hsiao, BS; Amnuaypornsri, S.; Nimpaiboon, A.; Sakdapipanich, J. Entanglements and Networks to Strain-Induced Crystallization and Stress-Strain Relations in Natural Rubber and Synthetic Polyisoprene at Various Temperatures.Macromolecules 2013, 46(13), 5238-5248. https: / / doi.org / 10.1021 / ma400504k. [Non-patent document 3] Yeang, HY; Arif, SAM; Yusof, F.; Sunderasan, E. Allergenic Proteins of Natural Rubber Latex. Methods 2002, 27(1), 32-45. https: / / doi.org / 10.1016 / S1046-2023(02)00049-X. [Non-patent document 4] Nimpaiboon,A.;Sriring,M.;Kumarn,S.;Sakdapipanich,J.Reducing and Stabilizing the Viscosity of Natural Rubber by Using Sugars:Interference of the Maillard Reaction between Proteins and Sugars.Journal of Applied Polymer Science 2020, 137(45), 49389. https: / / doi.org / 10.1002 / app.49389. Summary of the Invention [Problem to be solved by the invention]

[0005] However, the results of a comprehensive analysis of the components contained in rubber trees and their relationship to the product, natural rubber, are unknown.

[0006] An object of the present invention is to provide a method for evaluating latex and the resulting rubber products using comprehensive analysis of the latex. [Means for solving the problem]

[0007] The present invention provides the following: [1] Step A: A step of performing comprehensive mass analysis of the constituent molecules of the latex composition and obtaining the analysis results; and Step B: A step of analyzing the relationship between the analysis results obtained in Step A and information about the latex composition; A method for evaluating a latex composition, comprising: [2] Step A: performing comprehensive mass analysis of the constituent molecules of the latex composition and obtaining the analysis results; Step B: A step of analyzing the relationship between the analysis results obtained in Step A and information about the latex composition; and Step C: A step of identifying, as an evaluation marker, a component of the latex composition associated with at least one piece of information about the latex composition from the analysis result of Step B. A method for selecting an evaluation marker for a latex composition, comprising: [3] Step a1: A step of analyzing a latex composition as a standard substance by the method described in [1], and obtaining an analysis result relating the analysis result to information about the latex composition; and Step b1: A step of comprehensively analyzing a latex composition as a test substance and predicting the quality and / or properties of a rubber composition obtained from the latex composition as the test substance by comparing the analysis results obtained in step a1 with those obtained in step b1. A method for predicting the quality and / or properties of a rubber composition, comprising: [4] Step a2: A step of determining an evaluation marker for the latex composition as a standard substance by the method described in [2]. Step b2: A step of predicting the quality and / or properties of a rubber composition obtained from the latex composition as the test substance by performing a comprehensive analysis of the latex composition as the test substance and confirming the presence or amount of the evaluation marker obtained in step a2. A method for predicting the quality and / or properties of a rubber composition, comprising: [5] The method according to any one of [1] to [4], wherein the analytical results obtained in step A are analytical results of 40 or more constituent molecules of the latex composition. [6] The method according to any one of [1] to [5], wherein the analytical results obtained in step A are analytical results of 400 or more constituent molecules of the latex composition. [7] The method according to any one of [1] to [6], wherein the information about the latex composition includes a relationship between one or more physical properties of a rubber composition obtained from the latex composition and constituent molecules. [8] The method according to [7], wherein the physical properties of the rubber composition include one or more properties selected from Mooney scorch, vulcanization characteristics, mechanical strength, and heat aging resistance. [9] The method according to any one of [1] to [8], wherein the comprehensive mass spectrometry is metabolomic analysis.

[10] The method according to any one of [1] to [9], wherein the comprehensive mass analysis is an analysis by LC-TOFMS and / or CE-TOFMS.

[11] The method according to [9] or

[10] , wherein the results of the comprehensive mass analysis are expressed by one or more of the following: peak area ratio, the presence or absence of metabolites, and the content of metabolites.

[12] The method according to any one of [1] to

[11] , wherein the analysis is a multivariate analysis.

[13] The method according to any one of [1] to

[12] , wherein the analysis is a hierarchical clustering analysis. [Effects of the Invention]

[0008] According to the present invention, comprehensive analysis of latex compositions can be utilized to evaluate latex compositions and the resulting rubber compositions. Therefore, the present invention can be utilized to select rubber compositions suitable for the latex composition and to select latex compositions as raw materials for rubber compositions having desired performance. Furthermore, the present invention enables the improvement of the physical properties of rubber compositions by adding predetermined components, which is useful for revitalizing the rubber industry and rubber manufacturing industry. [Brief explanation of the drawings]

[0009] [Figure 1] Figure 1 shows the regression accuracy of a multiple regression model for training data. The vertical axis represents predicted values, and the horizontal axis represents measured values. [Figure 2] Figure 2 shows the regression accuracy of the multiple regression model for test data. The vertical axis represents predicted values, and the horizontal axis represents measured values. Black circles represent plots of test data, and white circles represent plots of training data. [Figure 3] FIG. 3 is a diagram showing the effect of improving variability in test data when changing the composition. DETAILED DESCRIPTION OF THE INVENTION

[0010] 1. Evaluation method of latex composition The evaluation method of the latex composition includes the following steps A and B.

[0011] [1.1 Process A] Step A is a step of performing comprehensive mass analysis of the constituent molecules of the latex composition and obtaining the analysis results.

[0012] -Latex composition- The object of analysis in step A is a latex composition. In this specification, the term "latex composition" refers to an aqueous dispersion derived from the sap of a rubber plant, and refers to a composition containing a polymer, which is a rubber component, as well as non-rubber components. An example of a rubber plant is a rubber tree (mainly Hevea brasiliensis). The latex composition may be the sap itself of the rubber plant, or may be a processed sap (e.g., processed by adding a solvent, concentrating, etc.), and may contain additives such as coagulation inhibitors, preservatives, and stabilizers, as necessary.

[0013] -Constituent molecules of latex composition- The constituent molecules of the latex composition include polymers, which are so-called rubber components, as well as non-rubber components. Examples of non-rubber components include metabolites of rubber-producing plants, such as nucleic acids, lipids, proteins, peptides, amino acids, sugars, glycoproteins, their salts, metabolic intermediates, decomposition products, fragments, and trace metals. Specific examples include the following (1) to (443). These metabolites were extracted in the metabolome analysis described in the Examples below. (Note that (399) to (401) and (403) to (411) are compounds of unknown structure.)

[0014] (1)1,2,3-Propanetricarboxylic acid (2)1,2-Distearoyl-glycero-3-phosphocholine (3) 1,3-Diaminopropane (4)10-Hydroxyoctadecanoic acid (5)15-Deoxy-Δ12,14-prostaglandin J2 (6)16-Hydroxyhexadecanoic acid (7) 17α-Estradiol (8) 17α-Hydroxyprogesterone (9)19-Methylarachidic acid; Heneicosanoic acid (10)1-Deoxyjirimycin (11)1-Deoxysphinganine (12)1-Methyl-4-imidazoleacetic acid (13)1-Methyladenosine (14)1-Oleoyl-glycero-3-phosphocholine (15)1-Palmitoyl-glycero-3-phosphocholine (16)1-Stearoyl-glycero-3-phosphocholine (17)2,4-Diaminobutyric acid (18)22-Hydroxycholesterol (19)2-Aminoadipic acid;O-Acetylhomoserine;Glutamic acid γ-methyl ester (20)2-Aminoisobutyric acid;2-Aminobutyric acid (21)2’-Deoxycytidine (22)2-Deoxyribonic acid (23)2-Hydroxy-4-methylvaleric acid;2-Hydroxy-3-methylvaleric acid (24)2-Hydroxydecanoic acid (25)2-Hydroxyglutaric acid (26)2-Hydroxyhexadecanoic acid (27)2-Hydroxyisovaleric acid;2-Hydroxyvaleric acid (28)2-Hydroxyoctadecanoic acid (29)2-Hydroxypyridine (30)2-Hydroxytetradecanoic acid (31)2-Methylserine (32)2’-O-Methylcytidine (33)2-Oxobutyric acid (34)2-Oxoglutaric acid (35)2-Oxoisovaleric acid (36)3-(3,4-Dihydroxyphenyl)-2-methylalanine;3-Methoxytyrosine (37)3,4-Dihydroxyphenylglycol (38)3-Amino-2-piperidone (39)3-Aminopropane-1,2-diol (40)3-Aminopropionitrile (41)3’-AMP(Adenosine monophosphate) (42)3-Deoxy-D-manno-2-octulosonic acid (43)3-Hydroxy-2-methyl-4-pyrone (44)3-Hydroxy-3-methylglutaric acid (45)3-Hydroxyanthranilic acid (46)3-Hydroxybutyric acid (47)3-Hydroxydodecanoic acid (48)3-Hydroxyhexadecanoic acid (49)3-Hydroxyproline (50)3-Hydroxypropionic acid (51)3-Hydroxytetradecanoic acid (52)3-Methoxy-4-hydroxyphenylethyleneglycol (53)3-Methylguanine (54)3-Methylhistidine;1-Methylhistidine (55)3-Nitropropionic acid (56)3-Nitrotyrosine (57)3-Phenylpropionic acid (58)3-Phosphoglyceric acid (59)3’-UMP(Uridine monophosphate) (60)3-Ureidoisobutyric acid (61)3β-Hydroxy-5-cholestenoic acid (62)4-(β-Acetylaminoethyl)imidazole (63)4-Amino-3-hydroxybutyric acid (64)4-Guanidinobutyric acid (65)4-Methylaminobutyric acid;5-Aminovaleric acid (66)4-Methylpyrazole (67)4-Oxopyrrolidine-2-carboxylic acid (68)5-Amino-3,4-dihydro-2H-pyrrole-2-carboxylic acid (69)5-Hydroxylysine (70)5-Methyl-2’-deoxycytidine (71)5-Methylcytidine (72)5-Methylcytosine (73)5-Oxoproline (74)5α-Cholestan-3-one (75)6-Gingerol (76)6-Keto-prostaglandin E1 (77)6-Phosphogluconic acid (78)7-Dehydrocholesterol (79)9(S)-HODE(9S-Hydroxy-10E,12Z-octadecadienoic acid) (80)Abietic acid (81)AC(18:1)(Acylcarnitine(18:1)) (82)Acylcarnitine(18:1) (83)Acylcarnitine(20:1) (84)Adenine (85)Adenosine (86)Adenylosuccinic acid (87)ADMA(Asymmetric dimethylarginine) (88)AEA(18:1)(Arachidonyl Ethanolamide(18:1));Oleoyl ethanolamide (89)AEA(18:3) (90)AEA(20:3) (91)AEA(22:4) (92)AEA(22:6) (93)Ala (94)Ala-Ala;XC0145 (95)Albendazole (96)Allantoic acid (97)allo-Threonine (98)Aminoacetone (99)AMP(Adenosine monophosphate) (100)Anandamide (101)Arachidic acid (102)Arachidonic acid (103)Arg (104)Argininosuccinic acid (105)Ascorbate 2-glucoside (106)Asn (107)Asp (108)Behenic acid (109)Betaine (110)Betaine aldehyde +H2O (111)Betonicine (112)Biotin (113)Bisacurone (114)Butyric acid;Isobutyric acid (115)Cadaverine (116)Caffeine (117)Campesterol (118)Carboxymethyllysine (119)Carnitine (120)Cholesterol sulfate (121)Choline (122)cis-10-Nonadecenoic acid (123)cis-11,14-Eicosadienoic acid (124)cis-11-Eicosenoic acid (125)cis-4-Hydroxyproline (126)cis-5,8,11,14,17-Eicosapentaenoic acid (127)cis-8,11,14-Eicosatrienoic acid (128)cis-Aconitic acid (129)Citric acid (130)Citrulline (131)CMP(Cytidine monophosphate) (132)CMP-N-acetylneuraminate (133)Coenzyme Q10 (134)Creatinine (135)Cystathionine (136)Cysteine glutathione disulfide (137)Cystine (138)Cytidine (139)Cytosine (140)Decanoic acid (141)Dehydrozingerone (142)Deoxycorticosterone (143)Desmosterol (144)Dimethylaminoethanol (145)Docosanedioic acid (146)Ectoine (147)Eleutheroside B (148)Ergothioneine (149)Erucic acid (150)Ethanolamine (151)Ethanolamine phosphate (152)Ethyl arachidonate (153)Ethyl glucuronide (154)Ethylacetimidate (155)Etiocholan-3α-ol-17-one (156)Fatty acid(12:0) (157)Fatty acid(14:1) (158)Fatty acid(14:2) (159)Fatty acid(14:3) (160)Fatty acid(15:1) (161)Fatty acid(16:2) (162)Fatty acid(16:3) (163)Fatty acid(17:1) (164)Fatty acid(17:2) (165)Fatty acid(17:3) (166)Fatty acid(19:0) (167)Fatty acid(19:1) (168)Fatty acid(19:2) (169)Fatty acid(24:0) (170)Flavanone (171)Fructose 6-phosphate (172)Fumaric acid (173)GABA(γ-Aminobutyric acid) (174)Gibberellic acid (175)Glabridin (176)Gln (177)Glu (178)Glucaric acid (179)Gluconic acid (180)Gluconolactone (181)Glucosamine (182)Glucosamine 6-phosphate (183)Glucosaminic acid (184)Glucose 1-phosphate (185)Glucose 6-phosphate (186)Glucosylceramide(d18:1 / 24:1) (187)Glu-Glu (188)Glutaric acid;Methylsuccinic acid (189)Glutathione(GSSG)divalent (190)Gly (191)Gly-Asp (192)Glyceric acid (193)Glycerol (194)Glycerol 2-phosphate (195)Glycerol 3-phosphate (196)Glycerophosphocholine (197)Glycochenodeoxycholic acid (198)Gly-Gly (199)Gly-Leu (200)GMP(Guanosine monophosphate) (201)Guanidinosuccinic acid (202)Guanidoacetic acid (203)Guanine (204)Guanosine (205)Gulonolactone (206)H-Asp(Gly-OH)-OH (207)Hecogenin (208)Heptadecanoic acid;Fatty acid(17:0) (209)Hercynine (210)Hexadecanedioic acid (211)Hexanoic acid (212)Hexylamine (213)His (214)Histamine (215)Homoarginine (216)Homocitric acid (217)Homocitrulline (218)Homoserine (219)Hydroxyprogesterone caproate (220)Hydroxyproline (221)Hyodeoxycholic acid (222)Hypotaurine (223)Hypoxanthine (224)IDP(Inosine diphosphate) (225)Ile (226)Imidazole-4-methanol (227)Imidazolelactic acid (228)Iminodiacetic acid (229)IMP(Inosine monophosphate) (230)Indole-3-carboxaldehyde (231)Inosine (232)Isethionic acid (233)Isocitric acid (234)Isofraxidin (235)Isoglutamic acid (236)Isopropanolamine (237)Isovaleric acid;DL-2-Methylbutyric acid;Valeric acid (238)Kynurenic acid (239)Lactic acid (240)Lanosterol;Cycloartenol (241)Lathosterol;Cholesterol (242)Lauric acid (243)Leu (244)Lignoceric acid (245)Linoleic acid (246)Linolenic acid;γ-Linolenic acid (247)Linoleyl ethanolamide (248)Lipoamide (249)LPE(16:0);1-Palmitoyl-glycero-3-phosphoethanolamine (250)LPG(16:0)(Lysophosphatidylglycerol(16:0)) (251)Lutein (252)Lys (253)Malic acid (254)Mannosamine (255)meso-Tartaric acid (256)Met (257)Methionine sulfoxide (258)Methoxamine (259)Mucic acid (260)myo-Inositol 2-phosphate (261)myo-Inositol 3-phosphate;myo-Inositol 1-phosphate (262)Myristic acid (263)Myristoleic acid (264)N-(1-Deoxy-1-fructosyl)valine (265)N’-Formylkynurenine (266)N1-Acetylspermidine (267)N1-Methylguanosine (268)N2,N2-Dimethylguanosine (269)N5-Ethylglutamine (270)N6,N6,N6-Trimethyllysine (271)N6-Acetyllysine (272)N6-Methyladenine (273)N6-Methyladenosine (274)N6-Methyllysine (275)N-Acetylasparagine (276)N-Acetylglucosamine 1-phosphate (277)N-Acetylglucosamine;N-Acetylgalactosamine;N-Acetylmannosamine (278)N-Acetylglucosylamine (279)N-Acetylglutamic acid (280)N-Acetylhistidine (281)N-Acetylornithine (282)N-Acetylproline (283)N-Acetylputrescine (284)N-Acetylserine (285)N-Acetylthreonine (286)N-Acetyl-β-alanine;N-Acetylalanine (287)N-Amidinoglutamic acid (288)N-Ethylglycine (289)N-Hexanoylsphingosine (290)Nicotinamide (291)Nicotinamide riboside (292)Nicotinic acid (293)N-Methylalanine (294)N-Methylanthranilic acid (295)N-Methylaspartic acid (296)N-Methylglutamic acid (297)N-Methylproline (298)N-Oleoylglycine (299)Nω-Methylarginine (300)Octadecanedioic acid (301)Octanoic acid (302)Octopamine;Dopamine (303)o-Hydroxybenzoic acid (304)Oleamide (305)Oleic acid (306)Ophthalmic acid (307)Ornithine( (308)Oxalic acid (309)Oxamic acid (310)PAF(17:0)(Platelet-activating factor(17:0)) (311)Palmitic acid (312)Palmitoleic acid (313)Palmitoylcarnitine (314)Palmitoylcholine (315)Palmitoylethanolamide (316)Pantothenic acid (317)Pelargonic acid (318)Pentadecanoic acid (319)Phe (320)Phosphorylcholine (321)Phytosphingosine (322)Pipecolic acid (323)Piperidine (324)Pro (325)Propionic acid (326)Prostaglandin B2 (327)Putrescine (328)Pyrazole (329)Pyridoxal (330)Pyridoxine (331)Pyroglutamine (332)Pyrrole-2-carboxylic acid (333)Pyruvic acid (334)Quinic acid (335)Retinol (336)Riboflavin (337)Ribulose 5-phosphate (338)Ricinoleic acid (339)Saccharopine (340)S-Adenosylhomocysteine (341)Sarcosine (342)S-Carboxymethylcysteine (343)SDMA (344)Ser (345)Ser-Glu (346)Shikimic acid (347)Sitosterol (348)S-Methylglutathione (349)S-Methylmethionine (350)Spermidine (351)Spermine (352)Sphinganine (353)Sphinganine(d20:0) (354)Sphinganine(d22:0) (355)Sphingomyelin(d18:1 / 16:0) (356)Sphingomyelin(d18:1 / 18:0) (357)Sphingosine (358)Sphingosine(d20:1) (359)S-Sulfocysteine (360)Stachydrine (361)Stearic acid (362)Stearidonic acid (363)Stearoyl ethanolamide (364)Stigmasterol (365)Succinic acid (366)Succinyladenosine (367)Tartaric acid (368)Taurolithocholic acid 3-sulfate (369)Terephthalic acid (370)Testosterone acetate (371)Tetradecanedioic acid (372)Theobromine (373)Thiaproline (374)Thr (375)Thr-Asp (376)threo-3-Hydroxyaspartic acid (377)Threonic acid (378)threo-β-Methylaspartic acid (379)Thymidine (380)trans-Glutaconic acid (381)Tricosanoic acid (382)Tridecanoic acid (383)Trigonelline (384)Trilaurin (385)Trimethylamine (386)Trimethylamine N-oxide (387)Triptolide (388)Tropic acid (389)Trp (390)Tryptamine (391)Tyr (392)Tyramine (393)Tyrosine methyl ester (394)UMP(Uridine monophosphate) (395)Uracil (396)Uridine (397)Urocanic acid (398)Val (399)XA0004 (400)XA0033 (401)XA0065 (402)Xanthine (403)XC0016 (404)XC0029 (405)XC0040 (406)XC0065 (407)XC0071 (408)XC0089 (409)XC0126 (410)XC0144 (411)XC0154 (412) Xylulose 5-phosphate; Ribose 1-phosphate (413)Zeaxanthin (414)α-Tocopherol (415)α-Tocopherol acetate (416)β-Ala (417)β-Cryptoxanthin (418)β-Cyanoalanine (419)β-Estradiol (420)β-Hydroxyisovaleric acid (421)γ-Butyrobetaine (422)γ-Glu-Ala (423)γ-Glu-Arg divalent (424)γ-Glu-Asn (425)γ-Glu-Asp (426)γ-Glu-Citrulline (427)γ-Glu-Gln (428)γ-Glu-Glu (429)γ-Glu-Gly (430)γ-Glu-His (431)γ-Glu-Leu;γ-Glu-Ile (432)γ-Glu-Lys divalent (433)γ-Glu-Met (434)γ-Glu-Ornithine;H-Asp(Lys-OH)-OH (435)γ-Glu-Phe (436)γ-Glu-Ser (437)γ-Glutamyl-S-Allylcysteine (438)γ-Glu-Thr (439)γ-Glu-Trp (440)γ-Glu-Tyr (441)γ-Glu-Val (442)γ-Glu-Val-Gly (443)γ-Tocopherol

[0015] The number of constituent molecules to be analyzed may be at least one, preferably two or more, more preferably three or more, still more preferably four or more, and may be 40 or more, 100 or more, 200 or more, 300 or more, or 400 or more. The analysis target preferably includes at least one non-rubber component, and it is preferable that those highly related to information on the latex composition used for analysis in step B are preferentially included.

[0016] -Comprehensive mass analysis- Comprehensive mass analysis refers to a comprehensive analysis using the masses of the constituent molecules contained in the latex composition. Examples include metabolomic analysis, proteomic analysis, lipidomic analysis, and glycomic analysis, with metabolomic analysis being preferred. Various mass spectrometry (MS) methods can be used for mass analysis, including time-of-flight (TOF), quadrupole, double-focusing, and ion cyclotron resonance mass spectrometry. Specific examples include LC-TOFMS, CE-TOFMS, GC-MS, LC-MS, and UPLC-QTOFMS. TOF-based mass spectrometry is preferred, with LC-TOFMS and CE-TOFMS being more preferred. The analysis results typically provide comprehensive quantitative data on the masses of the constituent molecules of the latex composition. Quantitative data can be obtained, for example, by calculating the relative area values ​​of each peak in a mass spectrum or by calculating the volume of a conical peak from the measured mass spectrum data in three dimensions: mass, time, and intensity. These processes can be performed using appropriate software used in comprehensive mass spectrometry (e.g., software included with a metabolome analysis system). When using a commercially available analytical system for metabolome analysis, the system usually comes with software for calculating relative quantitative values, and such software can be used.

[0017] [1.2 Process B] Step B is a step of analyzing the relationship between the analysis results obtained in step A and information related to the latex composition.

[0018] -Information about latex composition- The information about the latex composition is not particularly limited as long as it is known information about the latex composition. For example, the relationship between data on the mass of one or more constituent molecules of the latex composition (preferably the mass of two or more constituent molecules) and the physical properties of the resulting rubber composition can be mentioned. The mass data may be data on the mass itself, the content ratio in the composition, or the mass ratio of two or more constituent molecules, or may be quantitative data processed in the same manner as the quantitative data obtained in step A. The rubber composition is a processed product of a latex composition, and refers to any of raw rubber (coagulated rubber), master batch (kneaded rubber), and vulcanized rubber. The physical properties of the rubber composition may be any physical properties related to rubber compositions. Examples include processing stability, vulcanization characteristics, mechanical strength, heat aging resistance, heat resistance, cold resistance, aging resistance, ozone resistance, weather resistance, heat resistance, dielectric constant, chemical resistance, oil resistance, and water resistance. Of these, processing stability, vulcanization characteristics, mechanical strength, and heat aging resistance are preferred.

[0019] Processing stability can be measured using Mooney scorch (Mooney viscosity (M1+3) 3 minutes after starting rotation after 1 minute of preheating, minimum Mooney viscosity (Vm), scorch time st5 (the time it takes for the viscosity to rise 5 units from Vm), scorch time st10 (the time it takes for the viscosity to rise 10 units from Vm), st10-st5). Vulcanization characteristics can be measured using the maximum stress (MH), minimum stress (ML), s0.4 (the time it takes for the stress to rise 0.4 units from ML), induction time (T10: the time when the stress reaches ML + (MH - ML) × 0.1), 50% cure time (T50: the time when the stress reaches ML + (MH - ML) × 0.5), 90% cure time (T90: the time when the stress reaches ML + (MH - ML) × 0.9), cure rate (T90 - T10), time to reach MH (tMH), and time to reach ML (tML). The mechanical strength can be obtained as, for example, modulus, tensile strength, and elongation at break. The heat aging resistance can be obtained as, for example, strength (modulus, tensile strength, and elongation at break) after aging treatment (e.g., 85°C, 72 hours, 240 hours, or 500 hours).

[0020] -analysis- The analysis can be performed by known methods, such as machine learning, deep learning, supervised and unsupervised data analysis, and clustering techniques (e.g., multivariate analysis). Examples of multivariate analysis include multiple regression analysis, logistic regression analysis, principal component analysis, independent component analysis, factor analysis, discriminant analysis, quantification theory, cluster analysis, conjoint analysis, multidimensional scaling (MDS), partial least squares discriminant analysis (PLS-DA), random forest, decision tree, support vector machine (SVM), k-nearest neighbor analysis, naive Bayes, linear regression, polynomial regression, SVM for regression, k-means clustering, and hidden Markov model. Multiple regression analysis is preferred. For example, it can be performed by comparing information about the latex composition prepared in advance using a test sample with a linear multiple regression model (multiple regression equation). Prior to the multiple regression analysis, explanatory variables (quantitative numerical data obtained by metabolome analysis) and response variables (physical property data of the rubber composition) may be standardized using an appropriate standardization method. Furthermore, quantitative numerical data may be selected and extracted based on a certain standard (for example, data with little variation) and used in multiple regression analysis.

[0021] The machine learning analysis can utilize one or more machine learning algorithms to correlate the results of the analysis of the constituent molecules contained in the latex composition with information about the latex composition. For example, an algorithm can be trained to receive the results of the analysis of the constituent molecules contained in the latex composition and output information about the latex composition.

[0022] 2. Method for selecting evaluation markers for latex compositions The above evaluation method can be used to select an evaluation marker for a latex composition. Such a selection method includes step C in addition to steps A and B described above.

[0023] [2.1 Process C] Step C is a step of identifying, from the analysis result of step B, a component of the latex composition associated with at least one piece of information about the latex composition as an evaluation marker. The evaluation marker can be specified by selecting at least one component highly related to information about the latex composition from among the constituent molecules in the statistical processing in step B. For example, a component whose content is greater or less than that of a rubber composition having a predetermined high physical property can be selected.

[0024] 3. Method for predicting the quality and / or properties of a rubber composition The above-mentioned evaluation method and marker selection method can be used to evaluate the quality and / or properties of a rubber composition. That is, the method for evaluating the quality and / or properties of a rubber composition includes the following steps a1 and b1, or steps a2 and b2. Step a1: A step of analyzing a latex composition as a standard substance by the method of claim 1, and obtaining an analysis result relating the analysis result to information about the latex composition; Step b1: A step of comprehensively analyzing a latex composition as a test substance and predicting the quality and / or properties of a rubber composition obtained from the latex composition as the test substance by comparing the analysis results obtained in step a1 with those obtained in step b1. Step a2: A step of determining an evaluation marker for the latex composition as a standard substance by the method of claim 2. Step b2: A step of predicting the quality and / or properties of a rubber composition obtained from the latex composition as the test substance by performing a comprehensive analysis of the latex composition as the test substance and confirming the presence or amount of the evaluation marker obtained in step a2.

[0025] In steps b1 and b2, the quality of the rubber composition refers to a physical property evaluated in a specific application of the rubber composition, and is selected from the above-mentioned physical properties of the rubber composition depending on the application. The characteristics of the rubber composition refer to the appropriate application of the rubber composition. [Example]

[0026] The present invention will be described below with reference to examples, but the following examples are not intended to limit the present invention.

[0027] Example 1 Multiple regression analysis of tensile properties in training data [Sampling and sample preservation] Latex was collected from multiple rubber trees on a plantation in Thailand over a 10-day period between May 2022 and January 2023. The latex collected from each plant on each collection day was mixed and designated samples 1 to 10 (for metabolome analysis and characteristic testing, respectively). Samples for metabolome analysis were doped with ammonia to prevent solidification, transported domestically at ambient temperature, and stored at -4°C. Samples for characteristic testing were similarly doped with ammonia, transported domestically at ambient temperature, and then stored at room temperature with the addition of a preservative (Bestcide-500, Nippon Soda Co., Ltd.).

[0028] [Metabolome analysis] -Metabolite extraction for LC-TOFMS- Approximately 100 mg of each sample (1-10) was placed in a homogenization tube with zirconia beads (5 mm diameter and 3 mm diameter). Next, 500 μL of 1% formic acid / acetonitrile containing 10 μM internal standard (H3304-1002, Human Metabolome Technologies, Inc. (HMT)) was added to the tube, and the samples were homogenized at 3,500 rpm for 60 minutes 20 times using a bead shaker (Micro Smash, MS-100R, TOMY DIGITAL BIOLOGY CO., LTD.) at 4°C for 60 minutes. After that, 67 μL of Milli-Q water was added to the mixture, and the mixture was homogenized at 3,500 rpm for 60 minutes 5 times at 4°C. The supernatant was then centrifuged at 9,100 × g for 120 min at 4 °C through a 3-kDa cutoff filter (NANOCEP 3K OMEGA, PALL Corporation) to remove macromolecules, and further filtered using a hybrid SPE phospholipid cartridge (Hybrid SPE-Phospholipid 30 mg / mL, SUPELCO) to remove phospholipids. The filtrate was evaporated, dried under nitrogen, and reconstituted in 200 μL of 50% isopropanol for metabolomic analysis in the HMT.

[0029] -Metabolite extraction for CF-TOFMS- Approximately 100 mg of frozen tissue was placed in a homogenization tube with zirconia beads (5 mm diameter and 3 mm diameter). Next, 500 μL of MeOH containing 50 μM internal standard (H3304-1002, Human Metabolome Technologies, Inc. (HMT)) was added to the tube, and the tissue was homogenized at 3,500 rpm for 60 minutes 20 times using a bead shaker (Micro Smash, MS-100R, TOMY DIGITAL BIOLOGY CO., LTD.) at 4°C. After that, 400 μL of Milli-Q water was added and thoroughly mixed with the homogenate, followed by further homogenization at 2,300 rpm for 5 minutes at 4°C. Subsequently, 400 μL of the supernatant was centrifuged through a 5-kDa cutoff filter (UltrafreeMC-PLHCC, HMT0) at 9,100 × g for 120 min at 4 °C to remove macromolecules. The filtrate was evaporated, vacuum-dried, and reconstituted in 50 μL of Milli-Q water for metabolomic analysis at HMT.

[0030] -Metabolome analysis- Metabolomic analysis was performed on two separate systems: three samples collected between May and July 2022 and six samples collected between August 2022 and January 2023. They were processed using CE-TOFMS and LC-TOFMS according to a dual-scan package (UltrafreeMC-PLHCC, HMT). Specifically, CE-TOFMS analysis was performed using an Agilent CE capillary electrophoresis system (Agilent Technologies, Inc.) equipped with an Agilent 6210 time-of-flight mass spectrometer. LC-TOFMS analysis was performed using an Agilent 1200 HPLC pump (Agilent Technologies, Inc.) equipped with an Agilent 6210 time-of-flight mass spectrometer. The systems were controlled by Agilent G2201AA ChemStation software version B.03.01 for CE and MassHunter for LC (both Agilent Technologies, Inc.).

[0031] -Data Processing- The spectrometer was scanned between m / z 50 and 1,000, and peaks were extracted using MasterHands (Keio University) automated integration software to obtain peak information, such as m / z, peak area, and migration time for CE-TOFMS analysis, and retention time for LC-TFMS analysis. Signal peaks corresponding to isotopic isomers, adducts, and other products of known metabolites were extracted, and the remaining peaks were annotated according to the HMT metabolite database based on m / z values ​​and Mt or RT. The annotated peak areas were normalized to the internal standard and sample amount to obtain the relative levels of each metabolite. As a result of this process, the metabolites (1) to (443) listed above were identified.

[0032] [Physical property test] -Preparation of rubber samples- Pure water was added to Samples A to C to achieve a predetermined total solids concentration, and sodium dodecyl sulfate was added to the mixture to achieve a specified concentration and stirred.The mixture was dried at 180°C and rubber samples were prepared using the following procedure.

[0033] First, each natural rubber was masticated in advance, and then compounded with auxiliary raw materials in the pure rubber composition shown below. The rubber samples were prepared by kneading the rubber using an open roll equipped with two rolls, one on the left and one on the right, according to the following procedure.

[0034] (Rubber composition) Raw rubber 100phr Stearic acid (Lunac (registered trademark) S-70V, manufactured by Kao Corporation) 0.5 phr Zinc oxide (zinc oxide type 2, Sakai Chemical Industry Co., Ltd.) 6 phr Sulfur (fine powder sulfur, manufactured by Hosoi Chemical Industry Co., Ltd.) 3.5 phr Thiazole vulcanization accelerator (Suncera (registered trademark), manufactured by Sanshin Chemical Industry Co., Ltd.) 0.5 phr From the latex collected during the same month, many solid rubber samples were prepared and tested for tensile stress (100% modulus: M100(0H)).

[0035] (Mixing procedure) (a) The roll gap is set to 0.2 mm, and the natural rubber is passed through the roll twice without being wrapped around it. (b) The roll gap is set to 1.4 mm, and natural rubber is wound around the roll and kneaded to form a smooth strip. When this is achieved, widen the roll gap to 1.8 mm. (c) Add all the auxiliary ingredients. (d) Alternate between left and right, three times each. (e) The rubber material is cut off from the roll, and the roll gap is set to 0.8 mm and rolled six times. conduct. (f) When the rubber material has formed into a sheet with a thickness of 2.2 mm, it is removed from the roll.

[0036] -Tensile test- Each pure rubber composition was press-vulcanized at 150°C for 20 minutes to produce a sheet-shaped vulcanized rubber specimen (120 mm long, 120 mm wide, 2 mm thick). These rubber samples were then cut into dumbbell-shaped test pieces conforming to JIS K 6251 No. 5. The tensile properties (100% modulus (M100(OH))) of these test pieces were measured at a tensile speed of 500 mm / min.

[0037] -Structural analysis of metabolites- The structural diversity of the metabolites identified by the metabolome analysis described above was analyzed by compressing the Morgan fingerprints of each metabolite (mentioned above, (1) to (443)) into two dimensions using the Uniform Manifold Approximation and Projection (UMAP) method. Four metabolites for which compound IDs in PubChem could be identified were extracted (Table 1).

[0038] [Table 1]

[0039] (Footnotes to Table 1) 2.22E-16 was converted to 2^(-52) for normalization of below detection limit (ND).

[0040] [Data Analysis] The measured M100(0H) values ​​and the metabolite peak area values ​​obtained by metabolome analysis were standardized. Regression analysis was performed using the standardized measurements as the objective variable and the metabolite peak area values ​​as the explanatory variables. First, multiple linear regression models were created, each with a unique feature for each metabolite in the metabolite group. The root mean square errors of these models were compared, and the model with the smallest root mean square error was selected as the best simple regression model. Next, a linear multiple regression model was created using all metabolites in the metabolite group as features, and this was used as the forced entry model. Four metabolites were then selected using sequential forward floating selection (SFFS), and a linear multiple regression model using only the selected metabolites was created (Figure 1). Figure 1 plots all nine models created using cross-validation without averaging.

[0041] Example 2: Confirming the accuracy of the multiple regression model using test data [Sampling and sample preservation] Latex was collected from multiple rubber trees on a plantation in Thailand over three days between May and July 2023. The latex collected from each plant on each collection day was mixed and designated Samples A to C. Ammonia was added to prevent coagulation, and the samples were transported domestically at ambient temperature and stored at -4°C.

[0042] [Analysis of four metabolites] The same analysis as in the metabolome analysis of Example 1 was carried out, and the four metabolites shown in Table 2 were quantified (Table 2).

[0043] [Physical property test] Rubber samples were prepared and subjected to tensile tests in the same manner as in the physical property tests of Example 1, and M100(0H) was measured (Table 2).

[0044] [Table 2]

[0045] [Footnotes to Table 2] 2.22E-16 was converted to 2^(-52) for normalization of below detection limit (ND).

[0046] [Verifying the performance of multiple regression models through cross-validation] The actual measured values ​​obtained in the same manner for three samples A to C from May to July 2023 were plotted on the multiple regression model in Figure 1 to confirm the performance of the multiple regression model created in Example 1 (Table 2, Figures 2 and 3). From Figures 2 and 3, it was determined that both the prediction accuracy and regression accuracy of the multiple regression model were sufficient.

[0047] Example 3: Confirmation of regression performance of multiple regression model using test data Based on the partial regression coefficients of the multiple regression model, examples were calculated in which each component was adjusted to reduce the variance in the measured physical properties of Samples A to C measured in Example 2 (underlined parts in Table 3, Figure 4). It was assumed that the components could be accurately added up to the target values.

[0048] [Table 3]

[0049] After preparation, the relative standard deviation improved from the measured value of 3% to the predicted value of 0.6%, indicating that improved physical properties could be expected (Figure 4).

[0050] These results indicate that the four compounds in the table are related to rubber strength, and that latex compositions with relatively high contents of these compounds are useful as materials for producing rubber compositions with high rubber strength. Also, these compounds can be used as markers of rubber strength.

Claims

1. Step A: A step of performing comprehensive mass analysis of the constituent molecules of the latex composition and obtaining the analysis results; and Step B: A step of analyzing the relationship between the analysis results obtained in Step A and information about the latex composition; A method for evaluating a latex composition, comprising:

2. Step A: performing comprehensive mass analysis of constituent molecules of the latex composition and obtaining analysis results; Step B: A step of analyzing the relationship between the analysis results obtained in Step A and information about the latex composition; and Step C: A step of identifying, as an evaluation marker, a component of the latex composition associated with at least one piece of information regarding the latex composition from the analysis result of Step B. A method for selecting an evaluation marker for a latex composition, comprising:

3. Step a1: A step of analyzing a latex composition as a standard substance by the method of claim 1, and obtaining an analysis result relating the analysis result to information about the latex composition; and Step b1: A step of comprehensively analyzing a latex composition as a test substance and predicting the quality and / or properties of a rubber composition obtained from the latex composition as the test substance by comparing the analysis results obtained in step a1 with those obtained in step b2. A method for predicting the quality and / or properties of a rubber composition, comprising:

4. Step a2: A step of determining an evaluation marker for the latex composition as a standard substance by the method of claim 2. Step b2: A step of predicting the quality and / or properties of a rubber composition obtained from the latex composition as a test substance by performing a comprehensive analysis of the latex composition as a test substance and confirming the presence or amount of the evaluation marker obtained in step a2. A method for predicting the quality and / or properties of a rubber composition, comprising:

5. The method according to any one of claims 1 to 4, wherein the analytical results obtained in step A are analytical results of 40 or more constituent molecules of the latex composition.

6. The method according to any one of claims 1 to 4, wherein the analytical results obtained in step A are analytical results of 400 or more constituent molecules of the latex composition.

7. The method according to any one of claims 1 to 3, wherein the information about the latex composition includes a relationship between one or more physical properties of a rubber composition obtained from the latex composition and constituent molecules.

8. The method according to claim 7, wherein the physical properties of the rubber composition include one or more properties selected from Mooney scorch, vulcanization characteristics, mechanical strength, and heat aging resistance.

9. The method according to any one of claims 1 to 4, wherein the comprehensive mass analysis is metabolome analysis.

10. The method according to any one of claims 1 to 4, wherein the comprehensive mass analysis is analysis by LC-TOFMS and / or CE-TOFMS.

11. The method according to claim 9, wherein the results of the comprehensive mass analysis are expressed by one or more selected from the peak area ratio, the presence or absence of metabolites, and the content of metabolites.

12. The method according to any one of claims 1 to 4, wherein the analysis is a multivariate analysis.

13. The method according to any one of claims 1 to 4, wherein the analysis is a hierarchical clustering analysis.

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