Prediction of the heats of combustion for food-related organic compounds. A quantitative structure-property relationship (QSPR) study

被引:0
|
作者
Diaz, Mario G. [1 ]
Dimarco Palencia, Frida V. [1 ]
Andrada, Matias F. [2 ]
Vega-Hissi, Esteban G. [1 ]
Duchowicz, Pablo R. [3 ]
Garro Martinez, Juan C. [1 ]
机构
[1] Univ Nacl San Luis, Fac Quim Bioquim & Farm, IMIBIO SL CONICET, RA-5700 San Luis, Argentina
[2] Inst Fis Aplicada INFAP, CCT San Luis CONICET, San Luis, Argentina
[3] Univ Nacl La Plata, CONICET, Inst Invest Fisicoquim Teor & Aplicadas, RA-1900 La Plata, Buenos Aires, Argentina
关键词
Foods research; Heats of combustion; QSPR model; Organic compounds; Predictive capacity; DESCRIPTORS; ALGORITHM; CHEMISTRY; SAFETY; MODELS; HEALTH;
D O I
10.1007/s10973-024-13559-w
中图分类号
O414.1 [热力学];
学科分类号
摘要
In the field of food research, the determination of the heats of combustion (Delta H-c) of the nutrients is essential to estimate the amount of energy obtained by metabolizing during digestion. Here, we have developed six novel QSPR models to predict this thermodynamic property of different families of organic compounds. The models were developed using the experimental data set of 215 compounds (71 organic acids, 28 amino acids, 37 amines and amides, 31 sulfur compounds and 48 heterocyclic compounds). About 16,000 molecular descriptors were calculated to represent the molecular structure of the compounds. The QSPR models resulted to be simple MLRs with a maximum of three variables, facilitating the interpretation and comparison with existing models in the literature. The statistical parameters exhibited excellent predictive capacity and robustness of the models obtained. The correlation coefficients of the selected models were major to 0.8 and the root means square error minor to 0.1. These results suggested that the models could be utilized for the prediction of the Delta H-c of other compounds that could be present in the foods.
引用
收藏
页码:11747 / 11759
页数:13
相关论文
共 50 条
  • [31] Estimation of surface tension of organic compounds using quantitative structure-property relationship
    Dai Yi-min
    Liu You-nian
    Li Xun
    Cao Zhong
    Zhu Zhi-ping
    Yang Dao-wu
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2012, 19 (01) : 93 - 100
  • [32] Prediction of viscosity index and pour point in ester lubricants using quantitative structure-property relationship (QSPR)
    Nasab, Shima Ghanavati
    Semnani, Abolfazl
    Marini, Federico
    Biancolillo, Alessandra
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2018, 183 : 59 - 78
  • [33] Predictive quantitative structure-property relationship (QSPR) modeling for adsorption of organic pollutants by carbon nanotubes (CNTs)
    Roy, Joyita
    Ghosh, Sulekha
    Ojha, Probir Kumar
    Roy, Kunal
    ENVIRONMENTAL SCIENCE-NANO, 2019, 6 (01) : 224 - 247
  • [34] A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure
    Liu, Fengping
    Cao, Chenzhong
    Cheng, Bin
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2011, 12 (04): : 2448 - 2462
  • [35] Quantitative structure-property relationship study for estimation of quantitative calibration factors of some organic compounds in gas chromatography
    Luan, Feng
    Liu, Hui Tao
    Wen, Yingying
    Zhang, Xiaoyun
    ANALYTICA CHIMICA ACTA, 2008, 612 (02) : 126 - 135
  • [36] Singlet oxygen generation by porphyrins and metalloporphyrins revisited: A quantitative structure-property relationship (QSPR) study
    Buglak, Andrey A.
    Filatov, Mikhail A.
    Althaf Hussain, M.
    Sugimoto, Manabu
    JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY A-CHEMISTRY, 2020, 403
  • [37] Quantitative structure-property relationship (QSPR) study of glass transition temperatures for diverse set of polymers
    Chen, Min
    Jabeen, Farukh
    Rasulev, Bakhtiyor
    Ossowski, Martin
    Boudjouk, Philip
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2015, 250
  • [38] How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR)
    Dearden, J. C.
    Cronin, M. T. D.
    Kaiser, K. L. E.
    SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2009, 20 (3-4) : 241 - 266
  • [39] Prediction of the θ(UCST) of Polymer Solutions: A Quantitative Structure-Property Relationship Study
    Gharagheizi, Farhad
    Sattari, Mehdi
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2009, 48 (19) : 9054 - 9060
  • [40] Quantitative Structure-Property Relationship Study for Prediction of Flash Point of Some Organic Compounds Based On SW-MLR Method
    Rahimi, Mehdi
    Nekoei, Mehdi
    Analytical Chemistry Letters, 2013, 3 (04) : 278 - 286