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Holman AP, Pickett DN, Orr AE, Tarone AM, Kurouski D. A nondestructive technique for the sex identification of third instar Cochliomyia macellaria larvae. J Forensic Sci 2024. [PMID: 39223721 DOI: 10.1111/1556-4029.15619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 08/16/2024] [Accepted: 08/21/2024] [Indexed: 09/04/2024]
Abstract
Forensic entomology plays an important role in medicolegal investigations by using insects, primarily flies, to estimate the time of colonization. This estimation relies on the development of the flies found at the (death) scene and can be affected (and sometimes corrected) by external factors, such as temperature and humidity, and internal factors, such as species and sex. This study leverages infrared (IR) spectroscopy combined with machine learning models-Partial Least Squares Discriminant Analysis (PLS-DA) and eXtreme Gradient Boosting trees Discriminant Analysis (XGBDA)-to differentiate between male and female Cochliomyia macellaria larvae, commonly found on human remains. Significant vibrational differences were detected in the infrared spectra of third instar C. macellaria larvae, with distinct peaks showing variations in relative absorbance between sexes, suggesting differences in biochemical compositions such as cuticular proteins and lipids. The application of PLS-DA and XGBDA yielded high classification accuracies of about 94% and 96%, respectively, with female spectra consistently having higher sensitivity than males. This non-destructive approach offers the potential to refine supplemental post-mortem interval estimations significantly, enhancing the accuracy of forensic analyses.
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Affiliation(s)
- Aidan P Holman
- Department of Entomology, Texas A&M University, College Station, Texas, USA
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA
| | - Davis N Pickett
- Department of Biology, Texas A&M University, College Station, Texas, USA
| | - Abigail E Orr
- Department of Entomology, Texas A&M University, College Station, Texas, USA
| | - Aaron M Tarone
- Department of Entomology, Texas A&M University, College Station, Texas, USA
| | - Dmitry Kurouski
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas, USA
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Qu H, Zhang X, Ye C, Ngando FJ, Shang Y, Yang F, Xiao J, Chen S, Guo Y. Combining spectrum and machine learning algorithms to predict the weathering time of empty puparia of Sarcophaga peregrine (Diptera: Sarcophagidae). Forensic Sci Int 2024; 361:112144. [PMID: 39018983 DOI: 10.1016/j.forsciint.2024.112144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 07/05/2024] [Accepted: 07/07/2024] [Indexed: 07/19/2024]
Abstract
The weathering time of empty puparia could be important in predicting the minimum postmortem interval (PMImin). As corpse decomposition progresses to the skeletal stage, empty puparia often remain the sole evidence of fly activity at the scene. In this study, we used empty puparia of Sarcophaga peregrina (Diptera: Sarcophagidae) collected at ten different time points between January 2019 and February 2023 as our samples. Initially, we used the scanning electron microscope (SEM) to observe the surface of the empty puparia, but it was challenging to identify significant markers to estimate weathering time. We then utilized attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to detect the puparia spectrogram. Absorption peaks were observed at 1064 cm-1, 1236 cm-1, 1381 cm-1, 1538 cm-1, 1636 cm-1, 2852 cm-1, 2920 cm-1. Three machine learning models were used to regress the spectral data after dimensionality reduction using principal component analysis (PCA). Among them, eXtreme Gradient Boosting regression (XGBR) showed the best performance in the wavenumber range of 1800-600 cm-1, with a mean absolute error (MAE) of 1.20. This study highlights the value of refining these techniques for forensic applications involving entomological specimens and underscores the considerable potential of combining FTIR and machine learning in forensic practice.
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Affiliation(s)
- Hongke Qu
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China; School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Xiangyan Zhang
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Chengxin Ye
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Fernand Jocelin Ngando
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Yanjie Shang
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Fengqin Yang
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Jiao Xiao
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Sile Chen
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China
| | - Yadong Guo
- Department of Forensic Science, School of Basic Medical Sciences, Central South University, Changsha 410013, China.
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Ruggeri M, Bianchi E, Vigani B, Sánchez-Espejo R, Spano M, Totaro Fila C, Mannina L, Viseras C, Rossi S, Sandri G. Nutritional and Functional Properties of Novel Italian Spray-Dried Cricket Powder. Antioxidants (Basel) 2023; 12:antiox12010112. [PMID: 36670974 PMCID: PMC9854902 DOI: 10.3390/antiox12010112] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 01/04/2023] Open
Abstract
Insects, especially crickets, have been proposed as a novel source of nutrients in human nutrition since they possess bioactive molecules, including high protein content, lipids, chitin, vitamins and minerals. In this work, the nutritional and functional properties of a novel Italian spray-dried (SD) cricket powder were evaluated. The powder was characterized by physico-chemical properties (morphology, size distribution, solid state, thermal profiles, and surface zeta potential), and antioxidant properties. Moreover, preclinical properties (cytocompatibility and pro-inflammatory immune response) were assessed. The powder was characterized by microparticle structure with bulges and rough surfaces, showing distinctive antioxidant properties. The preclinical results suggested that the SD crickets were biocompatible towards Caco-2 and macrophages without immune response, representing an interesting material for the food industry that could provide health benefits in addition to the basic nutritional value of traditional foods.
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Affiliation(s)
- Marco Ruggeri
- Department of Drug Sciences, University of Pavia, Viale Taramelli 12, 27100 Pavia, Italy
| | - Eleonora Bianchi
- Department of Drug Sciences, University of Pavia, Viale Taramelli 12, 27100 Pavia, Italy
| | - Barbara Vigani
- Department of Drug Sciences, University of Pavia, Viale Taramelli 12, 27100 Pavia, Italy
| | - Rita Sánchez-Espejo
- Department of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, University of Granada, Campus of Cartuja s/n, 18071 Granada, Spain
| | - Mattia Spano
- Department of Chemistry and Technology of Drugs, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | | | - Luisa Mannina
- Department of Chemistry and Technology of Drugs, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - César Viseras
- Department of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, University of Granada, Campus of Cartuja s/n, 18071 Granada, Spain
| | - Silvia Rossi
- Department of Drug Sciences, University of Pavia, Viale Taramelli 12, 27100 Pavia, Italy
| | - Giuseppina Sandri
- Department of Drug Sciences, University of Pavia, Viale Taramelli 12, 27100 Pavia, Italy
- Correspondence:
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Highly Efficient Use of Infrared Spectroscopy (ATR-FTIR) to Identify Aphid Species. BIOLOGY 2022; 11:biology11081232. [PMID: 36009859 PMCID: PMC9404783 DOI: 10.3390/biology11081232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Revised: 08/09/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022]
Abstract
Aphids are commonly considered to be serious pests for trees, herbaceous and cultivated plants. Recognition and identification of individual species is very difficult and is based mainly on morphological features. The aims of the study were to suggest the possibility of identifying aphids through the use of Fourier-transform infrared (FTIR) spectroscopy, and to determine which absorption peaks are the most useful to separate aphid species. Using FTIR spectroscopy, based on the chemical composition of the body, we were able to distinguish 12 species of aphid. We have shown that using nine distinct peaks corresponding to the molecular vibrations from carbohydrates, lipids, amides I and II, it is possible to accurately identify aphid species with an efficiency of 98%.
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