The global population of the world is on an exponential increase, expected to surpass 9 billion by the year 2050. This places a huge demand on food securities and the need to address the challenges facing food security. Sensor-based techniques [e.g., Fourier-transform infrared spectroscopy] have enhanced the understanding and diagnosis of several disease conditions, including cancers and are increasingly being applied to answer research questions in other areas including agriculture. Methods employed are relatively non-destructive, rendering samples reusable to be analyzed by more conventional approaches as well as allow the fingerprinting of biological samples based on the vibrational modes of the molecules within the sample. Spectra are derived consisting of wavenumber-absorbance intensities within a typical biological experiment and a complex dataset is quickly generated. Biological samples ranging from biofluids to cytology to tissue sections derived from human or sentinel organism sources including plants can easily be observed using this technique. Using a reference range of a designated normal state, anything lying outside this is judged as potentially atypical. Discriminating chemical entities can be identified using computational approaches, which allow one to minimize within-category confounding factors. Technologies involving sensor-based approaches provide a sensitive, cost effective technique for biological and agricultural research. Sensor-based techniques allow the characterization of biological material based on its biochemical-cell fingerprint and could enhance the study of plant species in agricultural research.
Key words: Biochemical-cell fingerprint, biospectroscopy, computational analysis, Fourier-transform infrared, infrared spectra, fluted pumpkin, Telfairia occidentalis.
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