Ageing related states of complex network formation in areca nuts

Complex pattern formation is an essential characteristic of plants and their ageing, growth, and evolution. Perception towards these patterns is an intrinsic nature of plant-dependent animals for coexistence. Areca nut is considered to be addictive for humans and has increased adverse health effects. A large number of areca nuts has been studied since 2017 to develop a low-cost tool for the LMICs to categorise areca nuts. We present the first finding to identify similarities among complex networks of differently aged areca nuts. We investigated the internal patterns of differently aged areca nuts randomly chosen from the same age group. We developed a smartphone camera-based high-resolution measurement with comprehensive biophysical mathematics and a quantum mechanical concept called density of states (DOS). We found that the DOS can provide a unique coefficient to represent age and ageing together using a single number. The average of these single numbers for less aged nuts and highly aged nuts are 4.9 and 3.8, respectively. If a fruit looks aged from its external morphology as well as internal morphology, our method identifies the intrinsic similarities between two phenotypic expressions without implementing any computationally expensive search algorithm. We have also conducted further analyses of local DOS, Fourier decomposition, correlation study, spectral decomposition, and structural similarity index.