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Complex pattern formation is an essential characteristic of plants and theirageing, growth, and evolution. Perception of these patterns is an intrinsicnature of plant-dependent animals for coexistence. Areca nut consisting ofcomplex patterns is considered to be addictive for humans and has increasedadverse health effects. However, no critical study is performed on the complexpattern of the areca nut. A large number of areca nuts has been studied since2017 to develop a low-cost tool for the LMICs to categorise areca nuts. Wepresent the first finding to identify similarities among complex networks ofdifferently aged areca nuts by investigating the internal patterns of randomlychosen nuts from the same age group. We developed a smartphone camera-basedhigh-resolution measurement with comprehensive biophysical mathematics and aquantum mechanical concept called density of states (DOS). We found that theDOS can provide a unique coefficient to represent age and ageing together usinga single number. The average of these single numbers for less aged nuts andhighly aged nuts are 4.9 and 3.8, respectively. If fruit looks aged from itsexternal morphology as well as internal morphology, our method identifies theintrinsic similarities among the ageing networks without implementing anycomputationally expensive search algorithm. We show clear evidence of thediversity of ageing from relative and absolute colour vision perspectives. Wehave also conducted further analyses of local DOS, Fourier decomposition,correlation study, spectral decomposition, and structural similarity index.

Ageing related states of complex network formation in areca nuts