Optimum maturity and ripeness at the time of harvest is highly important to maintain the nutritional parameters of fruits. Maturity and ripeness of most of the fruit samples depends on various physiochemical parameters such as color, shape, size, total soluble solid and many more. Several state-of-the-art solutions such as GC–MS, Electronic Nose, Spectrometer and many more are available to measure various fruit quality parameters but most of the solutions available in the market are bulky, time consuming, lab-level and requires skilled manpower for operation. Presented manuscript reports a battery operated, smartphone spectrometer based solution to carry out the variety of activities in the field. Overall device uses UV–Vis-NIR led array as source and collection of spectral sensors (AS7262 and OPT101) to acquire overall UV–Vis-NIR spectrum over the range of 400–1000 nm with the resolution of 40 nm. Designed source and detector modules have been interfaced with designed triggering, filter and amplification circuit. A low power wireless solution along with on-board microcontroller facility has been designed and interfaced with circuits, source and detectors. All essential components such as source, detectors, filters, lens and all circuits have been assembled in a housing of dimensions 18.0 × 9.0 × 6.0 (in cm) and the entire device weighs 183.35 g. Different statistical and neural network based modelling techniques have been explored to design prediction models for total soluble solids, weight, volume, chlorophyll, sugar content and acidity. Models have been evaluated based on accuracy, memory and time usage. Best performed models have been used to train handheld smartphone based spectrometer device to predict various quality parameters for citrus samples. System communicates data to smartphone based android app to display various parameters. Android app also provides facility to save data on cloud with tree and orchard ID to monitor overall yield and harvesting time.