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Measurements

Agrosta adds new features to its Roxanne colorimeter software

The 2026 versions of the Training and Measurement Software allow users to save and resume sessions, reload data stored in Excel and delete selected rows

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21 July, 2026
Measurements

Agrosta has introduced several improvements to the 2026 versions of the software for Roxanne, its colorimeter and spectrophotometer designed for the analysis and classification of food, fruit, vegetables and other products. The new features facilitate the management of training and measurement processes that require multiple sessions, particularly when working with a large number of samples or categories.

 

New features for saving and resuming sessions

The Training Software now allows users to save a session and resume it later. This function is intended for lengthy processes involving numerous categories, enabling users to interrupt their work and complete it over several sessions without having to repeat the training previously carried out.

The Measurement Software allows the data obtained to be saved directly to an Excel file and reloaded at a later stage. Measurements can therefore be resumed from the point at which the session was interrupted, while keeping the results from the same project together.

Agrosta has also added row deletion functions to both applications. Users can select and remove entries they do not wish to retain, either while preparing classification files or recording measurements.

Agrosta Roxanne Measurement Software, whose 2026 version allows users to save data to Excel, reload it and resume measurement sessions later

 

Classification using visible and infrared wavelengths

Agrosta Roxanne combines the functions of a colorimeter and a spectrophotometer, recording information across the visible spectrum and near-infrared range. According to the company, this combination makes it possible to identify differences between samples that may be imperceptible to the human eye, such as those associated with fruit maturity or the fat content of milk.

The device provides ten values per measurement: eight corresponding to the visible spectrum, one to infrared and one to gloss. According to the information provided by Agrosta, it offers a resolution of 1/1000 across the different wavelengths and uses a neural network operating in a nine-dimensional space to classify samples.

Users can work with classification files based on CTIFL color standards or create their own files for a particular product or requirement. To do so, the sample is placed on the colorimeter head, the corresponding classification indices are entered into the software and the resulting data are saved. The resulting "neural file" can subsequently be used to classify new samples.

This capability makes it possible to develop specific classifications for different fruit and vegetables. Applications highlighted by the company include maturity analysis and the classification of products such as strawberries, apples and tomatoes, as well as other uses in research, quality control and R&D in the food, pharmaceutical and chemical sectors.

 

USB-powered operation and Windows software

Roxanne is powered through a USB connection to a computer and operates with training, classification and measurement software developed for Windows. The system includes two sample holders for analysing flat and spherical samples, as well as a preloaded strawberry classification file.

The company states that the device is designed to operate without maintenance throughout its service life and is covered by a two-year warranty. The software allows information to be exported to Excel and other analysis tools, a capability expanded in the 2026 version through the option to reload these files and continue taking measurements.

On its website, Agrosta also reports a comparison carried out by a Spanish customer specialising in olive research between data provided by a Konica Minolta colorimeter and those obtained with the Roxanne sensor. According to the information published by the company, the color measurements obtained with the two devices were similar.

 

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