1. A method for detecting “sugar end” defects in potatoes, comprising: irradiating potatoes with at least one light source with wide-band light, for a plurality of locus points on each potato, wherein locus points lie on both end regions of the potato and other locus points lie in a central region of the potato, selectively projecting the light reflected from or transmitted through the respective locus points onto at least one photo sensor, generating, with the at least one photo sensor, light measurement signals for each locus point from the received light which light measurement signals are generated as the spectra of the light reflected from or transmitted through the locus points, and intermediately storing such light measurement signals generated for each locus point, determining at least one classification feature from the light measurement signals in a wavelength range between 350 and 2500 nm by determining at least one classification feature from the spectra of the nth (n=1, 2,. .. ) derivative of the spectra, and classifying potatoes as having “sugar end” defects if at least one classification feature corresponds to a predefined “sugar end” criterion, wherein determining at least one classification feature from the respective spectrum or the nth derivative of the respective spectrum of the locus points comprises calculating the difference curve for the respective locus point by calculating the differences between the spectral light measurement signals of the respective locus point and the spectral values of a reference spectrum for a number of wavelengths or by calculating the differences between the nth derivative of the spectral light measurement signals of the respective locus point and the nth derivative of the reference spectrum for a number of wavelengths, and that the classification feature is thus determined by the difference curve calculated in this way, wherein a classification feature derived from the difference curves is the curve of the first or second differential quotient of the respective difference curve and the classification criterion is selected from exceeding or falling below limit values of the differential quotient at defined wavelengths or wavelength bands, optionally with calculating average values of the differential quotient values within the wavelength bands, or the presence of difference quotient values within or out of a defined differential quotient value range at defined wavelengths or wavelength bands, optionally with calculating average values of the differential quotient values within the wavelength bands, or the similarity of at least one portion of the differential quotient curve with a predefined pattern.