Strawberry cultivar identification and quality evaluation on the basis of multiple fruit appearance features

Abstract

The appearances of agricultural  products are important indices for evaluating the quality of commodities and the characteristics of different varieties. In general, the appearances are evaluated by experts based on visual observations. However, the concern regarding this method is that it lacks objectivity, and it is not quantifiable because it depends greatly on an empirical knowledge. In addition, agricultural products have multiple appearance features; therefore, several of them need to be analyzed simultaneously for correct evaluation of the appearance. In this study, we developed a new image analysis system that can simultaneously evaluate multiple appearance characteristics such as the color, shape and size, of agricultural products in detail. To evaluate the effectiveness of this system, we conducted quality evaluations and cultivar identification on the basis of cluster analysis, multidimensional scaling and discriminant analysis of the appearance characteristics. The results of the cluster analysis revealed that strawberries could be classified on the basis of their appearance characteristics. Furthermore, we were able to visualize the small differences in the appearance of the fruit based on multiple characteristics on a two-dimensional surface by performing multidimensional scaling. The results demonstrate that our system is effective for qualitative evaluations of the appearance of strawberries. The results of the discriminant analysis revealed that the accuracy of strawberry cultivar classification using 14 cultivars was <42%, when only single feature was used. However, the rate increased to 68% after combining the three features. These results indicate that our system exploits the advantage of analyzing multiple appearance characteristics.

Developing a strawberry lexicon to describe cultivars at two maturation stages

“…Strawberries of differing cultivars were able to be distinguished by all appearance, aroma, and flavor attributes, excluding fermented and floral aroma, as well as firmness and astringency. This is supported by previous research indicating differences between cultivars in both sensory and quality properties (Du et al, ; Fernández‐Lara et al, ; Gündüz, ; Šamec et al, ; Yamamoto et al, ). Appearance attributes have been previously demonstrated as distinguishing cultivars (Yamamoto et al, ).…”

“…This is supported by previous research indicating differences between cultivars in both sensory and quality properties (Du et al, ; Fernández‐Lara et al, ; Gündüz, ; Šamec et al, ; Yamamoto et al, ). Appearance attributes have been previously demonstrated as distinguishing cultivars (Yamamoto et al, ). In addition to this, research indicates that esters, furanones, and lactones are volatiles that fluctuate in strawberries dependent upon the cultivar (Dong et al, ; Larsen & Poll, ; Latrasse, ).…”

“…There have been many recorded differences in both flavor and quality properties of various cultivars (Du et al, ; Fernández‐Lara et al, ; Gündüz, ; Šamec et al, ; Yamamoto et al, ). In addition, differing environmental conditions have been documented as affecting the combination of chemical components, and thus the flavor and quality of strawberry fruit (Davik, Bakken, Holte, & Blomhoff, ; Josuttis, Dietrich, Patz, & Kruger, ; Kruger, Toldam‐Anderson, & Dietrich, ; Kumar et al, ; Menzel, Smith, & Moisander, ; Samykanno, Pang, & Marriott, ; Tsormpatsidis et al, ).…”

“…Within the Fragaria ananassa species, hundreds of cultivars exist (Smith et al, 2003), with current breeding programs continually developing new cultivars worldwide (Hancock et al, 2008). Fragaria ananassa cultivars can be classified as either Short-Day (SD), Day-Neutral (DN), or Everbearing plants, depending on their flowering response to photoperiod (daylight hours) and air temperature (Darrow, 1936) There have been many recorded differences in both flavor and quality properties of various cultivars (Du et al, 2014;Fern andez-Lara et al, 2015;G€ und€ uz, 2016;Samec et al, 2016;Yamamoto et al, 2015).…”

Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods

“…validation of methodology with real foods Fatih TARLAK 1 with the computer vision system is the best way to measure the colour of food products, which have non-homogenous colour, and the system could be used for classification and prediction of chemical properties of foods. Recently, Yamamoto et al (2015) have demonstrated that qualitative evaluation of the appearance of strawberries can be achieved based on a computer vision analysis technique.…”