Technology to validate the authenticity of varieties - a case study using apples of scientific principles and potential applications

苹果品种的准确描述是一个挑战，因为许多性状与果实的细微特征有关，迄今为止还不清楚哪一个是提供最佳描述的最小性状集。今年在阅读进行的一个本科项目，利用Brogdale国家水果收藏馆的苹果品种，在确定关键形态特征集的目标方面取得了重大进展。最有趣的是，计算机辅助形状分析表明，苹果形状似乎是一个特别强大的字符时，适当的量化。该项目还表明，以前只用于定性的颜色也可以使用色度学进行量化，并提供了相当大的潜力作为一个字符。与描述相关联的是识别。无论是业余爱好者还是商业人士，都对快速有效地鉴定苹果很感兴趣。例子包括从“花园底部的那个苹果”的识别，到识别苹果（在超市货架上销售）的商业重要问题，而这些苹果并不是他们声称的那样。然而，世界上有成千上万的苹果品种：英国国家苹果注册处列出了大约。在1853年至1968年期间，英国种植了6,000个苹果品种;目前在Brogdale的国家水果收藏馆中有2,000多个苹果品种。客观鉴定是非常困难的，只有少数具有多年经验的专家才能根据品种的外观命名。基于DNA的鉴定是昂贵的，缓慢的和破坏性的。计算机图像分析提供了将数千种可能性减少到几十种可能性的潜力，其中手动识别对于经验较少的人来说是可行的。与其他几个（容易测量的）特征相结合，可能性的数量可以进一步减少，直到只有品种差异，例如，味道，或颜色图案的微妙之处可能仍然存在。我们的博士项目将扩展已经进行的初步分析，包括更广泛的苹果品种;它将开发形状的计算机辅助分析，并建立一个确定的特征集进行识别。它将使用形态学方法与DNA标记方法（微卫星和多样性阵列技术，DArT）获得的结果进行对比。除了这项科学工作外，我们还将开发一个基于网络的图像分析系统，以便提供在线识别服务，需要输入少量关键特征测量值，包括未知苹果的适当照片图像。其目的是提供一个初步的识别，相关的正确性概率，以及可能的替代方案。该学生还将与Sainsbury一起探索开发识别系统的方法的适用性，以自动识别特定品种水果系中的非类型。此外，亦会探讨形状分析在其他新鲜农产品方面的广泛应用。

The accurate description of apple cultivars is a challenge because many of the characters relate to subtle features of the fruit, and it has hitherto been unclear which is the minimum set of characters to provide an optimal description. An undergraduate project carried out this year at Reading, utilizing apple accessions from the National Fruit Collections at Brogdale, has made significant progress towards the objective of identifying a key morphological character set. Most interestingly, computer-aided shape analysis has indicated that apple shape appears to be a particularly powerful character when appropriately quantified. The project also showed that colour, previously used only qualitatively, can also be quantified using colourimetry and offers considerable potential as a character. Allied to description is identification. There is much interest, both amateur and commercial, in rapid and effective identification of apples. Examples range from the identification of 'that apple at the bottom of the garden', to the commercially significant problem of identifying apples (for sale on supermarket shelves) which are not what they claim to be. There are however, many thousands of apple cultivars in the world: the National Apple Register of the UK lists approx. 6,000 apple cultivars known to have been grown in the UK between 1853 and 1968; and there are over 2,000 cultivars of apple currently held in the National Fruit Collections at Brogdale. Objective identification is very difficult and only a few experts with many years experience can name cultivars by their appearance. DNA-based identification is expensive, slow and destructive. Computerised image analysis offers the potential to reduce thousands of possibilities down to a few tens of possibilities where manual identification is practical for those with less experience. In combination with a few other (easily-measured) characters the number of possibilities could be reduced still further until only cultivar differences relating, for example, to taste, or subtleties in colour patterning are likely to remain. Our PhD project would extend the preliminary analysis already carried out to include a much wider range of apple cultivars; it would develop the computer-aided analysis of shape and establish a definitive character set for identification. It would contrast the results obtained using a morphological approach with DNA marker methods (microsatellites and Diversity Array Technology, DArT). Alongside this scientific work, we would develop an image-analysis Web-based system with a view to providing an on-line identification service, requiring the input of a small number of key character measurements, including an appropriate photographic image of the unknown apples. The aim would be to provide a preliminary identification, associated probability of correctness, and possible alternatives. The student would also, in conjunction with Sainsbury's, explore the suitability of the approach for development of an identification system to allow automated identification of off-types in variety-specific lines of fruit. The potential wider applications of shape analysis to other fresh produce would also be explored.