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

验证品种真实性的技术——以苹果为例的科学原理和潜在应用案例研究

• 批准号: BB/I015752/1
• 金额: $ 11.71万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Training Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI015752%2F1
• 关键词: Technology; validate; authenticity; varieties; case

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.

对苹果品种的准确描述是一个挑战，因为许多特征与水果的微妙特征有关，并且迄今为止还不清楚哪一个是提供最佳描述的最小特征集。今年在雷丁大学开展的一个本科项目利用了布罗格代尔国家水果保藏中心的苹果品种，在识别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，如果适当量化，苹果形状似乎是一个特别强大的特征。该项目还表明，以前仅定性使用的颜色也可以使用比色法进行量化，并且作为一种字符具有相当大的潜力。与描述相关的是识别。无论是业余爱好者还是商业人士，都对快速有效地识别苹果感兴趣。例子包括识别“花园底部的那个苹果”，以及识别与他们声称的不符的苹果（在超市货架上出售）的商业重大问题。然而，世界上有数千个苹果品种：英国国家苹果登记册列出了大约 10 个。 1853 年至 1968 年间，英国已知种植了 6,000 个苹果品种；布罗格代尔国家水果保藏中心目前拥有 2,000 多个苹果品种。客观鉴定非常困难，只有少数具有多年经验的专家才能通过外观来命名品种。基于 DNA 的鉴定昂贵、缓慢且具有破坏性。计算机图像分析有可能将数千种可能性减少到几十种可能性，其中手动识别对于经验较少的人来说是实用的。与其他一些（易于测量的）特征相结合，可能性的数量可以进一步减少，直到仅可能保留与口味或颜色图案的微妙性等相关的品种差异。我们的博士项目将扩展已经进行的初步分析，以包括更广泛的苹果品种；它将开发计算机辅助形状分析并建立用于识别的明确字符集。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。目的是提供初步识别、相关的正确概率以及可能的替代方案。该学生还将与塞恩斯伯里公司合作，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中的异常类型。还将探索形状分析在其他新鲜农产品中的潜在更广泛应用。