University of Hawaii at Hilo, Pacific Internship Program for Exploring Science, Hilo, Hawaii, United States of America.
USDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America.
PLoS One. 2024 Jun 6;19(6):e0303532. doi: 10.1371/journal.pone.0303532. eCollection 2024.
Avocados are an important economic crop of Hawaii, contributing to approximately 3% of all avocados grown in the United States. To export Hawaii-grown avocados, growers must follow strict United States Department of Agriculture Animal and Plant Health Inspection Service (USDA-APHIS) regulations. Currently, only the Sharwil variety can be exported relying on a systems approach, which allows fruit to be exported without quarantine treatment; treatments that can negatively impact the quality of avocados. However, for the systems approach to be applied, Hawaii avocado growers must positively identify the avocados variety as Sharwil with APHIS prior to export. Currently, variety identification relies on physical characteristics, which can be erroneous and subjective, and has been disputed by growers. Once the fruit is harvested, variety identification is difficult. While molecular markers can be used through DNA extraction from the skin, the process leaves the fruit unmarketable. This study evaluated the feasibility of using near-infrared spectroscopy to non-destructively discriminate between different Hawaii-grown avocado varieties, such as Sharwil, Beshore, and Yamagata, Nishikawa, and Greengold, and to positively identify Sharwil from the other varieties mentioned above. The classifiers built using a bench-top system achieved 95% total classification rates for both discriminating the varieties from one another and positively identifying Sharwil while the classifier built using a handheld spectrometer achieved 96% and 96.7% total classification rates for discriminating the varieties from one another and positively identifying Sharwil, respectively. Results from chemometric methods and chemical analysis suggested that water and lipid were key contributors to the performance of classifiers. The positive results demonstrate the feasibility of NIR spectroscopy for discriminating different avocado varieties as well as authenticating Sharwil. To develop robust and stable models for the growers, distributors, and regulators in Hawaii, more varieties and additional seasons should continue to be added.
鳄梨是夏威夷的重要经济作物,约占美国种植鳄梨的 3%。为了出口夏威夷种植的鳄梨,种植者必须遵守美国农业部动植物健康检验局(USDA-APHIS)的严格规定。目前,只有 Sharwil 品种可以通过系统方法出口,该方法允许在没有检疫处理的情况下出口水果;处理方法会对鳄梨的质量产生负面影响。然而,为了应用该系统方法,夏威夷鳄梨种植者在出口前必须通过 APHIS 积极识别 Sharwil 品种。目前,品种识别依赖于物理特征,这些特征可能存在错误和主观性,并且受到种植者的质疑。一旦水果被收获,品种识别就变得困难。虽然可以通过从果皮中提取 DNA 来使用分子标记,但该过程会使水果失去市场价值。本研究评估了使用近红外光谱技术非破坏性地区分不同夏威夷种植的鳄梨品种(如 Sharwil、Beshore、Yamagata、Nishikawa 和 Greengold)的可行性,并从上述其他品种中积极识别 Sharwil。使用台式系统构建的分类器对彼此进行分类的总分类率达到 95%,对 Sharwil 进行正识别的总分类率达到 95%,而使用手持式光谱仪构建的分类器对彼此进行分类的总分类率达到 96%,对 Sharwil 进行正识别的总分类率达到 96.7%。化学计量学方法和化学分析的结果表明,水和脂质是分类器性能的关键贡献者。积极的结果表明,近红外光谱技术可用于区分不同的鳄梨品种以及验证 Sharwil 的真实性。为了为夏威夷的种植者、分销商和监管机构开发稳健和稳定的模型,应继续添加更多品种和更多季节的数据。