Kumar Rajeev, Paul Vijay, Pandey Rakesh, Sahoo R N, Gupta V K
Division of Plant Physiology, ICAR-Indian Agricultural Research Institute (IARI), New Delhi, Delhi 110012 India.
Present Address: Division of Vegetable Production, ICAR-Indian Institute of Vegetable Research (IIVR), Varanasi, Uttar Pradesh 221 305 India.
Physiol Mol Biol Plants. 2022 Jan;28(1):275-288. doi: 10.1007/s12298-022-01126-2. Epub 2022 Feb 7.
The preference and quality of tomato fruit are primarily determined by its apparent colour and appearance. Non-destructive and rapid methods for assessment of tomato colour and ripeness are therefore of immense significance. This study was conducted to identify reflectance-based indices and to develop models for the non-destructive determination of colour and ripeness (maturity) of tomato fruits. Tomato fruits of two varieties and two hybrids, representing different ripening stages were investigated. Fruits were either harvested directly from the plants or they were picked up from the lots stored at 25 °C. Reflectance from individual fruit was recorded in a spectrum ranging from 350 to 2500 nm. These fruits at different ripening stages were ranked on a relative ripening score (0.0-8.5). Obtained data (reflectance and ripening score) were subjected to chemometric analysis. In total, six models were developed. The first-best model was based on the index R (reflectance at wavelength 521 nm) i.e., y (colour/ripeness) = - 2.456 ln (x) - 1.093 where x is R. This model had a root mean standard error of prediction (RMSEP) ≥ 0.86 and biasness = - 0.09. The second-best model y = 2.582 ln (x) - 0.805 was based on the index R (x) and had RMSEP ≥ 0.89 and biasness = 0.10. Models could bifurcate tomatoes into basic ripening stages and also red and beyond red tomato fruits from other stages across the varieties/hybrids and ripening conditions [for plant harvested (fresh) and stored (aged) fruits]. Findings will prove useful in developing simple and thereby cost-effective tools for rapid screening/sorting of tomato fruits based on their colour or ripeness not only for basic research (phenotyping) but also for the purpose of processing, value-addition, and pharmaceutical usages.
The online version contains supplementary material available at 10.1007/s12298-022-01126-2.
番茄果实的偏好和品质主要由其表观颜色和外观决定。因此,用于评估番茄颜色和成熟度的非破坏性快速方法具有极其重要的意义。本研究旨在确定基于反射率的指标,并建立用于非破坏性测定番茄果实颜色和成熟度(成熟)的模型。研究了代表不同成熟阶段的两个品种和两个杂交种的番茄果实。果实要么直接从植株上采收,要么从25℃储存的批次中挑选。记录单个果实从350到2500nm光谱范围内的反射率。这些处于不同成熟阶段的果实根据相对成熟度评分(0.0 - 8.5)进行排序。对获得的数据(反射率和成熟度评分)进行化学计量分析。总共开发了六个模型。最佳模型基于指标R(波长521nm处的反射率),即y(颜色/成熟度)= -2.456 ln(x) - 1.093,其中x为R。该模型的预测均方根标准误差(RMSEP)≥0.86,偏差为 -0.09。次佳模型y = 2.582 ln(x) - 0.805基于指标R(x),RMSEP≥0.89,偏差为0.10。这些模型可以将番茄分为基本成熟阶段,还能区分不同品种/杂交种以及成熟条件下(植株采收的新鲜果实和储存的陈年果实)红色及红色以上阶段的番茄果实与其他阶段的果实。研究结果将有助于开发简单且经济高效的工具,用于基于颜色或成熟度对番茄果实进行快速筛选/分选,不仅适用于基础研究(表型分析),也适用于加工、增值和药用目的。
在线版本包含可在10.1007/s12298 - 022 - 01126 - 2获取的补充材料。