Payne William Z, Kurouski Dmitry
Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, 77843, USA.
Department of Biomedical Engineering, Texas A&M University, College Station, TX, 77843, USA.
Plant Methods. 2021 Jul 15;17(1):78. doi: 10.1186/s13007-021-00781-y.
Our civilization has to enhance food production to feed world's expected population of 9.7 billion by 2050. These food demands can be met by implementation of innovative technologies in agriculture. This transformative agricultural concept, also known as digital farming, aims to maximize the crop yield without an increase in the field footprint while simultaneously minimizing environmental impact of farming. There is a growing body of evidence that Raman spectroscopy, a non-invasive, non-destructive, and laser-based analytical approach, can be used to: (i) detect plant diseases, (ii) abiotic stresses, and (iii) enable label-free phenotyping and digital selection of plants in breeding programs. In this review, we critically discuss the most recent reports on the use of Raman spectroscopy for confirmatory identification of plant species and their varieties, as well as Raman-based analysis of the nutrition value of seeds. We show that high selectivity and specificity of Raman makes this technique ideal for optical surveillance of fields, which can be used to improve agriculture around the world. We also discuss potential advances in synergetic use of RS and already established imaging and molecular techniques. This combinatorial approach can be used to reduce associated time and cost, as well as enhance the accuracy of diagnostics of biotic and abiotic stresses.
我们的文明必须提高粮食产量,以养活预计到2050年将达到97亿的世界人口。这些粮食需求可以通过在农业中应用创新技术来满足。这种变革性的农业概念,也被称为数字农业,旨在在不增加耕地面积的情况下最大限度地提高作物产量,同时将农业对环境的影响降至最低。越来越多的证据表明,拉曼光谱作为一种非侵入性、非破坏性的基于激光的分析方法,可用于:(i)检测植物病害,(ii)非生物胁迫,以及(iii)在育种计划中实现无标记表型分析和植物的数字选择。在本综述中,我们批判性地讨论了关于使用拉曼光谱进行植物物种及其品种的确认鉴定以及基于拉曼的种子营养价值分析的最新报告。我们表明,拉曼光谱的高选择性和特异性使其成为田间光学监测的理想技术,可用于改善全球农业。我们还讨论了拉曼光谱与已成熟的成像和分子技术协同使用的潜在进展。这种组合方法可用于减少相关的时间和成本,以及提高生物和非生物胁迫诊断的准确性。