PDF(Pubmed)
Abstract：
Biological nitrogen fixation (BNF) by symbiotic bacteria plays a vital role in sustainable agriculture. However, current quantification methods are often expensive and impractical. This study explores the potential of Raman spectroscopy, a non-invasive technique, for rapid assessment of BNF activity in soybeans. Raman spectra were obtained from soybean plants grown with and without rhizobia bacteria to identify spectral signatures associated with BNF. δN15 isotope ratio mass spectrometry (IRMS) was used to determine actual BNF percentages. Partial least squares regression (PLSR) was employed to develop a model for BNF quantification based on Raman spectra. The model explained 80% of the variation in BNF activity. To enhance the model\'s specificity for BNF detection regardless of nitrogen availability, a subsequent elastic net (Enet) regularisation strategy was implemented. This approach provided insights into key wavenumbers and biochemicals associated with BNF in soybeans.
摘要：
共生菌的生物固氮(BNF)在可持续农业中发挥着重要作用。然而,当前的量化方法通常是昂贵且不切实际的。这项研究探索了拉曼光谱的潜力，一种非侵入性技术，用于快速评估大豆中的BNF活性。从有和没有根瘤菌生长的大豆植物获得拉曼光谱，以鉴定与BNF相关的光谱特征。δN15同位素比质谱(IRMS)用于确定实际的BNF百分比。采用偏最小二乘回归(PLSR)来建立基于拉曼光谱的BNF定量模型。该模型解释了80%的BNF活性变异。为了增强模型对BNF检测的特异性，无论氮的可用性如何，随后实施了弹性网(Enet)正则化策略。这种方法提供了与大豆中BNF相关的关键波数和生物化学物质的见解。
