Dualex便攜式智能氣象-葉綠素-花青素-黃酮醇測(cè)量?jī)x

摘要

準(zhǔn)確估計(jì)和及時(shí)診斷作物氮素狀況有助于季節(jié)施肥管理。為了評(píng)估三個(gè)葉片和冠層光學(xué)傳感器在無損診斷冬小麥氮素狀況方面的性能，使用七個(gè)小麥品種和多種氮素處理（0–360 kg N ha?1）進(jìn)行了三個(gè)試驗(yàn)，于2015年至2018年在中國(guó)江蘇省進(jìn)行。在主要生長(zhǎng)期，分別使用兩個(gè)葉片傳感器（SPAD 502，Dualex 4 Scientific+）和一個(gè)冠層傳感器（RapidSCAN CS-45）獲取葉片和冠層光譜數(shù)據(jù)。同時(shí)測(cè)定了葉片氮濃度（LNC）、葉片氮積累（LNA）、植株氮濃度（PNC）、植株氮積累（PNA）和氮素營(yíng)養(yǎng)指數(shù)（NNI）五個(gè)氮素指標(biāo)。在每個(gè)生長(zhǎng)階段，建立了六個(gè)基于傳感器的指數(shù)（葉片水平：SPAD、Chl、Flav、NBI、冠層水平：NDRE、NDVI）與五個(gè)N參數(shù)之間的關(guān)系。結(jié)果表明，基于Dualex的NBI在四個(gè)葉傳感器指標(biāo)中表現(xiàn)相對(duì)較好，而RS傳感器的NDRE在不同生長(zhǎng)階段的五個(gè)N指標(biāo)估計(jì)中，由于冠層傳感器的采樣面積較大，因此表現(xiàn)最好。NNI診斷模型的面積一致性范圍為SPAD為0.54至0.71，NBI為0.66至0.84，NDRE為0.72至0.86，SPAD為0.30至0.52，NBI為0.42至0.72，NDRE為0.53至0.75。總的來說，這些結(jié)果揭示了基于傳感器的診斷模型在快速、無損診斷N狀態(tài)方面的潛力。

關(guān)鍵詞：氮指示劑；氮營(yíng)養(yǎng)診斷；光學(xué)傳感器；光譜指數(shù)

Evaluation of Three Portable Optical Sensors for Non-Destructive Diagnosis of Nitrogen Status in Winter Wheat

Abstract

The accurate estimation and timely diagnosis of crop nitrogen (N) status can facilitate in-season fertilizer management. In order to evaluate the performance of three leaf and canopy optical sensors in non-destructively diagnosing winter wheat N status, three experiments using seven wheat c*rs and multi-N-treatments (0–360 kg N ha?1) were conducted in the Jiangsu province of China from 2015 to 2018. Two leaf sensors (SPAD 502, Dualex 4 Scientific+) and one canopy sensor (RapidSCAN CS-45) were used to obtain leaf and canopy spectral data, respectively, during the main growth period. Five N indicators (leaf N concentration (LNC), leaf N accumulation (LNA), plant N concentration (PNC), plant N accumulation (PNA), and N nutrition index (NNI)) were measured synchronously. The relationships between the six sensor-based indices (leaf level: SPAD, Chl, Flav, NBI, canopy level: NDRE, NDVI) and five N parameters were established at each growth stages. The results showed that the Dualex-based NBI performed relatively well among four leaf-sensor indices, while NDRE of RS sensor achieved a best performance due to larger sampling area of canopy sensor for five N indicators estimation across different growth stages. The areal agreement of the NNI diagnosis models ranged from 0.54 to 0.71 for SPAD, 0.66 to 0.84 for NBI, and 0.72 to 0.86 for NDRE, and the kappa coefficient ranged from 0.30 to 0.52 for SPAD, 0.42 to 0.72 for NBI, and 0.53 to 0.75 for NDRE across all growth stages. Overall, these results reveal the potential of sensor-based diagnosis models for the rapid and non-destructive diagnosis of N status.  

Keywords: nitrogen indicator; nitrogen nutrition diagnosis; optical sensor; spectral index 

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