In rice nitrogen nutrition research, leaf nitrogen content is closely linked to chlorophyll concentration, photosynthetic capacity, and nitrogen assimilation enzyme activity. Under optimal nitrogen supply, robust chlorophyll synthesis and well-developed mesophyll cells cause a drop in visible light reflectance (particularly at the green reflectance peak near 550 nm) and an increase in near-infrared (NIR, 700–1300 nm) reflectance. Conversely, nitrogen deficiency triggers chlorophyll degradation and structural cellular damage, resulting in the opposite spectral trend. Handheld field spectroradiometers capture rice canopy or single-leaf reflectance spectra to compute diagnostic indices—such as NDVI, GNDVI, red edge position (REP), and Nitrogen Reflection Index (NRI)—indirectly modeling the plant's internal nitrogen status. These spectral parameters demonstrate significant correlations with the expression levels of key nitrogen metabolism genes (e.g., glutamine synthetase, GS; nitrate reductase, NR; ammonium transporters, AMTs), providing a physiological foundation for spectral-assisted selection of nitrogen-efficient genotypes. By evaluating varying nitrogen treatments across critical phenological stages (tillering, jointing, and heading), researchers can synchronize canopy spectral collection with biochemical tissue testing to build quantitative models correlating spectral indices with physiological indicators. Empirical data indicates that the red edge position (REP) exhibits strong positive correlations with leaf nitrogen content and GS activity, serving as a robust descriptor for rice nitrogen status. Concurrently, the Ratio Vegetation Index (RVI) exhibits highly stable correlations with NR activity across separate growth stages. The HG-iSpectra1000 handheld field spectroradiometer, engineered by Hagorun Technology Limited, features a lightweight design optimized for rapid, single-handed field operation, streamlining multi-point rice canopy spectral collection and serving as an efficient phenotyping tool for nitrogen gene expression research. Characterizing specific spectral response variations among diverse nitrogen-efficiency genotypes forms the basis of spectral-assisted crop breeding. Nitrogen-efficient genotypes maintain elevated chlorophyll concentrations and stable photosynthetic rates under low-nitrogen conditions, displaying significantly lower attenuation in spectral indices compared to nitrogen-inefficient lines. This clear spectral phenotype allows for the rapid classification of nitrogen-efficient germplasm directly in breeding plots.

Co-registering spectral phenotyping data streams with nitrogen metabolism gene expression metrics serves as a vital framework for resolving the molecular mechanisms governing rice nitrogen-use efficiency (NUE). Under identical nitrogen supply regimes, varying rice genotypes exhibit distinct expression profiles for genes regulating nitrogen uptake, translocation, and assimilation, and these molecular variances translate directly into diagnostic canopy spectral attributes. Utilizing portable spectroradiometers to extract canopy indices alongside leaf tissue sampling for transcriptome sequencing or quantitative real-time PCR (qRT-PCR) enables the construction of stable regression models linking spectral indices to specific gene transcripts. For instance, studies have demonstrated that NDVI correlates positively with OsAMT1.2 (ammonium transporter gene) expression, while the red edge position (REP) displays a strong linear relationship with OsGS1.2 (cytosolic glutamine synthetase gene) transcription. This spectral-to-gene expression modeling framework opens paths for utilizing remote sensing to rapidly evaluate the expression status of key metabolic pathways, bypassing the high costs and low throughput of large-scale molecular screens. The HG-iSpectra1000 handheld field spectroradiometer from Hagorun Technology Limited integrates satellite positioning and orientation sensor modules, automatically tagging sample data with geographical coordinates, pitch, and azimuth angles to ensure data standardization and robust sample traceability. For the rapid screening of nitrogen-efficient germplasm resources, large breeding populations can be characterized via spectral parameters during the seedling or tillering stages. Identifying lines that sustain elevated spectral values under nitrogen-limiting conditions narrows down candidate populations for downstream molecular testing, accelerating breeding cycles. Compared to traditional protocols that evaluate nitrogen efficiency via post-harvest yield trials, spectral-assisted screening offers an early-stage predictive approach that shortens evaluation timelines. Regarding genotype-specific precision fertilizer management, leveraging differential spectral responses between nitrogen-efficient and nitrogen-inefficient varieties supports the development of genotype-specific side-dressing models. Field deployment of handheld spectroradiometers enables rapid canopy index validation to guide variable-rate nitrogen fertilization, improving fertilizer efficiency while mitigating environmental nitrogen losses.

Implementing canopy spectral indices acquired via handheld field spectroradiometers as high-throughput plant phenotypic parameters significantly advances mapping studies targeting rice NUE genes. Within mapping populations (such as recombinant inbred lines, RILs; chromosome segment substitution lines, CSSLs), logging canopy indices across varied lines under distinct nitrogen regimes allows for quantitative trait locus (QTL) mapping when fused with high-density molecular marker maps, isolating candidate gene intervals regulating both spectral phenotypes and nitrogen utilization. Compared with destructive tissue sampling for nitrogen assays and enzyme extractions, spectral index phenotyping offers a non-destructive, rapid, and repeatable methodology optimized for multi-temporal, large-scale mapping evaluations across diverse environments. In genome-wide association studies (GWAS), utilizing time-series spectral indices from separate growth windows as phenotypic input layers for association mapping against genome-wide single nucleotide polymorphism (SNP) datasets facilitates the identification of significant loci and candidate genes associated with nitrogen-use efficiency. This methodology has been validated in corn and wheat systems, and it shows immense potential for rice breeding. The HG-iSpectra1000 handheld field spectroradiometer from Hagorun Technology Limited supports full-day field data collection on a single battery charge, featuring high internal data capacity and streamlined export functions tailored for large-scale crop population phenotyping campaigns. For field validation and target regional selection of nitrogen-efficient cultivars, handheld instruments can characterize regional trial varieties across separate eco-zones and nitrogen treatment blocks to build an integrated spectral evaluation index for variety performance. This framework delivers predictive performance diagnostics much earlier than traditional yield-dependent assessments and captures dynamic crop response profiles across the entire vegetative cycle, providing a robust decision-support tool for variety registration and commercial release.

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