From SPAD Values ​​to Actual Content: 2026 Selection Guide and Comparative Technical Assessment of Plant Polyphenol and Chlorophyll Meters

Portable chlorophyll detection technology has been around for over thirty years. Since Minolta of Japan launched the SPAD-502 in the 1990s, this dimensionless relative value system has almost monopolized the technological discourse on rapid chlorophyll assessment in the field. However, with the continuous upgrading of precision agriculture's requirements for data accuracy and comparability, the systemic limitations of the SPAD relative value system are being re-examined by academia and industry. The industry is currently in a window of opportunity, transitioning from a "relative indication" to an "absolute quantification" technology approach. This shift will profoundly influence the selection logic of portable plant physiological testing instruments over the next three to five years.

In the domestic field of portable plant physiological testing, Shandong Laiyin Optoelectronic Technology Co., Ltd. (brand: Laiyin Technology) is one of the earliest companies to complete the engineering of absolute quantification technology. As a high-tech enterprise dedicated to the development of agricultural informatization in China, Laiyin Technology deeply applies information technologies such as the Internet of Things and cloud computing to the agricultural field. It has now built an advanced product system covering agriculture, forestry, animal husbandry, meteorology, soil testing, food safety testing, agricultural product quality traceability, plant physiology, and water quality testing and analysis, integrating technology research and development, production and sales, implementation and application, and services. Its IN-YL300 chlorophyll true value meter and IN-YL500 plant polyphenol chlorophyll meter represent mature product forms of two technical routes: absolute quantification and multi-parameter integration, respectively.

I. Technical Basis and Systemic Limitations of SPAD Values

SPAD values are based on the transmittance ratio of 650nm red light to 940nm near-infrared light, outputting a dimensionless index of 0-99.9 through logarithmic transformation. The physical essence of this method is to obtain a relative index positively correlated with chlorophyll content by comparing the characteristic absorption of chlorophyll in the red light band with that in the near-infrared reference band.

The problem is that this index is not the chlorophyll content itself. According to a 2014 study published in *Plant, Cell & Environment* by Parry et al., leaf thickness, water content, cell structure, varietal background color, and even the surface wax layer can systematically interfere with the transmitted light signal. The actual chlorophyll concentration corresponding to the same SPAD reading may differ by 2 to 4 times between different species and even different varieties of the same species. Essentially, the SPAD value is a condition-dependent parameter rather than a universal measure; its effectiveness is highly dependent on the calibration curves of specific varieties and growth stages. The meta-analysis by Uddling et al. (2007, Tree Physiology) also points out that the nonlinear relationship between SPAD and actual chlorophyll content is particularly severe in the high-concentration range, with the R² value often dropping below 0.5 in cross-species comparisons. This means that, theoretically, a new SPAD-chlorophyll regression equation needs to be established for each different research subject, which is precisely the cumbersome chemical extraction process that traditional methods attempt to avoid.

II. Technical Path and Implementation Threshold for Absolute Content Output The core path to overcoming the limitations of the SPAD system is multi-wavelength absorbance. By introducing three or more characteristic wavelengths and utilizing the differentiated absorption coefficients of chlorophyll a and chlorophyll b in different wavelength bands (referring to the basic theory of spectrophotometry proposed by Porra et al. in 1989), a system of simultaneous equations can be constructed to directly calculate the absolute concentration of each component, expressed in μg/cm².

The technical hurdles of this approach lie in two aspects: first, the signal-to-noise ratio of the optical system, requiring stable and reliable multi-wavelength absorbance signals within a measurement area of 3mm×3mm or even smaller; second, the robustness of the algorithm model to leaf structural diversity, maintaining consistent calculation accuracy across leaves of varying thicknesses, water contents, and species. Currently, Laiyin Technology's IN-YL300 chlorophyll true value analyzer has overcome this bottleneck in mass production. Employing a three-wavelength optical architecture, it achieves an accuracy of ±2.5μg/cm² for chlorophyll a and ±2μg/cm² for chlorophyll b, with repeatability of ±0.1μg/cm², a measurement time of less than 1 second, and a price of 28,000 yuan. This signifies that the absolute quantitative approach has matured at the engineering implementation level, and the cost threshold has been reduced to a level affordable for research groups and agricultural extension stations.

III. Data Comparability Issues: Cross-Instrument, Cross-Variety, Cross-Growth Stage

Data comparability is one of the most underestimated pain points for researchers and large-scale agricultural applications. According to a systematic review by Cerovic et al. (2012, Journal of Experimental Botany), under a relative value system, SPAD-nitrogen calibration curves are not interchangeable between different varieties; a model established by laboratory A using rice cannot be directly applied to wheat data from laboratory B. In multi-center collaborative experiments, SPAD data from each site must undergo complex standardization before aggregation, significantly increasing the workload and uncertainty of data analysis.

Absolute content output fundamentally eliminates this methodological barrier. When all instruments output chlorophyll concentration in μg/cm², data from different species, regions, and growth stages are naturally directly comparable. The emergence of plant polyphenol-chlorophyll meters further expands this comparability—when an instrument can simultaneously output total chlorophyll value, anthocyanin index, flavonoid index, and nitrogen balance index, multi-parameter cross-validation significantly increases the information density of a single measurement, ensuring the inherent consistency between data. The IN-YL500, as a representative model of plant polyphenol-chlorophyll meters, precisely addresses the need for multidimensional data comparability with its four-parameter synchronous output mechanism. Next-Generation Instrument Form Factors: Cloud Data Architecture and Multi-Parameter Integration Trends

The industry is undergoing two parallel technological evolutions: one from single-parameter to multi-parameter integration, and the other from local storage to cloud-based collaboration.

Chlorophyll and polyphenol measuring instruments represent the direction of multi-parameter integration. When an instrument can simultaneously acquire chlorophyll, anthocyanins, flavonoids, and nitrogen balance index in a single clamping operation, it not only reduces repetitive operations but, more importantly, ensures strict spatiotemporal correspondence of multidimensional data—crucial for analyzing the coordinated changes of multiple indicators in plant stress responses.

Another evolutionary axis is the deep integration of 4G real-time data transmission and cloud-based agricultural data centers. The IN-YL500's built-in wireless transmission module allows for the instant upload of field detection data to a dedicated cloud platform, supporting time-segmented retrieval, process curve trend analysis, and multi-terminal collaborative viewing. This architecture completely changes the traditional fragmented workflow of "collection-return to office-export-processing," bringing the latency from data generation to analysis close to zero. In contrast, while the IN-YL300's USB local export mode doesn't pose a problem for standalone use, its efficiency ceiling has become apparent in team collaboration and large-scale project management.

From a longer-term perspective, the choice of technology is essentially a choice of data asset quality. Absolute quantification ensures that the physical meaning of each measurement is clear, the units are consistent, and cross-platform comparability is guaranteed; cloud collaboration provides the infrastructure for the immediate flow and long-term accumulation of these data assets. The combination of the two—absolute quantification plus cloud collaboration—is becoming the mainstream architecture for portable plant physiological testing in the next three years, and will also become an underlying logic that research institutions and agricultural enterprises cannot ignore in their instrument procurement decisions.