Application of Handheld Near-Infrared Spectroscopy (NIRS) as a Portable Phenotyping Tool in Horticultural and Agronomic Breeding Programs

Hunter Weber

March 21, 2024 at 5:35 pm | Updated March 21, 2024 at 5:35 pm | 4 min read

By Galen George, Director of Applied Science at Felix Instruments.

Introduction

Plant breeding stands as a cornerstone of horticulture and agronomy, disciplines vital for the sustainability and advancement of agriculture worldwide. This scientific practice, which involves the selective crossing of plants to produce new cultivars with desirable traits, is fundamental in addressing the multifaceted challenges faced by contemporary agriculture. The increasing global population, coupled with the impacts of climate change and the pressing need for environmental conservation, underscores the urgency for more efficient, resilient, and nutritious crops.

The primary directives of most breeding programs are to enhance crop yield, improve nutritional value, and confer resistance to biotic and abiotic stressors, such as diseases, pests, drought, salinity, and extreme temperatures. This not only contributes to food security but also supports sustainable farming practices by reducing dependence on chemical pesticides and fertilizers, thereby minimizing agriculture’s ecological footprint.

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Phenotyping is a critical component of every plant breeding program that involves the systematic measurement and evaluation of observable physical and biochemical traits. Traditionally, the phenotyping process requires time and labor-intensive destructive laboratory analysis. In recent years, modern technology has allowed for many advancements in phenotyping with advanced technologies like high-throughput imaging, remote sensing, and automated data analysis tools to efficiently measure and analyze traits across large populations. Portable (or handheld) near-infrared spectroscopy (NIRS) tools, such as the Felix Instruments F-750 Produce Quality Meter, are among these technological advancements that can provide breeders with rapid, non-destructive, and accurate quantitative measurements of physicochemical attributes within the exocarp and mesocarp tissue of horticultural and agronomic commodities.

NIRS For Phenotyping

Previous Research 

Near-Infrared Spectroscopy (NIRS) has recently been adapted as a revolutionary, non-destructive tool for rapid phenotyping in plant breeding applications. By utilizing the unique absorption characteristics of near-infrared light by organic molecules, NIRS facilitates the quick assessment of a wide range of phenotypic traits without harming the plant material. This technology has proven instrumental in evaluating critical phenotypic parameters such as moisture content, nutrient composition, and disease resistance markers, which are essential for breeding programs to develop high-yield and resilient plant varieties. NIRS enables the real-time analysis of these traits, significantly accelerating the breeding cycle and enhancing the efficiency of selection processes. Its capability to rapidly and accurately assess multiple traits simultaneously positions NIRS as a cornerstone technology in modern plant breeding. It offers a powerful means to meet the growing demands for food security and agricultural sustainability. 

Table 1. Horticultural and Agronomic Commodities and Corresponding Physicochemical Properties Modeled with NIRS. Numbers within the table correspond to the reference number. 

F-750 Produce Quality Meter

The Felix F-750 Produce Quality Meter, paired with the free companion AI-powered chemometrics platform, AppBuilder, provides an all-in-one solution for plant breeders that wish to create predictive NIRS models for phenotypic traits in virtually any agricultural or horticultural commodity. Users can fully customize spectral pre-treatment, model type (PLS, ANN), wavelength range, model tuning parameters, user interface, and more due to the open, low-code nature of the AppBuilder software. Data captured by the F-750 is capable of direct transfer to a local server via Wi-Fi or can be customized to integrate into any data-hosting or management system for more robust data transparency and regulation.  

Figure 1. Second derivative absorbance spectra of avocados at varying maturity levels from 729-975nm. Graph exported directly from AppBuilder software.

Figure 2. Reference vs. predicted values for a brix model built with Hayward (green) kiwifruit at varying maturity levels. Graph exported directly from AppBuilder software.

Conclusion

NIRS is a robust technology that can allow any breeding program to perform non-destructive phenotyping while utilizing a fraction of the time, labor, and resources required for conventional laboratory testing methods. Previous research has demonstrated the ability of portable NIRS devices to accurately model key physicochemical traits in various agricultural and horticultural commodities.

The Felix F-750 Produce Quality Meter and AppBuilder software provides breeders with an all-in-one solution for rapid, non-destructive phenotyping, From the creation of fully customizable predictive models to deploying those models onto a handheld and user-friendly device to managing their data streams with full transparency.

 

By Galen George, Director of Applied Science at Felix Instruments.

References

  1. Bai W, Yoshimura N, Takayanagi M, Che J, Horiuchi N, Ogiwara I. (2016). Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements. J Vis Exp. 28;(112):53981.
  2. Donis-González, I. R., Valero, C., Momin, M. A., Kaur, A., & Slaughter, D. C. (2020). Performance evaluation of two commercially available portable spectrometers to non-invasively determine table grape and peach quality attributes. Agronomy, 10(1), 148.
  3. Ecarnot, M., Bączyk, P., Tessarotto, L., & Chervin, C. (2013). Rapid phenotyping of the tomato fruit model, Micro-Tom, with a portable VIS–NIR spectrometer. Plant physiology and biochemistry, 70, 159-163.
  4. León-Moreno, L. (2012). Usefulness of portable near infrared spectroscopy in olive breeding programs. Spanish Journal of Agricultural Research, 10(1), 141-148.
  5. Sánchez, M. T., De la Haba, M. J., Benítez-López, M., Fernández-Novales, J., Garrido-Varo, A., & Pérez-Marín, D. (2012). Non-destructive characterization and quality control of intact strawberries based on NIR spectral data. Journal of Food engineering, 110(1), 102-108.
  6. Spielbauer, G., Armstrong, P., Baier, J. W., Allen, W. B., Richardson, K., Shen, B., & Settles, A. M. (2009). High‐throughput near‐infrared reflectance spectroscopy for predicting quantitative and qualitative composition phenotypes of individual maize kernels. Cereal chemistry, 86(5), 556-564.

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