Sheep graze in a pasture. ("Grazing Sheep at PaSu Farms" by Heidi Schuyt is licensed under CC BY-NC-SA 2.0)
Sheep graze in a pasture. (“Grazing Sheep at PaSu Farmsby Heidi Schuyt is licensed under CC BY-NC-SA 2.0)

Introduction

New Zealand, one of the largest exporters of agricultural products (such as dairy, meat and wool), relies upon its grazed pastures as a major dietary feed source for livestock. Estimating pasture quantity and quality can aid farmers with determining and providing the most advantageous diet for livestock, thereby optimizing stocking rate and animal performance.

Background

Pastures, or land that is used for grazing, are extensive, complex terrestrial ecosystems. Grazed pastures feature multiple species of grasses and perennials having different growth stages, animal interference from variable grazing patterns, excreta and urine patches.

Traditional methods used to estimate pasture quality involve destructive, labor-intensive procedures whereby pasture samples need to be hand-cut and sent to a lab for chemical analysis. This is a slow and expensive sampling method (an estimated $200 per sample, plus milling and prep costs), and often, by the time the pasture quality information is obtained, the pasture has already been grazed by livestock.

End-to-end precision agriculture, satellite farming or site-specific crop management, is a near real-time fully integrated farming management system based on observing, measuring and responding to inter and intra-field variability in crops; it aims to increase efficient and sustainable use of farm resources while improving profitability, productivity, and a lower ecological footprint.

Dr. Pullanagari Reddy, senior research officer at New Zealand’s Massey University, is leading a research team focused on developing an end-to-end precision agriculture method that includes a complete workflow of measuring, modeling and precision management to characterize and quantify biophysical and biochemical features of pastures in New Zealand. His team uses advanced remote sensing technology to measure pasture and soil spatial variability.

Method

Remote sensing describes the acquisition of information about an object or phenomenon without making any physical contact with the object. To quantify complex grassland areas and their vegetation properties, it is essential to collect accurate detailed measurements near the Earth’s surface.

Malvern Panalytical’s ASD FieldSpec 4 Hi-Res spectroradiometer is a portable instrument providing full-range (350-2500 nm) uniform visible-near infrared (VNIR) data collection near the Earth’s surface. VNIR is non-destructive, requires little or no sample preparation, and allows multiple constituents to be analyzed in a single scan.

Dr. Reddy and his research team have been employing the ASD FieldSpec 4 instrument for remote sensing purposes to ground truth airborne hyperspectral overflight data and to develop a chemometric model, enabling them to quantitatively map grassland properties.

Chemometrics correlate information of a representative set of samples with the data and measurements of reflectance spectra to develop a statistical calibration model. This calibration then trains the instrument to analyze additional unknown, but related samples, leveraging the detailed and more costly analysis of a few hundred samples to analyze (and predict) a much larger set of related samples.

NIRS Chemometrics Calibration Procedure – steps for field and lab applications (Image/ASD)

Results and Discussion

For over a decade, since 2010, Dr. Reddy’s team has collected thousands of spectral measurements during different times of the year and from a wide range of farm conditions.

Field plot. Image courtesy of P. Reddy.

The collected spectra were preprocessed to remove noise and applied to different algorithms to select the best wavelength bands for modeling pasture properties.

Using this data, Dr. Reddy’s team developed an individual statistical calibration model for each pasture quality parameter, including crude protein, fiber, metabolizable energy, phosphorus, potassium, sulfur, and zinc. The team also used the collected spectral measurements to quantify the botanical composition of clover and ryegrass percentage, species diversity, and indicator plants.

Based on the success of this proximal study, the Ministry for Primary Industries, New Zealand’s public service department, entered into a seven-year joint research Primary Growth Partnership program called, “Pioneering to Precision – Application of Fertilizer in Hill Country” with Ravensdown Limited and AgResearch. The aim of the project was to develop a methodology to sense the nutrient status of grassland farms using remote sensing technology to link to soil fertility and deliver fertilizer precisely using GPS-guided topdressing aircraft. The research goal is to develop a precision agriculture program including a complete workflow, such as measuring pasture, modeling, estimating soil fertility and precision management.

Conclusion

Implementing remote sensing techniques in near real-time can effectively improve farm productivity and profitability. The ASD FieldSpec spectroradiometer, as compared to other sensors, is easy to use and cost-effective, significantly reducing the time gap to estimate pasture quality parameters compared to traditional methods.

The end-to-end precision agriculture study developed by Dr. Reddy and his research team using the ASD FieldSpec to measure pasture quality of grassland areas can help ensure farm sustainability and profitability while minimizing the negative impact on the environment.

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