The driving force for this work is rooted in data that confirms the contamination of streams and lakes caused from excessive use of nitrogen, pesticides and other soil amendments. Traditional analytical (wet chemistry) methods are too slow and too costly for detecting ecological abuse. A technology that would characterise the nutritional status of growing plants in a timelier manner (preferably in real time as an applicator moves through the field) is needed to control the volume of amendments. This paper explores the potential of near infrared (NIR) spectrometry for measuring nitrogen in plant tissue. In particular, it discusses the development of nitrogen calibrations, and performance of those calibrations, for both green- and dry-grass tissue. Results, based on collaborative studies by several researchers indicate that nitrogen can be measured with an SEP of 0.411% and 0.167% for green- and dry-grass tissue, respectively.

A hand-held near-infrared (NIR) meter (called the Gmeter), based upon gap-second derivative (GSD) theory, was designed, constructed, and performance-tested. The design incorporated narrow-band interference filters for isolating the three wavelengths required by the GSD calculations. A microprocessor was included in the design to facilitate both stand-alone and personal computer (PC) operation. The Gmeter was mounted in a caddy for making measurements within the laboratory. Performance of the Gmeter was compared with the performance of a FOSS NIRSystems Model 6500 spectrophotometer for measuring protein in soy-protein/sugar mixtures and for measuring nitrogen in fescue grass tissue. Two calibrations were developed on both instruments: (1) single-term GSD equations and (2) three-term (log 1/R) multiple linear regression (MLR) equations. Second-derivative calibration experiments on the Model 6500 spectrophotometer formulated the basis for selecting the three filters in the Gmeter. Model 6500 data indicated that the GSD calibration [coefficient of variation (CV) = 5.14%] performed better than a three-term MLR equation (CV = 8.0%). In addition, the Gmeter performed almost as well (CV = 6.30%) as the Model 6500 (CV = 5.14%) for measuring protein in the mixtures using single-term GSD equations. An exciting extra in this study was the fact that measurements from the same three filters selected for determining protein in protein/sugar mixtures could be used for determining nitrogen (CV = 17.2%) in dry-grass tissue.

The design and performance of a low-cost no-moving-parts handheld NIR spectrometer are discussed. Dubbed the TWmeter, this device was conceived for use by researchers and others in developing countries unable to afford more costly technology found in developed countries. Two design features contribute to the novelty of this spectrometer: (1) three unfiltered light emitting diodes (LEDs) with peak emissions at 700, 880, and 940 nm for measuring chlorophyll in plant tissue and moisture in paper, and (2) a silicon intensity-to-frequency detector (a silicon detector with an integral voltage-to-frequency converter). The latter feature allows an ordinary microcomputer to obtain intensity measurements by counting for a fixed length of time, thus avoiding the need for higher-priced analog-to-digital hardware. Performance tests, using multiple linear regression for calibration, demonstrate that chlorophyll and moisture can be determined with a root mean squared standard error of prediction of 0.99 mg/cm2 of leaf surface for a range of 1–8 mg/cm2 and 1.04% (wet basis) for a range of 30–65% moisture, respectively. Development of the TWmeter (costing less than $300 US), demonstrates that spectrometry need not be costly.

The sections in this article are Introduction Historical Perspective Biological Samples Qualitative NIR Spectroscopy Fundamental Components Water, Oil, Protein and Starch Water Oil Protein Starch Plant Materials Grains Wheat and Wheat Components Other Grains Tea Coffee Tobacco Food and Drink Food Cereals Meats, Poultry and Fish Fresh Fruit Additives: Molasses, Honey, Corn Syrup and Lemon Extract Sweets: Sucrose, Saccharin, Extra and Chocolate Drink Milk and Water Ethanol–Water Mixtures Spirits Fiber Cotton, Flax and Wool Human Samples Skin Hair Blood Urine Future Trends in NIR Spectroscopy Hyphenated Systems Imaging Spectrometry and Remote Sensing Hand‐Held Spectrometry Dedication