TITLE: USDA LTAR Common Experiment measurement: Obtaining quality metrics in forage aboveground biomass
AUTHORS: Kimberly A. Cassida, Harold Collins

[DESCRIPTION]
Harvesting crops for potential use as livestock forage must include nutritional value measurements to understand how these feedstuffs will meet the consumptive needs of animals. Nutritional value is often called “forage quality.” Nutritional value can change rapidly over hours to days as plants grow, mature, and respond to their environment. Measuring nutritive constituents in forage follows standardized methodologies across commercial and research laboratories. Crude protein (CP) estimates the true protein concentration based on tissue nitrogen analysis and the assumption that most plant protein is 16% nitrogen. Ash measures the total mineral elements present in forage, such as calcium and phosphorus, which do not contribute to its nutritional energy value. Cell wall constituents in forages are quantified using the Van Soest system (Goering and van Soest, 1970), where neutral detergent fiber (NDF) includes cellulose, hemicellulose, and lignin, while acid detergent fiber (ADF) contains cellulose and lignin, and acid detergent lignin (ADL) contains only lignin. This protocol outlines the methodology for analyzing ash, CP, ADF, NDF, and lignin in a forage sample. 

[STEPS]
SECTION: Sample collection
1. Sampling for forage quality requires the collection of biomass samples in addition to those samples outlined in the LTAR aboveground biomass protocol. These additional samples are necessary to capture a sample that reflects the cutting height of forage harvesting equipment or animal grazing. To best represent the forage intended for removal, do not clip forage to ground level; instead, clip samples at a height similar to that of forage harvesting or grazing. Ensure that all personnel clip uniformly at the designated stubble height. Use a height guide or ruler because the eye can easily deceive on this measurement. Grab samples for quality analyses should not be taken directly from fresh material harvested by a machine because the contamination of these samples by soil is possible during harvest, inflating the ash value.
SECTION: Sample collection
2. Forage quality samples should be collected at each scheduled machine harvest or managed grazing event. Continuously stocked pastures should be sampled at least monthly during the grazing season. 
SECTION: Sample processing
3. When measuring total biomass from quadrats or small plot harvesters: 
SECTION: Sample processing
3.1. Within 48 h before biomass harvest, hand clip forage quality subsamples with garden shears from a location within 10 ft of each quadrat area used in the LTAR aboveground biomass sampling protocol. The representative composited forage quality sample should be between 200 g to 400 g of fresh forage. 
SECTION: Sample processing
3.2. The ground area clipped at each location depends on forage type: For fine-stemmed monoculture forages, clipping a hand-sized ground area or a 6-in section of the row may suffice, whereas coarse-grained cover crop mixtures may require a quadrat for effective sampling. When forages are planted in rows, quadrat width should be a multiple of the inter-row spacing to accurately capture row and inter-row biomass. Getting a representative sample of all forage present is key. Clipping quality samples from within the biomass sampling area requires adding the quality sample biomass weight back to the total for the unit. 
SECTION: Sample processing
3.3. Three composited sub-samples per experimental unit suffice for small plots (Grimsbo-Jewitt et al., 2001), while 10-20 composited subsamples suffice on field scale units. 
SECTION: Sample processing
3.4. Place composited samples in clean paper, cloth, or mesh bags and record fresh weights. Use bags large enough to allow air circulation within the forage mass. Paper bags should have perforations to help speed drying (use a drill press to make uniform holes through a stack of bags). 
SECTION: Sample processing
4. When measuring total harvested biomass as weighed bales of hay:

Taking forage quality samples is possible with a commercial hay core sampler, with at least one core from each hay bale composited across the experimental unit. 
SECTION: Sample processing
5. Fresh forage samples should be transported promptly from the field to the dryer—do not pile the bags in the sun for hours or leave them in a truck overnight because the forage will quickly begin to heat, and this heating can change nutritional values. Place the bags in a forced air dryer at 55 °C until the weight is constant (equilibrium) and record the dry weight. A low temperature of 55 °C is required to avoid heat damage and inaccurate crude protein results.
SECTION: Sample analysis
6. Near-infrared reflectance spectroscopy (NIRS) is a rapid, nondestructive technique that uses light reflectance from reference samples of known chemical composition to build prediction equations for chemical constituents in unknown samples (Abrams et al., 1987; Shenk and Westerhaus, 1993). NIRS has emerged as the dominant method of forage quality analysis which ensures its future use in the LTAR network. 
SECTION: Sample analysis
7. Forage samples will be analyzed using NIRS for the primary metrics crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin, and ash.
SECTION: Sample analysis
8. The NIRS Forage and Feed Consortium (NIRSC, Berea, KY) provides validated prediction equations for forage analysis and a detailed handbook of sample preparation and scanning protocols (McIntosh et al., 2022) to research and commercial laboratories. 
SECTION: Sample analysis
9. Ensure analysis consistency across locations by analyzing all samples using these NIRSC equations by:
1. analyzing samples in a research laboratory with access to NIRSC equations or
2. analyzing samples at a commercial laboratory that is using NIRSC equations.
SECTION: Sample analysis
10. Forage analysis by NIRS has extreme sensitivity to sample preparation and spectrum collection methods. Therefore, follow the protocols described in Guidelines for Optimal Use of NIRSC Forage and Feed Calibrations in Membership Laboratories (McIntosh et al., 2022) for sample drying, subsampling, grinding, and spectra collection. These protocols are consistent with National Forage Testing Association (Undersander et al., 2093) and North American Forage Improvement Assoc. (Sheaffer et al., 1995) guidelines for standardized forage testing. An abbreviated overview of key points is listed below, but the reference contains specific details.
SECTION: Sample analysis
10.1. Ideally, the entire sample collected from the field will be dried because representative subsamples from whole mixed plants are extremely difficult to obtain. However, if the sample size makes drying the entire sample unrealistic, chop the collected plants into pieces a few inches in size and mix thoroughly in a large pail/can. Collect a representative subsample of approximately one (1) gallon and place it in a dryer. 
SECTION: Sample analysis
10.2. Grind the entire dry sample. Samples less than 100 g in total weight can go directly to Step 3 (12.3). Larger samples can either be subsampled prior to Step 3 (12.3) or the entire sample can be processed if preferred.  
To subsample, grind the entire dry sample coarsely to pass a 2-8-mm screen in a Wiley mill or equivalent, mix thoroughly, and then split to 100-g size using a riffle splitter or the quadrant subsampling technique (Bohnert et al., 2011).
SECTION: Sample analysis
10.6. Thorough mixing of samples, as detailed in McIntosh et al. (2022), before scanning is essential for good results. Particles will segregate during grinding and even in storage containers because of the normal movement of containers from place to place. Shaking containers or stirring with scoopulas does not provide adequate mixing. Mixing methods are described in McIntosh et al. (2022).
SECTION: Sample analysis
10.3. Final preparation for NIRS analysis using the NIRSC protocol requires grinding to pass a 2-mm screen in a Wiley mill or equivalent grinder, followed by grinding to pass a 1-mm screen in a cyclone mill. Do not omit steps or use different screen sizes because this deviation will change particle size distribution, which affects analysis results. Keep grinders in good condition with effective grinding surfaces and screens. 
SECTION: Sample analysis
10.4. The final ground sample size should be 50-100 g for analysis and archiving. NIRS scanning is non-destructive and requires 15 g-25 g of dry sample, depending on the instrument model.
SECTION: Sample analysis
10.5. If samples are not ground immediately upon removal from the dryer, hygroscopic constituents will quickly absorb atmospheric moisture. To facilitate grinding, use samples containing at least 93% dry matter (7% moisture). Attempting to grind wetter samples will likely cause fine material to stick to inside surfaces of grinders, skewing the proportions of nutritive constituents. 

 

SECTION: Sample analysis
10.7. When scanned in the NIRS instrument, ground samples must be 95-97% dry matter (DM) for grass and grass/legume mixtures and 93.5-95% DM for legume hay and haylage. Samples outside these ranges will give erroneous results. Monitor DM results when running the first few samples. 

If samples are too wet upon initial analysis, transfer them to food-grade tin containers and place them in a dryer at 55 °C in 15-minute increments until they reach the target DM. 
If samples are too dry, leave opened containers on the benchtop for a few hours until they acquire enough atmospheric water to reach target analysis moisture.
SECTION: Reporting results
11. Metadata required for reporting NIRS results include: 

NIRS instrument brand, model number, and software
NIRSC calibration name, release year, and performance statistics, including SEC, r^2, and 1-VL for each constituent.
Date scanned
Worker name
GH and NH statistics for the prediction
Name of NIRSC wet chemistry reference laboratory used for validation, and validation statistics including correlation coefficient (R^2), standard error of prediction (SEP), standard error of cross validation (SECV), bias, and the number of samples used in the validation test.
SECTION: Concurrently sampled covariate metrics
12. Management data
Biomass removed from the field
Biomass left in the field
Elemental concentrations in ground tissue samples
Treatment name and crop species and variety
Collection date
Sampling implement (type of garden shear)
Exact number of subsamples within a composite
Worker name
NIRS instrument brand, model number, and software
NIRSC calibration name, release year, and performance statistics
SECTION: Calculations
13. All forage constituents will be reported on a 100% dry matter basis (e.g., 0% moisture).
SECTION: Quality assurance and quality control
14. A set of sample standards will be developed and distributed among locations studying forage quality. Standards will include a grass, a legume, a 50:50 grass:legume mix, and corn silage. Include duplicate standard samples of the appropriate calibration class in every sample set submitted for forage-quality analysis. 
SECTION: Quality assurance and quality control
15. NIRSC prediction equations will flag samples that fall outside the expected numeric bounds of the calibration (H value > 3). Carefully examine samples flagged as outliers for recording, sampling, sample preparation, or scanning errors, and if no errors exist, analyze the samples by wet chemistry at a NIRSC reference laboratory.
SECTION: Archiving
16. Keep subsamples (50 g-100 g) at Room temperature in controlled areas that are as dry and dark as possible. Glass containers are preferable because insects and rodents can chew into plastic.
SECTION: Illustrative Media
18. 
 

 
 

 

 

 

 
 

SECTION: Recommendations for data collection
17. Table 1. Summary of recommendations for the measurement of forage quality indicators in aboveground biomass leaving the field.
 
 
 
SECTION: Sample analysis
10.8. NIRS results generated from NIRSC equations should be validated in an NIRSC wet chemistry reference laboratory. Validation methods are outlined in McIntosh et al. (2022).