Introduction
A relatively new analysis used to evaluate grass forage quality is measurement of total nonstructural carbohydrates (TNC). Total nonstructural carbohydrates drive the efficiency of the rumen and the ensiling process. In the rumen, increasing TNC increases the use of rumen degradable protein and therefore increases microbial protein production. During the ensiling process, increasing TNC increases rate of fermentation and which increases the preservation of the ensiled nutrients.
Grass cultivars are normally selected for yield and resistance to disease and pests. From a milk production standpoint, palatability and the cows’ intake are very important. Dry matter intake allows the cow to meet her physiological requirements and supports efficient milk production. We are just beginning to see interest by researchers to learn more about a cultivar’s palatability and intake potential.
Understanding these performance differences between cultivars is of growing importance. In addition to the palatability and intake of the respective grasses, the nutrients derived from the grasses greatly influence milk production. The efficiency of grass protein or nitrogen utilization for milk production tends to be low, partially due to the lack of carbohydrate available to the microorganisms in comparison to the protein available to the microorganisms. This reduces the efficiency of capture of rapidly degradable plant nitrogen by the rumen microbial population and much of the nitrogen is excreted in the urine. When additional sugars are introduced to the rumen, microbial protein production is increased A major source of energy for microbial nitrogen synthesis in animals grazing grass forages is TNC.
Very little work has been done studying the natural variations between cultivars in sugar content. In a study examining palatability, researchers reported three tall fescue varieties having 13.3% water-soluble carbohydrates were considered more palatable to cattle than three others having only 10.8%..
A production study from the United Kingdom reported that dairy cows had higher feed dry matter intake (12.5 vs. 10.8 kg DM/day) and increased milk production (15.3 vs. 12.6 kg/day) when consuming green chop forages selected for higher TNC over typical ryegrasses. In addition, researchers observed differences in efficiency of use of feed nitrogen. Authors theorized this was primarily due to differences in the microbial capture of rumen degradable nitrogen. The data also suggests that selecting forages for higher TNC may have the potential to reduce nitrogen excretion.
The objectives of this study were to: Sample total nonstructural carbohydrates (TNC) and dry matter (DM) yield of cool-season forage grasses throughout the growing season.
- Samples total nonstructural carbohydrates (TNC) and dry matter (DM) yield to cool-season forage grasses throughout the growing season.
- In year 1, look specifically at seasonal and diurnal variations in a large population of cool season grasses.
- Observe potential variations in the relationship between the level of TNC and DM yield among species and varieties of cool-season forage grasses.
- In year 2, plant new varieties that have potential to be high in sugars including varieties studied in grazing trails in the UK and determine total sugar production throughout the season.
Materials and Methods
Year 1
Eleven perennial ryegrasses, four orchard grasses, one festolium, and one prairie grass were planted in 4 x 25’ field plots in Tillamook, Oregon. Three replicates of each variety were planted. Randomization was used to assign variety to plot. Each of the 51 field plots was harvested on six sampling dates in the 2001-growing season.
For each of the six dates, DM yield of each field plot was recorded. For three dates, April 20, June 28, and October 1, forage samples were collected for TNC analysis in both the early morning and late afternoon. Immediately after cutting, samples were placed on dry ice to reduce respiration losses. Samples were dried in an oven. TNC analyses were performed at Dairy One Laboratory.
Year 2
Ten perennial ryegrasses were identified as being possible high sugar grasses from forage breeders around the world. Cultivars were planted in 4’ x 25’ field plots and replicated three times. Each of the 30 field plots was harvested on six sampling dates in the 2002 - growing season. Immediately after cutting, samples were placed on dry ice to reduce respiration losses. Samples were dried in an oven. TNC analyses were performed at Dairy One Laboratory.
Results and Discussion
Non-structural carbohydrates in cool season grasses do significantly vary between varieties, species, from am to pm and seasonally. The variations found appear tremendous and can be difficult to document because of the enormous variation. However, this project was able to demonstrate that certain cultivars and varieties consistently were higher in non-structural carbohydrates than others. Table 1 is the non-structural carbohydrate data for year 1. This table shows the varieties study and the actual percent non-structural carbohydrate value for the testing period.
Interestingly, some varieties appeared to fluctuate more from am to pm than others, however, all varieties demonstrated some variation. Varieties are listed by average non-structural carbohydrate concentration from the highest to lowest. The value in the far right column labeled “total” is actually an index rating to rate varieties. The highest varieties are all ryegrasses. Matua is a prairie grass and ended up averaging in the middle of those varieties tested. The festuolium tested was Barfest, averaging below all the ryegrasses and just above the orchard grasses. All four varieties on the bottom of the table are orchard grasses. Figure 1, 2, and 3 illustrate the relationship observed between nonstructural carbohydrates and dry matter yield. Interestingly, this relationship was negative for April and October and slightly positive for June. The season average was negative and is illustrated in Figure 4.
This phenomenon is interesting, but not really surprising. It has been understood for years that slow growing hay, for example, will be of higher quality than fast growing hay. I believe during the middle of the summer growth rate slowed, actually shifting quality (non-structural carbohydrates) higher. Yield data tend to support this theory, but are not conclusive.
Cultivar | 4-20am | 4-20pm | 6-28am | 6-28pm | 10-1am | 10-1pm | Total |
---|---|---|---|---|---|---|---|
Elgron | 14.3 | 13.7 | 18.2 | 25.3 | 21.0 | 23.9 | 116.4 |
Tetralite | 14.8 | 14.7 | 16.3 | 25.1 | 19.4 | 23.9 | 114.2 |
Herbie | 11.5 | 13.3 | 19.2 | 25.9 | 19.6 | 21.7 | 111.2 |
BG-34 | 12.6 | 16.2 | 17.2 | 19.4 | 17.1 | 27.3 | 109.8 |
Tonga | 15.8 | 21.7 | 16.0 | 20.6 | 15.2 | 20.0 | 109.3 |
Glenn | 13.8 | 17.6 | 17.0 | 19.1 | 19.5 | 21.8 | 108.8 |
Bison | 12.1 | 12.4 | 18.4 | 24.5 | 15.9 | 22.9 | 106.2 |
Matua | 12.2 | 22.6 | 14.5 | 21.9 | 15.5 | 18.7 | 105.4 |
Barfort | 14.4 | 18.0 | 14.0 | 23.5 | 13.8 | 20.3 | 104.0 |
Flanker | 12.9 | 13.6 | 17.7 | 21.0 | 15.2 | 23.5 | 103.9 |
Belramo | 12.5 | 14.1 | 14.6 | 19.2 | 18.3 | 17.5 | 96.2 |
Bronsyn | 9.0 | 15.1 | 17.6 | 21.2 | 13.0 | 16.5 | 92.4 |
Barfest | 11.7 | 15.9 | 13.5 | 12.2 | 13.3 | 21.8 | 88.4 |
Orion | 14.3 | 11.9 | 17.1 | 22.4 | 10.2 | 11.1 | 87.0 |
Piza | 10.0 | 12.4 | 12.3 | 19.6 | 8.2 | 12.5 | 75.0 |
Cambria | 9.7 | 14.8 | 9.1 | 15.6 | 10.3 | 12.8 | 72.3 |
Baridana | 10.8 | 11.6 | 8.8 | 14.0 | 9.0 | 16.5 | 70.7 |
In year 2, data collection focused on documenting the total pounds of sugars or nonstructural carbohydrates produced. Tables 2, 3 and 4 illustrates the actual data by cutting. Amazon ryegrass averaged the highest percent non-structural carbohydrates throughout the season at 20.9 with Impact the lowest at 16.3%. When we determined total dry matter produced and consequently, total non- structural carbohydrates produced, the ryegrass variety from the UK, Aberavon was the highest at 2306 lbs/acre. This variety is one in particular that has been bred in Europe to be higher in non-structural carbohydrates than most ryegrasses.
Cultivar | 3-Apr | 26-Apr | 13-May | 13-Jun | 31-Jul | 3-Nov | Average |
---|---|---|---|---|---|---|---|
Tivoli | 20.8 | 18.1 | 20.6 | 13.1 | 13.3 | 22.7 | 18.1 |
Aberdart | 14.2 | 17.2 | 21.2 | 12.3 | 12.3 | 26. | 17.3 |
Aberavon | 12.3 | 20.7 | 23.5 | 16.9 | 24.3 | 26.3 | 20.7 |
Faithful | 23.8 | 20.3 | 23.3 | 12.3 | 15.8 | 26.5 | 20.3 |
TPM | 18.6 | 17.1 | 22.4 | 13.3 | 14.4 | 18.6 | 17.4 |
Amazon | 20.8 | 20.9 | 20.9 | 16.1 | 17.8 | 28.9 | 20.9 |
Zero Yatsyn | 17.6 | 18.3 | 20.6 | 13.5 | 16.4 | 23.5 | 18.3 |
Impact | 19.4 | 16.3 | 19 | 9.6 | 13 | 20.5 | 16.3 |
Barmultra | 16.2 | 17.9 | 24.7 | 12.1 | 14.9 | 18.5 | 17.4 |
Polly | 18.3 | 18.2 | 23.7 | 15.6 | 14.9 | 18.3 | 18.2 |
Cultivar | 3-Apr | 26-Apr | 13-May | 13-Jun | 31-Jul | 3-Nov | Average |
---|---|---|---|---|---|---|---|
Tivoli | 883 | 2065 | 2078 | 2621 | 1479 | 1598 | 10724 |
Aberdart | 834 | 2144 | 2420 | 2139 | 1501 | 1632 | 10670 |
Aberavon | 967 | 2143 | 2888 | 2672 | 1052 | 1353 | 11075 |
Faithful | 1045 | 1658 | 2182 | 2805 | 986 | 1345 | 10021 |
TPM | 1256 | 1897 | 2522 | 2812 | 1220 | 1458 | 11165 |
Amazon | 1103 | 1712 | 2176 | 2805 | 1156 | 1305 | 10257 |
Zero Yatsyn | 1233 | 2240 | 2503 | 2411 | 987 | 1643 | 11017 |
Impact | 1094 | 2030 | 1890 | 1983 | 1262 | 1543 | 9802 |
Barmultra | 1275 | 2134 | 2956 | 3042 | 905 | 1314 | 11626 |
Polly | 1355 | 2235 | 2804 | 2492 | 863 | 1191 | 10940 |
Cultivar | 3-Apr | 26-Apr | 13-May | 13-Jun | 31-Jul | 3-Nov | Average |
---|---|---|---|---|---|---|---|
Tivoli | 184 | 374 | 428 | 343 | 197 | 363 | 189 |
Aberdart | 118 | 369 | 513 | 263 | 185 | 431 | 1879 |
Aberavon | 119 | 444 | 679 | 452 | 256 | 356 | 2306 |
Faithful | 249 | 337 | 508 | 345 | 156 | 356 | 1951 |
TPM | 234 | 324 | 565 | 374 | 176 | 271 | 1944 |
Amazon | 229 | 358 | 45 | 462 | 206 | 377 | 2087 |
Zero Yatsyn | 217 | 410 | 516 | 325 | 162 | 286 | 2016 |
Impact | 212 | 331 | 359 | 190 | 164 | 216 | 1572 |
Barmultra | 207 | 382 | 730 | 368 | 135 | 243 | 2065 |
Polly | 248 | 407 | 665 | 388 | 132 | 218 | 2058 |
Conclusion
This two-year project has been extremely helpful in characterizing non-structural carbohydrates in cool season grasses. We have learned al ot about the normal flexuations seen across environments and more specifically, variations due to genetic differences. The main conclusions are:
- Across cool-seasons forage grasses in the study, level of non-structural carbohydrates and dry matter yield appear to be slightly negatively correlated.
- Percentages of non-structural carbohydrates are highly variable throughout the growing season and between species and varieties of cool-season forage grasses.
- Growth rate may affect the level of TNC in cool-season forage grasses.
- Consistently, the four varieties of orchard grasses contained low levels of TNC and high DM yields.
- Grasses bred in Europe to emphasize non-structural carbohydrates are higher in sugars than the average of the population found in the US, however, not 25% higher like they are advertised as being.
