Preprint
Article

In vitro gas Production of Common Southeast Asian Grasses in Response to Variable Regrowth Periods in Vietnam

Altmetrics

Downloads

102

Views

60

Comments

0

A peer-reviewed article of this preprint also exists.

Submitted:

19 February 2024

Posted:

23 February 2024

You are already at the latest version

Alerts
Abstract
The relationship between DM yield/cutting and fermentable organic matter (FOM) content of tropical grasses was appropriately investigated to re-access optimal grass maturity to feed dairy cattle. Nine different grass species belonging to the genera: Brachiaria spp. (Mulato II, Ruzi), Panicum spp. (Guinea, Hamil, Mombasa, TD58), and Pennisetum spp. (King, Napier, VA06) were chemically analyzed and subjected to an in vitro gas production (IVGP) test. For 72 h, gas production (GP) was continuously recorded with fully automated equipment. A triphasic, nonlinear, regression procedure was applied to analyse GP profiles. Across all the grasses, it was found that the neutral detergent fiber (NDF) contents increased with increasing maturity of the grass while the CP contents decreased with increasing NDF contents. In all nine grasses, digestible organic matter (dOM) was significantly affected by the week of cutting but IVGP was similar between weeks of cutting in Ruzi, Hamil, Mombasa, and Napier grass. Except for Guinea grass, the lowest dOM values were found when the grasses were cut after ≥ 5 weeks of regrowth. Harvesting grass one or two weeks earlier than normal cutting time is a practically relevant intervention in in-creasing forage quality and productivity of dOM and fermentation potential.
Keywords: 
Subject: Biology and Life Sciences  -   Animal Science, Veterinary Science and Zoology

1. Introduction

Dairy cows in Southeast (SE) Asian countries such as Thailand and Vietnam typically produce 4000-4500 kg of milk per lactation cycle with an average fat content below 4% [1,2,3]. In view of the low level of milk production compared to those of cows in temperate climates, the observed low milk fat content can be considered unexpected. Acetic acid (Hac) and ß-hydroxybutyric acid (Hbu) are important precursors of fatty acid synthesis in the mammary gland of dairy cows [4]. It can, therefore, be suggested that the supply of Hac and Hbu, to the mammary glands of Thai and Vietnamese dairy cows is insufficient. It is well known that the aforementioned precursors of milk fat originate predominantly from organic matter that is fermented in the rumen [5]. It thus would appear that the rations typically fed in Thailand and Vietnam contain insufficient fermentable organic matter (FOM) to yield Hac and Hbu to ensure milk fat synthesis.
Fresh grasses are mainly used to compose dairy rations in SE Asian countries. According to custom, Thai and Vietnamese farmers practice cutting intervals of 6 to 9 weeks, depending on the grass species in question, i.e. typically grasses that belong to the genera Pennisetum, Panicum, and Brachiaria. Cutting intervals of 6 to 9 weeks result in high dry matter (DM) yields per cutting but the harvested grasses are physiologically mature and, therefore, very fibrous and low in crude protein (CP). Furthermore, Huyen et al. [6] recently reported that, across the three aforementioned genera of grasses, in vitro gas production was, on average, only ~ 9% greater compared to that of rice straw, thereby, indicating that the FOM content of tropical grasses is relatively low when they are harvested under practical farming conditions. In temperate grasses, such as Lollium perenne, it is well established that a prolonged cutting interval is negatively associated with the FOM content of the grass [7]. In tropical grasses, however, the relationship between DM yield/cutting and FOM content is poorly understood due to a dearth of studies addressing this association. As such, whether the relationship between cutting interval/maturity of fresh grass and rumen digestibility, as found in temperate grasses, holds true for tropical grasses is still unknown. This question prompted us to conduct the current in vitro study using cumulative gas production and OM degradability as primary indicators of the FOM content of the tropical grasses. We hypothesized that a shorter regrowth period of tropical grasses commonly used for dairy rations in SE Asia results in an increased fermentability.

2. Materials and Methods

2.1. Grass Collection

Nine different grass species belonging to the genera: Brachiaria spp. (Mulato II, Ruzi), Panicum spp. (Guinea, Hamil, Mombasa, TD58), and Pennisetum spp. (King, Napier, VA06) were harvested at up to nine different weekly regrowth ages from June to August 2018 at the Animal Husbandry Research and Development Centre for Mountainous Zone (ARDC), Song Cong town, Thai Nguyen province, Vietnam. The centre is located at 21°29′14″N 105°48′47″E and experiences an annual rainfall of 2168 mm with an average temperature of 23 °C. Plot area used for each grass variety was 400 m2. An initial fertiliser dressing of N:P:K with 160:80:80 kg/ha/yr was applied at sowing, with further annual applications at the same rate. Annually, the amount of 20 tons/ha/yr of cattle manure was applied manually.
Chemical analyses and gas production were carried out on grasses at four cutting time points, excluding Napier and VA06 grasses of Pennisetum spp. and Guinea and TD58 grasses of Panicum spp. The selection of these time points was based on practical harvest times in Vietnam, including two time points before practical cutting, one during practical cutting, and one for late cutting. As it is unknown whether normal practical cutting provides precise nutritive information for determining the suitable cutting age, two grasses from each of the two most commonly used genera, based on the advice of recognized experts in ruminant nutrition, were selected for additional evaluation. These selections ranged from week 1 to 9 for Pennisetum spp. and from week 1 to week 6 for Panicum spp.
At each grass plot, a 10 × 10 m area was marked out for sampling, and by walking in a 'W' pattern, 20 evenly spaced cores were manually collected using a sickle. Grass was harvested, leaving around 10 cm stubble above ground level. After harvesting, each selected species and harvesting time grass sample was manually cut to 3 cm and mixed thoroughly before collecting a 5 kg representative sample which was divided equally into two bags (one for analysis and one for reserve) and stored at -20 °C in Vietnam. Subsequently, all frozen grass samples were transported to Wageningen University & Research (Wageningen, the Netherlands), maintaining -20 °C conditions, for analyses.

2.2. Chemical Analyses

Upon arrival at Wageningen, frozen fresh grass samples were thawed and dried during 16 h at 70 °C before being ground (1-mm screen) using a cross beater mill (Peppink 100 AN, Deventer, The Netherlands) and analysed in duplicate for DM, crude ash. Crude protein was calculated from nitrogen (N × 6.25) obtained via the Kjeldahl method [8]. The neutral detergent fibre (NDF; with heat stable α-amylase) content was analysed according to Van Soest et al. [9] while acid detergent fibre (ADF), and acid detergent lignin (ADL) contents were determined according to Van Soest [10].

2.3. In Vitro Gas and CH4 Production

Cumulative in vitro gas (IVGP) and methane (CH4) production over 72 h were measured in a fully automated gas production system [11]. Each ground and dried grass (~ 0.5 g) was accurately weighed in quadruplicate 250 ml fermentation bottles (Schott, Mainz, Germany). All samples were randomly distributed across three runs. Blank bottles (rumen fluid without grass) were used in triplicate for each run. The two non-lactating Holstein-Friesian rumen fluid donor cows were fed grass silage (NEL, 4.37 MJ/ kg DM; CP, 99 g/ kg DM; NDF, 675 g/kg DM) ad libitum and had free access to water. Approximately 350 ml rumen fluid was collected from each cow using a tube inserted via the esophagus before the morning feeding at the research farm of Wageningen University, the Netherlands. Subsequently, the rumen fluid was pooled and filtered through cheesecloth and subsequently mixed (1:2 v/v) with an anaerobic buffer/mineral solution [11] under continuous flushing with CO2. Prior to inoculation, the fermentation bottles were placed in a shaking water bath kept at 39 °C and pre-flushed with CO2. Sixty ml of buffered rumen fluid was added to the bottle before being connected to fully automated gas recording equipment for 72 h after which time the bottles were disconnected and placed on ice and 0.6 ml of the solution was pipetted into a 1.5 ml Eppendorf tube, and 0.6 ml of an internal standard solution (isocapronic acid) was added before vigorous mixing. After 5 min of centrifugation at 14,000 × g, a 0.75 ml sample of the supernatant was taken and mixed with an equal volume (1:1, v/v) of a stock solution composed of 25 ml of 85% (v/v) ortho-phosphoric acid dissolved in 200 ml Millipore water (Merck KGaA, Darmstadt, Germany) and 300 ml of a 4 g/l 4-methylvaleric acid (internal standard) for VFA analysis. The mixture was then stored at -20 °C pending analysis. Volatile fatty acids (VFA) were analysed using a gas chromatograph (Trace GC Ultra, Thermo Scientific, Milan, Italy) equipped with a flame ionization detector and an Agilent HP-FFAP column (Agilent Tech., Santa Clara, CA; 30 m length, 0.53 mm i.d., 1 µm film) using hydrogen as carrier gas (25 kPa, constant pressure). Isocaproic acid was used as an internal standard.
After 72 h of incubation, fermentation fluids from sample bottles were filtered in respective crucibles (P2 standard with pore size 40 - 100 µm, Foss Manufacturing Co.) with a filter plate of sintered glass and 0.5 cm washed and incinerated sea sand (VWR, art. no. 1.07711.5000). Before using the crucibles, they were washed with hot water and dried at 103 °C for 1 h, then ashed at 530 °C for 1 h and finally placed in a desiccator for 1 h to cool down before weighing with an analytical balance of 0.1 mg precision. The crucibles containing fermentation fluids were then vacuum drained and washed with hot distilled water by a cold extraction unit (FT 121 Fibertec™, Denmark) to remove microbial matter from the undegraded substrates, and then dried at 103 °C for 4 h and ashed at 530 °C for 2 h. The difference between these two values was termed residual OM. The degraded OM (OMd) was calculated as the difference between incubated and residual OM after 72 h of fermentation.
Precisely 10 μl of the headspace gas was collected from each fermentation bottle and directly injected into a gas chromatograph to determine headspace CH4 production at 0, 3, 6, 9, 12, 24, 30, 36, 48, 60, and 72 h, as described by Pellikaan et al. [12,13]. Briefly, measured CH4 production in individual bottles was expressed relative to the maximum production in each bottle and were fitted iteratively with a monophasic model. Methane production at each individual valve opening was then calculated, and cumulative CH4 was determined as the sum of the increase in headspace CH4 production between two successive valve openings, and the amount of CH4 vented from the bottle.

2.4. Curve Fitting and Calculations

Gas and CH4 production from all samples were corrected for the corresponding production by blank bottles at each time point [11,12]. The non-linear least squares regression procedure was used [14] and the data were fitted according to the following equation, as outlined by Groot et al. [15]:
Preprints 99296 i001
where, GP (ml/g OM) is the cumulative produced gas or CH4; n = total number of phases, i = number of phases, Ai (ml/g OM) is estimated asymptotic gas or CH4 production in phase i; Bi is a constant determining the switching characteristic of the curve in phase i; Ci (h) is the time at which half of the asymptotic gas or CH4 production was reached in phase i and t (h) is the time of incubation.
A tri-phasic model (n = 3) was fitted to the cumulative gas production following the procedure as described by Groot et al. [15], where phases 1 and 2 are assumed to relate to the fermentation of the soluble and non-soluble fraction, respectively, and phase 3 is assumed to be related to microbial turnover. The time windows related to the asymptotes of GP for phase 1, 2, and 3 (A1, A2, and A3, respectively) were pre-set from 0 to 3, 3 to 20, and 20 to 72 h after the start of incubation of the substrate, respectively to enable the estimation of the various parameters (Bi and Ci, respectively). The aforementioned time points were empirically determined by Van Gelder et al. [16] based on the work of Cone et al. [17]. Data on CH4 production were also fitted according to the above-mentioned model where n = 1.

2.5. Calculations and Statistical Analyses

Total VFA in fermentation fluid at 72 h was calculated as the sum of Hac, propionic acid (Hpr), Hbu, valeric acid (Hva), isobutyric acid (iso-Hbu) and isovaleric acid (iso-Hva). The branched-chain volatile fatty acids (BCVFA) in fermentation fluid were calculated as the sum of iso-Hbu and iso-Hva. The non-glucogenic to glucogenic ratio (NGR) was calculated as Ørskov [18]:
[acetate + 2 × (Hbu + isoHbu) + Hva + iso-Hva] / [Hpr + Hva + iso-Hva].
The most commonly used grass in Vietnam for each genus (Mombasa, Mulato II, King grass) was selected to calculate the estimated yield of FOM indicators as an example. Normal practical cutting was considered as 100% of in vitro digestible OM (dOM) and fermentation potential (GP, A1+A2) yield, whereafter the percentage of other cutting yields was calculated. For Mombasa and Mulato II grass, biomass yield equations (kg DM/ha/yr) were derived from data reported by Hare et al. [19,20], respectively, after conversion of biomass yields per year:
YMo = 0.1120x2 + 52.080x (0 ≤ x ≤ 90; R2 = 0.95)
YMu = 0.7423x2 + 34.672x (0 ≤ x ≤ 90; R2 = 0.99)
For King grass, biomass yield (kg dry matter/ha/yr) was determined using the equation provided by Sales et al. [21]:
YKi = -1.2426x2 + 282.64x (0 ≤ x ≤ 120)
where, YMo, YMu, YKi are the estimated yield of Mombasa, Mulato II and King grass, respectively; x is cutting time in days after regrowth.
Effects of regrowth age within each grass were subjected to analysis of variance (ANOVA) using the PROC MIXED procedure [14] using the following model:
Yij = μ + Hi + Rj + eij
where, Yij = response variable (i.e. GP-72, CH4-72 production, fermentation kinetics parameters), μ is the overall mean, Hi is the effect of harvest time (i = 1 to 9 regrowth week), Rj is the random effect of run j (j = 1 to 3) and eij is the residual error term. Differences among harvest times within each grass were determined using the least square means procedure and Tukey’s multiple comparisons. Throughout, the level of statistical significance was pre-set at P < 0.05 while a trend was declared at 0.05 ≤ P < 0.10.

3. Results and Discussion

3.1. Chemical Composition of Tropical Grasses at Different Regrowth Ages

The OM content of the grasses and advanced cutting age (Table 1) showed a moderate correlation (r = 0.61, P < 0.001, n = 49). Those belonging to the Pennisetum genus (especially King and VA06) generally showed a stronger correlation of OM content with cutting age (r = 0.83, P < 0.001, n = 21). This trend is consistent with the finding of Mutimura et al. [22] who reported that the OM content of Napier grass increased until 90 d after planting and then declined. The increase in OM might be attributed to the fact that grass is still in the development stage, during which OM accumulates relative to the inorganic matter.
The values related to cell wall constituents (NDF, ADF and ADL) increased with the advancement of grass maturity (r = 0.55, 0.60, 0.67 and P < 0.001, respectively). The current data were found to be in line with other previous reports [23,24].
Tropical grasses develop thick-walled cells with increased cell wall fractions, including cellulose, hemicellulose, and lignin, as a structural adaptation to minimize photorespiration, enhance overall resilience to tropical environmental conditions, that helps contribute to the plant's robustness owing to both the thickness and composition of cell walls [25]. Consequently, the NDF content of tropical grasses is higher than temperate grasses (60-75 vs 35-67% DM) [26,27,28].
In the present study, an increase in cell wall constituents of tropical grasses was associated with a decrease in CP content with cutting ages as cutting age advances, and this decrease was even more pronounced at later stages (r = -0.74, P < 0.001), which is consistent with observations of others in temperate grasses [29,30,31]. A notable example is the CP content of VA06, which significantly decreased from approximately 30 to 7.4% in the DM between the first and eighth week. Despite the decline in CP content with advancing grass maturity, the final concentration still exceeded the minimum CP level (7%) required for rumen function [32] although the CP content in rations recommended by the NRC [33] for lactating cows ranges from 14 to 18% DM.
The lipid concentration (EE) of the selected grasses ranged from 1.9 to 3.2% DM, which is comparable to the values reported by Melesse et al. [34] for tropical grasses (1.1-3.1% DM). The EE of the Brachiaria genus in the current study correlated well with increasing maturity age (r = -0.77, P = 0.02, n = 8). Other grasses showed a trend of an increase in EE content from early to the middle stage and then a decline from middle to the late stage of maturity.
In general, the reduction in cell contents, in particular CP content, was countered by the accumulation of structural carbohydrates as the grass matured.

3.2. In vitro gas and CH4 Production Parameters of Grasses Belonging to the Brachiaria Genus

As shown in Table 2, most of the parameters (except for CH4 expressed as a percentage of total gas production and A:P) of Mulato II grass were significantly influenced by harvesting time. The highest values of in vitro dOM, GP after 72 h incubation (GP-72), TVFA and NGR were found at week 4, which is earlier than the commonly used cutting time (week 6) under practical farming conditions in Vietnam. Nevertheless, the growth of Mulato II after week 4 also produced the highest quantity of cumulative CH4 production measured after 72 h of incubation (CH4-72), whereas the CH4 percentage (CH4:GP-72) was not different between cutting weeks. This can be explained by the low content of fibre at week 4 compared to other weeks. These findings are in line with Neto et al. [35] and Ruggieri et al. [36] who reported that forages rich in structural carbohydrates tend to yield greater amounts of CH4 and a decreased digestibility compared to forages higher in non-structural carbohydrates. It is well known that high levels of non-fibre carbohydrates in the diet stimulate rumen Hpr production, which subsequently reduces CH4 synthesis by the methanogens. In Ruzi grass, GP-72 was not affected by grass maturity, but most of other parameters indicated that week 4 is the most suitable harvesting age. Cutting grass at late stage (i.e. week 8) should not be beneficial in term of FOM content.
Both Mulato II and Ruzi, belonging to the Brachiaria genus, showed that NDF was negatively correlated with dOM (r = -0.96, -0.998 with P = 0.04, 0.002, respectively).
Overall, due to the high fermentation potential values (i.e. dOM, GP-72 and A1+A2) and high values of volatile fatty acids used for milk fat synthesis (i.e., NGR and A:P), the recommended harvest age for grasses belonging to the Brachiaria genus appears to be at week 4 after the previous cut.
A1+A2 = in vitro fermentation potential of the soluble in insoluble carbohydrates; A:P = acetic to propionic acid ratio; BCVFA = branched-chain volatile fatty acids; NGR = non-glucogenic to glucogenic ratio; OM = organic matter; TVFA = total volatile fatty acid.

3.3. In Vitro Gas and CH4 Production Parameters of Grasses Belonging to the Panicum Genus

The variation in in vitro gas and CH4 production parameters of grasses belonging to the Panicum genus were found to be large (Table 3). In Guinea grass, cutting at the first three weeks of regrowth had more advantages (except for CH4 production) than late cuttings. Normal practical cutting (week 5) resulted in higher values of in vitro dOM, GP-72, A1+A2, TVFA and BCVFA production compared to cutting one week earlier. Week 4 had the lowest values over almost all parameters. These discrepancies are not easy to explain but it can be speculated that the variation in those parameters does not properly reflect the FOM content. Cumulative CH4-72, expressed in both terms (g/kg OM and proportion) was not systematically affected by harvest time with week 4 having the least amount of CH4 being different to the other weeks. This is due to the lowest value of fibre content at week 4 compared to other weeks. The relationship between structural carbohydrates and CH4 production was mentioned in the previous section.
For Hamil grass, dOM gradually declined (P < 0.001) with grass maturity whilst GP did not differ among weeks (P = 0.184) although a numerical decrease was observed. A1+A2 values were different between week 2 and 6 with no difference in CH4-72 or CH4:GP-72 values. Cutting at the normal practical cutting time (week 5) did not differ from the other weeks, except for dOM and BCVFA. Under the assumption that NGR and A:P are the indicators related to milk fat synthesis, cutting at any given week between 2 and 6 produced similar results. Week 2 had the highest dOM, A1+A2, TVFA and BCVFA values, making it the most suitable harvest time for Hamil grass without concerns about increased CH4 production.
For Mombasa grass, except for dOM and BCFA, expressed as a percentage of TVFA, which had high values at either week 2 or week 4, all other parameters did not vary with cutting ages.
For TD58 grass, significant effects of cutting time were observed for dOM, GP-72, CH4-72, BCVFA, NGR and A:P with trend for CH4:GP-72 (P = 0.074) and TVFA (P = 0.050). The lowest values were observed in either week 2 or 3 for dOM, BCVFA, NGR and A:P corresponding to the high NDF content at these two weeks. GP was found to be significantly different, but A1+A2 was similar throughout the harvesting ages, suggesting that the asymptote GP associated with microbial turnover (A3) contributed to this difference. There was a similar trend for GP-72 and CH4 proportion which did not significantly differ from week 1 to 5, with week 6 having the lowest values. Inversely, NGR and A:P ratio had the highest value at week 1 but were similar from week 2 to 6. It should be noted that cutting every week would produce the biomass with the highest FOM.
In the present study, the NDF content of these four grasses was found to be negatively correlated with dOM and BCVFA concentrations (r = - 0.66, -0.94; P = 0.003, <0.001, respectively). In general, it appears that harvesting grasses belonging to the Panicum genus after two weeks of regrowth provides the highest concentration of FOM biomass and, thereby, can be expected to yield the greatest milk fat content by dairy cows in Vietnam.

3.4. In Vitro Gas and CH4 Production Parameters of Grasses Belonging to the Pennisetum Genus

As seen in Table 4, grasses belonging to the Pennisetum genus generally displayed a wide variation in their in vitro GP and CH4 emission potentials.
King grass exhibited a gradual decrease (P < 0.001) in dOM with advancing grass maturity similar to the other grasses. This decrease is due to plant growth and development, where over time grasses contain more fibrous materials such as cellulose and lignin, which are more challenging to digest and require more fermentation for breakdown. It is worth noting that frequent cuttings at 5 weeks of regrowth are the most suitable in view of King grass chemical composition. Both normal practical and late cutting resulted in a reduction in NGR and A:P compared to very early cutting (week 3) which had a relative low GP and A1+A2 values. Generally, forages rich in structural carbohydrates tend to result in greater CH4 emissions, however, the result of King grass exhibited the opposite trend.
Normal practical cutting at week 7 of Napier grass yielded the highest values for dOM and A1+A2, but relative low values for BCVFA, NGR and A:P ratios. Although no significant differences were found in GP-72, CH4 percentage and TVFA across cutting weeks, increased grass maturity led to a decline in BCVFA, NGR and A:P ratios. Cutting at either week 4 or week 5 appears optimal in term of fermentability and generation of precursors for milk fat synthesis.
Cutting VA06 grass at a very early stage (i.e., first two weeks) resulted in the lowest values of GP, A1+A2 and TVFA, however produced the highest values of BCVFA, NGR and A:P ratios. The highest values for degradable organic matter and fermentability were observed for normal practical cutting of this grass (week 5), but precursors for milk fat synthesis were less favorable. Overall, considering all parameters, week 4 appears to be the most suitable cutting time for VA06.
Meanwhile, CP content of King, Napier and VA06 grass was found to be positively correlated with BCFVA (r = 0.98, 0.76, 0.90 and P = 0.02, 0.03, <0.001, respectively). This finding aligns with the studies by Bowen et al. [37] and Musco et al. [38], which reported that grasses had lower protein level (compared to other feedstuffs) led to lower ammonia-N and branched-chain fatty acid concentrations because these acids are derived from the degradation of some amino acids (i.e., valine, proline, isoleucine, leucine). Methane proportion was not significantly affected by the maturity of all three grasses.
Overall, the data of grasses belonging to the Pennisetum genus indicate that they are best harvested at either week 4 or 5 in terms of digestibility and fermentability.

3.5. Relative Yield (%) of FOM Indices of Three Grasses

To affect milk fat content, the FOM content of the grasses is important but cutting earlier or later than the common practice will affect biomass yield and, as a result, total amount of FOM produced. Data on biomass yield in relation to cutting time of Mombasa ([19]), Mulato II ([20]) and King grass ([21]) were used to calculate the relative yields of DM, dOM, GP and A1+A2 and results were compared with those calculated for the current practical cutting time. As can be seen in Table 5, yield of DM biomass of Mombasa increased with cutting age, while total amount of dOM was lower for both early and late cutting compared to the normal cutting time at week 5. However, cutting after 4 weeks of regrowth produced on average 12% additional relative yield of fermentation potential (GP, A1+A2) than week 5. The relative biomass yields of Mulato II gradually increased with increasing maturity across all parameters. Mulato II cut at 8-week intervals compared to the normal cutting interval of 6 weeks showed an average increase of ~12.3% in relative yields of in vitro dOM and fermentation potential (GP and A1+A2). The decrease in the DM biomass of King grass when cutting age advances, might be attributed to the fact that this grass is still in the developmental stage, during which OM accumulates relative to the inorganic matter (Table 1). The effect of King grass maturity on all parameters was more pronounced in week 5 than week 7 with, on average, around 10% increase. The total biomass yield of dOM of King grass was shown a gradual decline with delayed harvesting times. However, cutting grass at week 3 might not be a good harvesting strategy due to lower values of relative yields of GP and A1+A2 compared to cutting at week 5.
Overall, the implementation of a well-timed grass-cutting strategy depends on selecting the appropriate parameter to enhance milk fat content while also balancing the demand for a large quantity of low-quality feed against the need for smaller amounts of higher-quality feed.

4. Conclusions

Harvesting tropical grasses one or two weeks earlier than normally practiced is a practically relevant intervention for increasing forage quality and productivity of dOM and fermentation potential, thereby, proving our hypothesis. The methane proportion was not significantly affected by the grass maturity (except for Ruzi and Guinea). Even within the same genus, grasses still exhibit different patterns of in vitro gas and CH4 productions. These results provide important insights into the potential use of fermentable organic matter indicators of tropical grasses in combination with improvements in nutritive value to meet dairy nutrition requirements.

Author Contributions

This chapter was a collaborative effort, and each author contributed to the design of the study. Dr. Trach Nguyen contributed to the design of grass fields and the collection of fresh grasses in Vietnam. Dr. Pellikaan assisted with in vitro methodology, data analysis, and interpretation. Huyen Nguyen formulated the study, carried out the research, analyzed the data, and wrote the manuscript. Dr. Schonewille and Dr. Hendriks reviewed and provided critical feedback on the manuscript and approved the version to be published.

Funding

This work was financially supported by Eurofins (Wageningen), De Heus (Ede) as well as Wageningen University & Research (Wageningen), the Netherlands. The authors also would like to acknowledge the scholarship provided by Vietnam Ministry of Education and Training (the funding number is 5859/QĐ-BGDĐT).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors also thank Mrs. Saskia van Laar-van Schuppen, Mrs. Xuan Huong van der Schans-Le and Mr. Michel Breuer for their technical assistance.

Conflicts of Interest

The authors are not aware of any conflicts of interest.

References

  1. Nguyen, T.; Phan, T.; Tran, P.; Tran, T. The factors affecting milk production of dairy cows in Ho Chi Minh City, Vietnam. IOP Conference Series: Earth and Environmental Science 2023, 1155, 012036. [CrossRef]
  2. Vu, N.H.; Lambertz, C.; Gauly, M. Factors influencing milk yield, quality and revenue of dairy farms in Southern Vietnam. Asian-Australas. J. Anim. Sci. 2016, 10, 290-299. [CrossRef]
  3. Wongpom, B.; Koonawootrittriron, S.; Elzo, M.A.; Suwanasopee, T. Milk yield, fat yield and fat percentage associations in a Thai multibreed dairy population. Agric. Nat. Resour. 2017, 51, 218–222. [Google Scholar] [CrossRef]
  4. Tyznik, W.J. The effect of the amount and physical state of the roughage upon the rumen fatty acids and milk fat of dairy cows; University of Wisconsin-Madison, USA: 1951; p. 110.
  5. Shabi, Z.; Arieli, A.; Bruckental, I.; Aharoni, Y.; Zamwel, S.; Bor, A.; Tagari, H. Effect of the synchronization of the degradation of dietary crude protein and organic matter and feeding frequency on ruminal fermentation and flow of digesta in the abomasum of dairy cows. J. Dairy Sci. 1998, 81, 1991–2000. [Google Scholar] [CrossRef]
  6. Huyen, T.D.N.; Schonewille, J.T.; Pellikaan, W.F.; Nguyen, X.T.; Hendriks, W.H. In vitro gas and methane production of some common feedstuffs used for dairy rations in Vietnam and Thailand. Asian-Australas. J. Anim. Sci. 2023, 0, 0-0. [CrossRef]
  7. Macome, F.M.; Pellikaan, W.F.; Hendriks, W.H.; Warner, D.; Schonewille, J.T.; Cone, J.W. In vitro gas and methane production in rumen fluid from dairy cows fed grass silages differing in plant maturity, compared to in vivo data. J. Anim. Physiol. Anim. Nutr. 2018, 102, 843–852. [Google Scholar] [CrossRef] [PubMed]
  8. NEN-ISO 5983-2. Animal feeding stuffs - Determination of nitrogen content and calculation of crude protein content - Part 2: Block digestion and steam distillation method. 2009.
  9. Van Soest, P.J.; Robertson, J.B.; Lewis, B.A. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 1991, 74, 3583–3597. [Google Scholar] [CrossRef] [PubMed]
  10. Van Soest, P.J. Collaborative study of acid detergent fibre and lignin. J. Assoc. Off. Anal. Chem. 1970, 56, 781-784.
  11. Cone, J.W.; van Gelder, A.H.; Visscher, G.J.W.; Oudshoorn, L. Influence of rumen fluid and substrate concentration on fermentation kinetics measured with a fully automated time related gas production apparatus. Anim. Feed Sci. Technol. 1996, 61, 113–128. [Google Scholar] [CrossRef]
  12. Pellikaan, W.F.; Hendriks, W.H.; Uwimana, G.; Bongers, L.J.G.M.; Becker, P.M.; Cone, J. A novel method to determine simultaneously methane production during in vitro gas production using fully automated equipment. Anim. Feed Sci. Technol. 2011, 168, 196–205. [Google Scholar] [CrossRef]
  13. Pellikaan, W.F.; Stringano, E.; Leenaars, J.; Bongers, D.J.G.M.; Schuppen, S.v.L.-v.; Plant, J.; Mueller-Harvey, I. Evaluating effects of tannins on extent and rate of in vitro gas and CH4 production using an automated pressure evaluation system (APES). Anim. Feed Sci. Technol. 2011, 166-167, 377-390. [CrossRef]
  14. SAS Institute Inc SAS Release 9.4, Cary, N.C 2012.
  15. Groot, J.C.J.; Cone, J.W.; Williams, B.A.; Debersaques, F.M.A.; Lantinga, E.A. Multiphasic analysis of gas production kinetics for in vitro fermentation of ruminant feeds. Anim. Feed Sci. Technol. 1996, 64, 77–89. [Google Scholar] [CrossRef]
  16. Van Gelder, A.H.; Hetta, M.; Rodrigues, M.A.M.; De Boever, J.L.; Den Hartigh, H.; Rymer, C.; van Oostrum, M.; van Kaathoven, R.; Cone, J.W. Ranking of in vitro fermentability of 20 feedstuffs with an automated gas production technique: Results of a ring test. Anim. Feed Sci. Technol. 2005, 123-124, 243-253. [CrossRef]
  17. Cone, J.W.; van Gelder, A.H.; Driehuis, F. Description of gas production profiles with a three-phasic model. Anim. Feed Sci. Technol. 1997, 66, 31–45. [Google Scholar] [CrossRef]
  18. Ørskov, E. Manipulation of rumen fermentation for maximum food utilization. World Rev. Nutr. Diet. 1975, 22, 152–182. [Google Scholar]
  19. Hare, M.; Phengphet, S.; Songsiri, T.; Sutin, N.; Stern, E. Effect of cutting interval on yield and quality of three Brachiaria hybrids in Thailand. Trop. Grassl. 2013, 1. [Google Scholar] [CrossRef]
  20. Hare, M.; Phengphet, S.; Songsiri, T.; Sutin, N.; Stern, E. Effect of cutting interval on yield and quality of two Panicum maximum cultivars in Thailand. Trop. Grassl. 2013, 1, 87–89. [Google Scholar] [CrossRef]
  21. Sales, F.A.; Caramori, P.H.; Ricce, W.d.S.; Costa, M.A.M.S.; Zaro, G.C. Biomass of elephant grass and leucaena for bioenergy production. Semina:Cienc. Agrar. 2015, 36, 3567-3578. [CrossRef]
  22. Mutimura, M.; Ebong, C.; Rao, I.; Nsahlai, I. Effect of cutting time on agronomic and nutritional characteristics of nine commercial cultivars of Brachiaria grass compared with Napier grass during establishment under semi-arid conditions in Rwanda. Afr. J. Agric. Res. 2017, 12, 2692–2703. [Google Scholar] [CrossRef]
  23. Ansah, T.; Osafo, E.L.K.; Hansen, H.H. Herbage yield and chemical composition of four varieties of Napier (Pennisetum purpureum) grass harvested at three different days after planting. Agric. Biol. J. N. Am. 2010, 1, 923–929. [Google Scholar] [CrossRef]
  24. Zailan, M.Z.; Yaakub, H.; Jusoh, S. Yield and nutritive value of four Napier (Pennisetum purpureum) cultivars at different harvesting ages. Agric. Biol. J. N. Am. 2016, 7, 213–219. [Google Scholar] [CrossRef]
  25. Barbehenn, R.V.; Chen, Z.; Karowe, D.N.; Spickard, A. C3 grasses have higher nutritional quality than C4 grasses under ambient and elevated atmospheric CO2. Glob. Change Biol. 2004, 10, 1565–1575. [Google Scholar] [CrossRef]
  26. Elizalde, J.C.; Merchen, N.R.; Faulkner, D.B. In situ dry matter and crude protein degradation of fresh forages during the spring growth. J. Dairy Sci. 1999, 82, 1978–1990. [Google Scholar] [CrossRef]
  27. Lopes, J.C. Nutrient composition and fiber digestibility measurements of tropical forages collected from intensively managed rotational grazing systems. University of Wisconsin-Madison, USA, 2011.
  28. Ortega-Gómez, R.; Castillo-Gallegos, E.; Rodríguez, J.; Escobar-Hernández, R.; Ocaña-Zavaleta, E.; Valles, B. Nutritive quality of ten grasses during the rainy season in a hot-humid climate and ultisol soil. Trop. Subtrop. Agroecosystems 2011, 13. [Google Scholar]
  29. Cone, J.W.; van Gelder, A.H. Influence of protein fermentation on gas production profiles. Anim. Feed Sci. Technol. 1999, 76, 251–264. [Google Scholar] [CrossRef]
  30. Man, N.; Wiktorsson, H. Forage yield, nutritive value, feed intake and digestibility of three grass species as affected by harvest frequency. Trop. Grassl. 2003, 37, 101–110. [Google Scholar]
  31. Macome, F.M.; Pellikaan, W.F.; Hendriks, W.H.; Dijkstra, J.; Hatew, B.; Schonewille, J.T.; Cone, J.W. In vitro gas and methane production of silages from whole-plant corn harvested at 4 different stages of maturity and a comparison with in vivo methane production. J. Dairy Sci. 2017, 100, 8895–8905. [Google Scholar] [CrossRef]
  32. Teklehaimanot, H.S.; Tritschler, J.P. Evaluation of spineless cactus (Opuntia ficus-indicus) as an alternative feed and water source for animals during dry season in Eritrea. In Sustainable agricultural development: Recent approaches in resources management and environmentally-balanced production enhancement, Behnassi, M., Shahid, S.A., D'Silva, J., Eds. Springer Netherlands: Dordrecht, 2011; pp. 245–252. [Google Scholar]
  33. NRC. Nutrient requirements of dairy cattle, 7th revised ed.; National Research Council: National Academies Press, Washington DC, USA, 2001; p. 408. [Google Scholar]
  34. Melesse, A.; Steingass, H.; Schollenberger, M.; Rodehutscord, M. Screening of common tropical grass and legume forages in Ethiopia for their nutrient composition and methane production profile in vitro. Trop. Grassl. 2017, 5, 163. [Google Scholar] [CrossRef]
  35. Neto, A.J.; Messana, J.D.; Granja-Salcedo, Y.T.; Castagnino, P.S.; Fiorentini, G.; Reis, R.A.; Berchielli, T.T. Effect of starch level in supplement with or without oil source on diet and apparent digestibility, rumen fermentation and microbial population of Nellore steers grazing tropical grass. Livest. Sci. 2017, 202, 171–179. [Google Scholar] [CrossRef]
  36. Ruggieri, A.C.; Cardoso, A.d.S.; Ongaratto, F.; Casagrande, D.R.; Barbero, R.P.; Brito, L.d.F.; Azenha, M.V.; Oliveira, A.A.; Koscheck, J.F.W.; Reis, R.A. Grazing intensity impacts on herbage mass, sward structure, greenhouse gas emissions, and animal performance: Analysis of Brachiaria pastureland. Agron. J. 2020, 10, 1750. [Google Scholar] [CrossRef]
  37. Bowen, M.K.; Poppi, D.P.; McLennan, S.R. Ruminal protein degradability of a range of tropical pastures. Aust. J. Exp. Agric. 2008, 48, 806–810. [Google Scholar] [CrossRef]
  38. Musco, N.; Koura, I.B.; Tudisco, R.; Awadjihè, G.; Adjolohoun, S.; Cutrignelli, M.I.; Mollica, M.P.; Houinato, M.; Infascelli, F.; Calabrò, S. Nutritional characteristics of forage grown in south of Benin. Asian-Australas. J. Anim. Sci. 2016, 29, 51-61. [CrossRef]
Table 1. Chemical composition (g/kg dry matter) of nine grasses at different stages of maturity commonly used in Vietnam.
Table 1. Chemical composition (g/kg dry matter) of nine grasses at different stages of maturity commonly used in Vietnam.
Grass1 Week OM CP EE NDF ADF ADL Grass1 Week OM CP EE NDF ADF ADL
Mulato II 2 851 226 28.8 519 255 20.3 TD58 3 875 132 28.6 688 372 20.1
4 846 147 25.7 498 234 19.3 4 873 138 24.5 644 310 18.1
6 858 113 19.2 607 316 24.5 5 855 148 27.5 676 362 21.2
8 860 118 18.1 656 362 30.9 6 863 165 24.3 667 350 16.9
Ruzi 2 889 179 32.2 536 268 21.5 King 3 859 181 24.8 598 336 17.2
4 878 163 25.7 505 234 21.4 5 869 136 33.4 602 336 19.4
6 915 116 24.5 660 354 26.7 7 896 87 27.9 646 377 23.6
8 888 162 25.6 622 328 29.8 9 920 103 23.7 659 409 47.3
Guinea 1 864 226 24.4 600 327 21.2 Napier 2 881 161 30.9 620 331 21.3
2 882 218 28.7 599 313 20.2 3 859 165 26.7 581 316 22.5
3 912 175 26.5 657 349 26.5 4 879 184 25.9 538 270 20.5
4 877 180 26.3 677 375 31.6 5 871 176 28.9 569 310 23.6
5 870 143 31.7 659 366 30.6 6 858 167 29.0 594 318 27.9
6 876 137 28.5 675 373 30.6 7 882 140 28.0 646 353 28.0
8 890 117 24.7 670 362 23.6
Hamil 2 844 254 29.7 572 293 14.9 9 911 132 18.7 696 397 33.1
4 876 97 23.3 732 413 27.5
5 845 96 - - 410 - VA06 1 824 298 28.8 491 276 21.4
6 840 85 - - 409 - 2 811 223 23.6 541 287 30.0
3 867 256 23.7 560 304 19.4
Mombasa 2 871 171 25.5 641 350 20.2 4 851 156 25.8 593 324 22.5
4 860 124 28.6 669 365 20.1 5 872 139 26.8 646 354 25.8
5 876 114 26.5 696 375 19.0 6 892 102 26.8 682 395 32.1
6 884 90 23.4 730 406 24.4 7 913 88 24.7 694 395 35.5
8 902 74 20.4 717 436 51.5
TD58 1 827 226 22.3 565 270 19.1 9 902 89 23.6 706 411 44.0
2 857 107 28.6 673 364 22.2
1 Mulato II = Brachiaria ruziziensis (B. ruziziensis × B. decumbens × B. brizantha); Ruzi = B. ruziziensis; Guinea = Panicum maximum Jacq.; Hamil = P. maximum cv. Hamill; Mombasa = P. maximum cv. Mombasa; TD58 = P. maximum cv.TD58; King = Pennisetum purpureum × P. glaucum; Napier = P. purpureum Schumach.; VA06 = P. purpureum × P. Americanum. ADF = acid detergent fibre, ADL = acid detergent lignin, CP = crude protein, EE = ether extract, NDF = neutral detergent fibre, OM = organic matter, - = not determined.
Table 2. In vitro 72 h organic matter digestibility (dOM), gas (GP-72) and methane production (CH4-72) parameters and volatile fatty acids related values of two grasses (Mulato II and Ruzi) belonging to the Brachiaria genus grown between 2 and 8 weeks.
Table 2. In vitro 72 h organic matter digestibility (dOM), gas (GP-72) and methane production (CH4-72) parameters and volatile fatty acids related values of two grasses (Mulato II and Ruzi) belonging to the Brachiaria genus grown between 2 and 8 weeks.
Grass Week dOM GP-72 A1+A2 CH4-72 CH4:GP-72 TVFA BCVFA NGR A:P
g/kg OM ml/g OM % of GP-72 mM % of TVFA mol/mol
Mulato II 2 783a 258ab 198ab 45.2ab 17.4 75.8ab 3.17a 3.20b 2.80
Mulato II 4 788a 276a 218a 49.5a 18.1 77.8a 2.86b 3.62a 3.04
Mulato II 6* 725b 247ab 185b 42.0b 17.0 71.8b 2.58c 3.25b 2.78
Mulato II 8 726b 233b 179b 40.2b 17.2 76.3ab 2.61c 3.25b 2.81
Pooled SE 5.9 10.3 10.7 1.81 1.00 1.78 0.09 0.17 0.18
P value <0.001 0.02 0.004 0.004 0.411 0.042 <0.001 0.01 0.05
Ruzi 2 772a 270 222a 46.7ab 17.5a 79.7a 3.07a 3.47ab 3.02x
Ruzi 4 794a 273 216a 48.0a 17.8a 80.5a 2.71b 3.61a 3.01x
Ruzi 6* 710b 246 193b 42.2bc 17.2a 75.3b 2.50c 3.30b 2.87xy
Ruzi 8 731b 251 189b 38.3c 15.4b 74.4b 2.84ab 3.34b 2.84y
Pooled SE 7.7 12.1 9.2 2.87 1.45 2.14 0.07 0.16 0.17
P value <0.001 0.086 0.006 0.001 0.006 0.002 <0.001 0.004 0.031
a,b,c Values within column and within grass with different superscripts differ (P < 0.05); x,yValues within column and within grass with different superscripts show a trend to be different (0.05 ≤ P < 0.10).*Normal cutting age in Vietnam.
Table 3. In vitro 72 h organic matter digestibility, gas (GP-72) and methane production (CH4-72) parameters and volatile fatty acids related values of four grasses (Guinea, Hamil, Mombasa and TD58) belonging to the Panicum genus grown between 1 and 6 weeks.
Table 3. In vitro 72 h organic matter digestibility, gas (GP-72) and methane production (CH4-72) parameters and volatile fatty acids related values of four grasses (Guinea, Hamil, Mombasa and TD58) belonging to the Panicum genus grown between 1 and 6 weeks.
Grass Week dOM GP-72 A1+A2 CH4-72 CH4:GP-72 TVFA BCVFA NGR A:P
g/kg OM ml/g OM % of GP-72 mM % of TVFA mol/mol
Guinea 1 741ab 248ab 181ab 45.9a 18.4a 74.7abc 3.66ab 3.65 3.22ab
Guinea 2 760a 255a 191a 48.4a 19.5a 78.6a 3.78a 3.72 3.31ab
Guinea 3 711bc 249a 180ab 47.2a 19.3a 77.6ab 3.46abc 3.77 3.34a
Guinea 4 627e 190c 116c 27.2b 14.4b 71.4c 3.00d 3.68 3.19ab
Guinea 5* 679cd 248a 182ab 46.3a 18.4a 72.9abc 3.34bc 3.57 3.11b
Guinea 6 646de 219b 167b 43.1a 19.6a 70.2c 3.22cd 3.65 3.16ab
Pooled SE 8.9 7.3 6.7 2.94 1.70 2.33 0.10 0.14 0.19
P value <0.001 <0.001 <0.001 <0.001 <0.001 0.005 <0.001 0.051 0.035
Hamil 2 768a 254 193a 49.4 19.5 77.8a 3.86a 3.56 3.17
Hamil 4 669b 255 183ab 46.8 18.3 74.7ab 2.93b 3.60 3.11
Hamil 5* 668b 240 184ab 45.6 19.1 73.8ab 2.92b 3.59 3.13
Hamil 6 621c 237 171b 44.8 19.0 70.4b 2.88b 3.54 3.07
Pooled SE 7.7 12.3 11.1 3.51 1.57 2.34 0.09 0.11 0.16
P value <0.001 0.184 0.026 0.117 0.254 0.005 <0.001 0.673 0.184
Mombasa 2 708a 252 190 47.6 18.3 74.4 3.25a 3.59 3.13
Mombasa 4 729a 280 210 51.9 18.9 75.7 3.20a 3.57 3.15
Mombasa 5* 708ab 237 189 45.9 20.2 79.2 2.97b 3.57 3.12
Mombasa 6 672b 265 187 45.1 17.2 75.0 2.80b 3.60 3.12
Pooled SE 8.4 15.5 10.0 4.30 1.71 2.13 0.04 0.11 0.16
P value 0.006 0.364 0.290 0.199 0.518 0.140 <0.001 0.910 0.943
TD58 1 797a 286ab 198 54.1ab 19.2 78.1ab 4.18a 3.92a 3.36a
TD58 2 769ab 269ab 202 51.9ab 19.1 76.0ab 3.34b 3.54b 3.07b
TD58 3 734c 273ab 201 49.3ab 18.0 77.2ab 2.92c 3.56b 3.07b
TD58 4 772ab 295a 210 54.4a 18.7 79.2a 3.19b 3.73ab 3.16b
TD58 5* 728c 271ab 200 49.2ab 18.4 73.6b 3.15bc 3.62b 3.14b
TD58 6 742bc 262b 196 45.1b 17.5 75.9ab 3.22b 3.66b 3.16b
Pooled SE 7.2 6.5 7.2 2.82 0.99 1.78 0.08 0.12 0.15
P value <0.001 0.040 0.650 0.003 0.074 0.050 <0.001 <0.001 <0.001
a,b,cValues within column and within grass with different superscripts differ (P < 0.05). *Normal cutting age in Vietnam. A1+A2 = in vitro fermentation potential of the soluble in insoluble carbohydrates; A:P = Hac to Hpr ratio; BCVFA = branched chain volatile fatty acids; NGR = non-glucogenic to glucogenic ratio; TVFA = total volatile fatty acid.
Table 4. In vitro 72 h organic matter digestibility (dOM), gas (GP-72) and methane production (CH4-72) parameters and volatile fatty acids related values of three grasses (King, Napier and VA06) belonging to the Pennisetum genus grown between 1 and 9 weeks.
Table 4. In vitro 72 h organic matter digestibility (dOM), gas (GP-72) and methane production (CH4-72) parameters and volatile fatty acids related values of three grasses (King, Napier and VA06) belonging to the Pennisetum genus grown between 1 and 9 weeks.
Grass Week dOM GP-72 A1+A2 CH4-72 CH4:GP-72 TVFA BCVFA NGR A:P
g/kg OM ml/g OM % of GP-72 mM % of TVFA mol/mol
King 3 731a 241b 179b 42.3b 17.7 73.7ab 3.27a 3.82a 3.37a
King 5 752a 272a 212a 50.9a 18.9 77.9a 3.09a 3.68b 3.13b
King 7* 701b 262ab 203ab 48.5a 18.6 76.3ab 2.63b 3.65b 3.03b
King 9 623c 240b 182b 42.8b 17.9 71.7b 2.61b 3.65b 3.10b
Pooled SE 7.6 11.2 10.0 2.73 1.48 1.08 0.09 0.13 0.17
P value <0.001 0.009 0.002 <0.001 0.325 0.010 <0.001 <0.001 <0.001
Napier 2 758ab 269 210ab 50.8ab 18.9 77.4 3.17a 3.73a 3.33a
Napier 3 756abc 265 195b 52.8a 20.0 76.7 3.25a 3.78a 3.34a
Napier 4 763ab 284 208ab 53.2a 18.7 78.2 3.17a 3.79a 3.24ab
Napier 5 758abc 284 218a 50.7ab 17.9 77.9 3.23a 3.74a 3.24ab
Napier 6 751abc 282 211ab 52.0a 18.5 76.8 3.21a 3.76a 3.27ab
Napier 7* 771a 276 216a 52.0a 19.0 79.8 2.84bc 3.66ab 3.16b
Napier 8 738abc 285 209ab 52.0a 18.3 77.3 2.88b 3.67ab 3.18b
Napier 9 722c 271 206ab 46.7b 17.2 77.6 2.67c 3.53b 2.96c
Pooled SE 8.1 11.2 10.7 2.60 1.33 1.58 0.07 0.13 0.17
P value 0.007 0.137 0.024 0.007 0.102 0.577 <0.001 0.002 <0.001
VA06 1 769a 212d 148d 39.4c 18.3 70.0c 4.16a 3.79ab 3.41a
VA06 2 736ab 245cd 184c 46.0b 18.7 73.8abc 3.45bc 3.84a 3.41a
VA06 3 756a 274abc 204abc 51.8a 19.0 77.1a 3.49b 3.72abc 3.31ab
VA06 4 766a 277ab 214a 53.7a 19.3 77.6a 3.23c 3.81ab 3.32ab
VA06 5 758a 289a 217a 54.2a 18.9 78.4a 2.91d 3.72bc 3.20c
VA06 6 708b 266abc 190bc 51.0a 19.3 74.6abc 3.31bc 3.71bc 3.22bc
VA06 7* 706b 287a 212ab 51.8a 18.1 78.4a 2.69d 3.75abc 3.21c
VA06 8 627c 253bc 184c 45.7b 18.1 71.0bc 2.78d 3.66c 3.09d
VA06 9 643c 253bc 186c 46.7b 18.5 75.6ab 2.68d 3.77abc 3.23bc
Pooled SE 6.7 9.8 10.6 2.76 1.21 1.77 0.08 0.12 0.18
P value <0.001 <0.001 <0.001 <0.001 0.126 <0.001 <0.001 0.001 <0.001
Table 5. Relative yields (%) of dry matter content, in vitro digestible organic matter (dOM) and in vitro fermentation potential (GP, A1+A2) of three grasses for early and late cutting1 compared to practical harvest time (100%) in Vietnam.
Table 5. Relative yields (%) of dry matter content, in vitro digestible organic matter (dOM) and in vitro fermentation potential (GP, A1+A2) of three grasses for early and late cutting1 compared to practical harvest time (100%) in Vietnam.
Parameter Mombasa Mulato II King
2 4 5 6 2 4 6 8 3 5 7 9
DM 95.8 98.6 100 101 68.4 84.2 100 116 116 108 100 92.2
dOM 95.3 99.7 100 97.1 73.9 91.5 100 116 116 112 100 84.1
GP 101 114 100 114 70.9 92.8 100 109 102 109 100 86.7
A1+A2 95.8 108 100 101 72.6 97.9 100 112 98 109 100 84.8
1Assuming additivity of harvest time.DM = dry matter content; GP = In vitro cumulative gas production; A1+A2 = in vitro fermentation potential of the soluble in insoluble carbohydrates.Based on data of Hare et al. [19,20] and Sales et al. [21].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2024 MDPI (Basel, Switzerland) unless otherwise stated