Acta agriculturae Slovenica, 120/1, 1–7, Ljubljana 2024 doi:10.14720/aas.2024.120.1.16702 Original research article / izvirni znanstveni članek Rumen gas kinetics: a comparative analysis of two in vitro assessment methods for forage evaluation Nejc VALCL 1, 2, Andrej LAVRENČIČ 1 Received November 22, 2023; accepted February 02, 2024. Delo je prispelo 22. novembra 2023, sprejeto 02. februarja 2024 1 University of Ljubljana, Biotechnical Faculty, Department of Animal Science, Ljubljana, Slovenia 2 Corresponding author, e-mail: nejc.valcl@bf.uni-lj.si Rumen gas kinetics: a comparative analysis of two in vitro assessment methods for forage evaluation Abstract: Gas production from thirty samples of feed- stuffs (10 samples of corn silage, grass silage, and grass hay, respectively) was assessed in vitro using two methods: the Hohenheim gas test (HGT) and the ANKOM RF Gas Produc- tion System (ANKOM). Samples were incubated in buffered rumen fluid. Gas kinetic parameters were calculated using the Gompertz model. Results revealed significantly lower gas production with the ANKOM compared to the HGT. Signifi- cant differences were observed between the HGT and AN- KOM in the specific gas production rate (parameter C), maxi- mum fermentation rate (MFR) and gas produced after 24 h of incubation (Gas24) for each feed group. High coefficients of determination (R2) were calculated between the methods for the gas kinetic parameters MFR, Gas24, total potential gas production (parameter B), decrease in the specific gas production rate (parameter A), moderate R2 for C, and low R2 for time of maximum fermentation rate (TMFR). Despite the lower quantities of gas generated with the ANKOM, there are strong correlations in the parameters of gas kinetics that promise the possibility of developing correction models. Fu- ture development of such models could position the ANKOM as a viable alternative to HGT, particularly for calculating me- tabolizable energy and net energy for lactation in feedstuffs. Key words: animal nutrition, rumen, gas production, gas kinetic parameters, Ankom RF Gas Production System, Hohenheim Gas Test Kinetika plinov v vampu: primerjalna analiza dveh in vitro metod za ocenjevanje krme Izvleček: Tvorba plina iz tridesetih vzorcev krme (po 10 vzorcev koruzne silaže, travne silaže in sena) je bila oce- njena in vitro z dvema metodama: Hohenheimskim plin- skim testom (HGT) in ANKOM RF Gas Production System (ANKOM). Vzorci so bili inkubirani v puferiranem vam- povem soku. Parametri kinetike produkcije plinov so bili izračunani z uporabo Gompertzovega modela. Rezultati so pokazali statistično značilno manjšo tvorbo plina pri me- todi ANKOM v primerjavi s HGT. Med metodama HGT in ANKOM smo opazili razlike v specifični hitrosti fermen- tacije (parameter C), največji hitrosti fermentacije (MFR) in plinu, proizvedenem po 24 urah inkubacije (Gas24), za vsako skupino krmil. Visoki koeficienti determinacije (R2) med metodama so bili izračunani za MFR, Gas24, skupno potencialno tvorbo plina (parameter B) in faktor mikrobne (ne)učinkovitosti (parameter A), zmeren R2 za parameter C in nizek R2 za čas, v katerem je bila dosežena največja hitrost fermentacije (TMFR). Kljub manjšim količinam plina, ki je nastal z uporabo metode ANKOM, obstajajo močne korela- cije v parametrih kinetike tvorbe plinov, ki kažejo na mo- žnost razvoja korekcijskih modelov. S prihodnjim razvojem takih modelov bi bila metoda ANKOM lahko uporabljena kot zadovoljiva alternativa HGT, zlasti za izračun presnovlji- ve energije in neto energije za laktacijo v krmi. Ključne besede: prehrana živali, vamp, produkcija plinov, kinetika produkcije plinov, parametri, metoda AN- KOM, Hohenheimski plinski test Acta agriculturae Slovenica, 120/1 – 20242 N. VALCL and A. LAVRENČIČ 1 INTRODUCTION In vitro measurements of gas production in the ru- men are an important scientific method for estimating metabolizable energy (ME) and net energy for lacta- tion (NEL) in conjunction with chemical analyses of feedstuffs. They are also used to determine the suitabil- ity of feed additives or feed rations for ruminants, the activity and biomass of microorganisms in the rumen and the quantification of volatile fatty acids produced during the incubation of substrata (Menke and Ste- ingass, 1988; Aiple et al., 1995). The standard method for measuring in vitro gas production in the rumen is the Hohenheim gas test (HGT; Menke and Steingass, 1988). In this method, substrata are incubated in glass syringes and gas production is measured manually at fixed times. The method is therefore very labour-inten- sive. Since the development of the HGT, new methods have been developed that aim to automate and simplify the measurement process (Davies et al., 2000). One of the first such systems was developed by Theodorou et al. (1994), which measured gas production using a pressure transducer. The incubations were carried out in gas-tight culture flasks in which gases could accu- mulate during fermentation. The pressure in each flask was displayed on a digital indicator and then recorded manually. Excess gas that accumulated in each flask was removed manually with a syringe needle. Davies et al. (2000) then developed an automatic system where the gas that accumulates in the headspace of the flask dur- ing fermentation is automatically recorded and released when the pressure in the flask reaches a certain level. This was a direct improvement over the classic HGT system, as the researcher did not have to be present at certain times to manually record the amount of gas produced. For the accurate calculation of the gas kinet- ic parameters, it is important to record the gas volumes more frequently. This makes manual recording very la- bour intensive. Therefore, an automatic system such as the ANKOMRF gas production system, which is able to automatically record the gas pressure produced at more frequent times during the incubation (e.g. every 30 minutes), should improve the accuracy and reliability of the measurements. The disadvantages of automatic systems are that they are prone to electronic and me- chanical errors. Such a system is also more expensive than the manual HGT. For the correct estimation of ru- men degradability of feedstuffs and the effects of feed additives, it is very important that the different systems are as accurate as possible when measuring rumen in vitro gas production. A comparison of the manual (HGT) and auto- matic (ANKOM) methods of measuring rumen in vitro gas production was carried out to determine whether the automatic method is a valid replacement for the standard HGT. The aim of the study was to compare the HGT with the ANKOM based on the gas production measured with both methods. The hypothesis was that the ANKOM does not differ from the HGT in terms of gas production measurements and therefore kinetic parameters of in vitro gas production. 2 MATERIALS AND METHODS 2.1 SUBSTRATES AND CHEMICAL COMPOSI- TION Thirty samples of forages, ten samples of vary- ing quality of grass silage (GS), 10 of corn silage (CS) and 10 of grass hays (H), were used as substrates. The substrata were dried at 50 °C to the constant mass and ground through a 1 mm sieve. Samples were analysed for dry matter (DM), crude protein (CP), ash and ether extract (EE). Neutral detergent fibre (NDF) content was determined using the Van Soest method (Goering and Van Soest, 1970). Chemical compositions of each feed group are presented as means ± standard deviation in Table 1. All values are presented as g kg–1 DM unless specified otherwise. 2.2 EXPERIMENTAL DESIGN AND IN VITRO GAS PRODUCTION For the evaluation of in vitro gas production, two measurement techniques were used: manual (HGT) with the measurement of the volume of gas in the glass syringes as described by Menke and Steingass (1988), Indices Corn silages Grass hays Grass silages DM (g kg−1) 940 ± 10.6 937 ± 11.8 928 ± 15.9 Ash 33 ± 3.5 70 ± 15.6 108 ± 38.1 EE 27 ± 3.1 15 ± 3.7 26 ± 6.0 CP 67 ± 11.9 95 ± 18.6 136 ± 33.2 NDF 465 ± 96.7 630 ± 45.3 533 ± 89.3 NFC 407 ± 101.0 190 ± 62.5 197 ± 110.2 Table 1: Chemical composition of corn silages, grass hays and grass silages (arithmetic means ± standard deviations; n = 10 for each feed group) DM – dry matter; EE – ether extract; CP – crude protein; NDF – neu- tral detergent fibre; NFC – non-fibre carbohydrates (1000 – (CP + EE + Ash + NDF)) Acta agriculturae Slovenica, 120/1 – 2024 3 Rumen gas kinetics: a comparative analysis of two in vitro assessment methods for forage evaluation and automatic with the measurements of gas pressure within the 100 ml glass flasks (ANKOM). Rumen fluid was taken from two mature castrated Jezersko Solčavska × Romanovska rams (Ovis aries), with an average weight of 70 kg, fitted with permanent rumen cannula. A daily ration consisting of average quality hay (Ash = 38 g kg–1 DM, CP = 172 g kg–1 DM, NDF = 579 g kg–1 DM) was offered to them ad libitum (approx. 1.5 kg consumed) with the addition of 0.25 kg pelleted commercial compound feed (160 g CP kg–1), and mineral and vitamin mix (0.025 kg) once per day. The diet composition was calculated according to the German metabolizable energy (ME) and utilisable protein requirements (nXP; DLG, 1997) with which the protein and energy requirements for maintenance were met and the energy-to-protein ratio of the rumen was balanced. Animals were kept in compliance with animal welfare regulations (U33401-12/2019/9 dated 16.7.2019, issued by the Food Safety, Veterinary and Phytosanitary Inspectorate, Ministry of Agriculture, Forestry and Food, Republic of Slovenia Food Safety, Veterinary and Plant Protection Administration, Lju- bljana, Slovenia). The study was conducted from October 2022 to March 2023 in 10 total consecutive runs (1 week = 1 run). All samples were incubated in rumen fluid using the HGT (runs = 3) and ANKOM (runs = 7). The num- ber of consecutive runs for the ANKOM was higher due to the smaller number of ANKOM modules avail- able. With both methods, the buffer medium was pre- pared as described by Menke and Steingass (1988) us- ing the rumen fluid to buffer solution ratio of 1:2. Both methods included two blank samples (only inoculum without substrate) and two samples of Italian ryegrass (Lolium multiflorum) 2nd cut in flowering period as hay standard. Gas production after 24 h for the hay stand- ards was known (HGT: 196 ml 1 g–1 DM–1; ANKOM: 140 ml g–1 DM–1). Hay standard factors (measured/ known gas production) were then calculated between runs and ranged from 0.92 to 1.12. The mean stand- ard factor for this trial was 1.004, hence gas production measurements for each run were not corrected. Sheep rumen fluid was taken before morning feed- ing, and was transported to the laboratory immediate- ly inside a thermo flask heated to 39 °C, and strained through two and then four layers of cheesecloth. Us- ing the manual method, gas production kinetics were evaluated by anaerobically incubating each feed sample (250 ± 5 mg/syringe) in four 100 ml glass syringes filled with 30 ml of buffered rumen fluid. Syringes were kept in a water bath at 39 °C. Gas production was measured manually after 0, 2, 4, 6, 8, 10, 12, 24, 36, 48, and 72 h. The syringes were manually shaken at each measurement. If gas production exceeded 80 ml in the first 36 h, the volume was recorded and the gas was released. In each run, two blank samples and two hay standard samples were included. Using the automatic method, developed by Ankom Technology® (Macedon, NY, USA; ANKOMRF gas pro- duction system), each feed sample (250 ± 5 mg/flask), was anaerobically incubated in the 30 ml of buffered rumen fluid. Each unit consisted of a 100 ml glass flask (actual volume: 137 ml; headspace volume: 107 ml) and an ANKOM pressure sensor module, equipped with a microchip and a radio sender. The system automatically measures gas pressure inside the unit and automatically releases the pressure when it reaches a set threshold of 7.5 kPa. The decision to set the pressure threshold to 7.5 kPa was based on methodologies of studies using the ANKOM method for in vitro gas production mea- surements (Tagliapietra et al. 2010; Cornou et al. 2013; Bachmann et al. 2020). The gas pressure was recorded every 30 minutes for 72 h. After the start of the incu- bation, the flasks were manually shaken daily. After in- cubation, the gas pressure was converted into amount units (moles) of gas using the “ideal” gas law (Equa- tion 1) and then converted to millilitres (ml) of gas produced by Avogadro’s law (Equation 2): 𝑛𝑛𝑛𝑛 = 𝑝𝑝𝑝𝑝 � 𝑉𝑉𝑉𝑉 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅� (1) where n is gas produced in moles (mol), p is cumulative pressure in kilopascals (kPa), V is the headspace volume in the glass flask in litres (l), T is the temperature in Kel- vin (K) and R is gas constant (8.314472 J (K × mol)–1). The gas production is then calculated as: 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 �𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚� = 𝑛𝑛𝑛𝑛 × 22.4 𝑚𝑚𝑚𝑚 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 × 1000 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑚𝑚𝑚𝑚 (2) where GP is the volume of gas produced. 2.3 CALCULATIONS AND STATISTIC ANALYSES Gas production kinetic parameters were calcu- lated as described by Lavrenčič et al. (1997). The net volume of gas produced at each incubation time was calculated as the difference between the total volume of gas produced and the volume of gas produced from the blank sample at each time of incubation. Net volumes at each time of incubation were adjusted afterwards to 1 g of substrate DM. The obtained in vitro gas produc- tion data were then fitted with the Gompertz model (Lavrenčič et al., 1997): Acta agriculturae Slovenica, 120/1 – 20244 N. VALCL and A. LAVRENČIČ 𝑌𝑌𝑌𝑌𝑡𝑡𝑡𝑡 = 𝐵𝐵𝐵𝐵 × 𝑒𝑒𝑒𝑒−𝐶𝐶𝐶𝐶×𝑒𝑒𝑒𝑒 −𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 (3) Where Yt is gas produced at the time “t” (ml g –1 DM), B is the total potential gas production (ml g–1 DM), C is the specific gas production rate, A is the decrease in specific gas production rate and t is the time in hours (h). The parameters were calculated in SAS 9.4. (SAS Software ver. 9.4; SAS Institute, Cary, NC, USA), using the PROC NLIN procedure for a nonlinear regression method with the Marquardt compromise to estimate the kinetic parameters and fit the curve for each sy- ringe within a substrate. By inserting a fixed time of 24 h in the equation of the Gompertz model with known parameters, the amount of gas produced in 24 h was calculated. By setting the second derivative of the Gompertz model to zero (0) and solving for “t”, times of maximum fermentation rates (TMFR) were calculated: 𝑑𝑑𝑑𝑑2𝑦𝑦𝑦𝑦 𝑑𝑑𝑑𝑑𝑡𝑡𝑡𝑡2 = 𝐴𝐴𝐴𝐴 × 𝐵𝐵𝐵𝐵2 × 𝐶𝐶𝐶𝐶2 × (𝑒𝑒𝑒𝑒−𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴)2 × 𝑒𝑒𝑒𝑒−𝐶𝐶𝐶𝐶×𝑒𝑒𝑒𝑒−𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 −𝐴𝐴𝐴𝐴 × 𝐵𝐵𝐵𝐵 × 𝐶𝐶𝐶𝐶2 × 𝑒𝑒𝑒𝑒−𝐶𝐶𝐶𝐶×𝑒𝑒𝑒𝑒−𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = 0 → 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (4) Using the corresponding value of TMFR in the first derivative equation, maximum fermentation rates (MFR) were calculated: 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 = 𝐵𝐵𝐵𝐵 × 𝐶𝐶𝐶𝐶 × 𝐴𝐴𝐴𝐴−𝐴𝐴𝐴𝐴×𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇×𝑒𝑒𝑒𝑒−𝐶𝐶𝐶𝐶×𝑒𝑒𝑒𝑒 −𝐴𝐴𝐴𝐴×𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (5) With a one-way analysis of variance (ANOVA), using the general linear model (PROC GLM), the ef- fect of the feed group, sample, method and interaction between the feed group and method on the estimated and calculated kinetic parameters of gas production, was compared. The results are presented as least square means (Table 1): 𝑌𝑌𝑌𝑌𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝜇𝜇𝜇𝜇 + 𝐹𝐹𝐹𝐹𝑖𝑖𝑖𝑖 + 𝑆𝑆𝑆𝑆𝑖𝑖𝑖𝑖 + 𝑀𝑀𝑀𝑀𝑖𝑖𝑖𝑖 + 𝐹𝐹𝐹𝐹𝑀𝑀𝑀𝑀𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 + 𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 (6) Where Yijkl are the estimated and calculated kinetic parameters of gas production, Fi is the effect of the feed group (i = corn silage, grass silage, grass hay), Sj is the effect of the sample (j = 1, 2… 30), Mk is the effect of the method (k = ANKOM, HGT) and FMik is the interac- tion between feed groups and methods. 3 RESULTS AND DISCUSSION Within each feed group, significant differences (p < 0.05) were found between the ANKOM and HGT for the parameters C, MFR and Gas24, but not for B, A and TMFR (Table 2). Parameter C measured with AN- KOM was 25 % lower for maize silage, 27 % lower for grass silage and 38.5 % lower for grass hay compared to the HGT. Using the ANKOM, the MFR parameter was lower in every of the feed groups compared to the HGT. The differences were –41.3 % for corn silages, –50 % for grass silages and –62.8 % for grass hays, respectively. The rate at which gas is produced with the ANKOM Feed group Method B (ml g-1 DM) C A MFR (ml h-1) TMFR (h) Gas24 (ml g-1 DM) Corn silage ANKOM 240 2.11 0.096 8.4 7.9 191 HGT 259 2.99 0.166 14.3 6.6 242 Grass silage ANKOM 160 1.97 0.087 5.3 8.6 120 HGT 182 2.69 0.156 10.6 6.3 168 Grass hays ANKOM 177 1.63 0.049 2.9 12.5 97 HGT 206 2.56 0.102 7.8 9.5 162 P – values F <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 S <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 M <.0001 <.0001 <.0001 <.0001 0.0005 <.0001 F × M 0.6470 0.0168 0.0625 <.0001 0.5486 0.0082 Table 2: Effect of method, individual sample, and feed group on estimated and calculated kinetic parameters of in vitro gas production F – feed group; S – sample; M – method; F × M – interaction between feed group and method; B – total potential gas production; C – specific gas production rate; A – decrease in specific gas production rate; MFR – maximum fermentation rate; TMFR – time of maximum fermentation rate; Gas24 – gas produced after 24 h of incubation Acta agriculturae Slovenica, 120/1 – 2024 5 Rumen gas kinetics: a comparative analysis of two in vitro assessment methods for forage evaluation could be affected by the amount of gas dissolved in the medium. With the ANKOM, the gas produced is re- leased out of the headspace of the flask only when the pressure inside reaches a certain threshold. According to Henry’s law, a certain proportion of these gases are dissolved in the medium and are released into the head- space of the flask only after the excess gasses are already released (Theodorou et al., 1994). It has also been point- ed out that microbial activity could be disturbed, if the pressure exceeds 48 kPa (Theodorou et al., 1994). Low- man (1998) implied that continuous venting of flasks at 4.5 kPa should prevent the saturation of the solution. They also found out that, if the flasks were not shaken at all, their gas production was higher than in flasks shak- en recurrently at pre-set times or continuously on an orbital shaker. Supersaturation of CO2 in the medium may also occur at high gas pressures in closed systems, which can lead to biased measurements of gas produc- tion (Tagliapietra et al. 2010; Cattani et al. 2014). In our study, the threshold for venting the ANKOM flasks was set at 7.5 kPa, which was similar to Cornou et al. (2013), and the flasks were shaken regularly. With the HGT, the plungers of the syringes were greased to avoid high pressures by allowing the accumulated gases to expand, and they were shaken at fixed times. Gas produced after 24 h for feeds measured with the HGT (Table 2) was similar to the findings of Getachew et al. (2004). Their corn silage produced 232 ml g–1 DM gas, while their wheat silage, which was similar to our grass silages, produced 172 ml g–1 DM gas. Compared to HGT, the ANKOM resulted in signifi- cantly lower (p < 0.05) gas production in the first 24 h Figure 1: Relationship between parameters B, Gas24, A, MFR, C, and TMFR using the HGT (Hohenheim gas test) versus the ANKOM RF gas system (dashed line = regression line; dotted line = constant diagonal) for corn silage (●), grass hays (■) and grass silage (∆) Acta agriculturae Slovenica, 120/1 – 20246 N. VALCL and A. LAVRENČIČ of incubation (Gas24) for all feed groups. The differ- ences were –21.0 % for corn silages, –28.5 % for grass silages and –40.1 % for grass hays. Bachmann et al. (2020) reported lower gas production measured in gen- eral with the ANKOM compared to the HGT. They also reported that the rankings of substrates remained the same regardless of the system used. These results were similar to our findings, as corn silages produced the most gas, grass silages were ranked second and grass hay produced the least gas, in both the HGT and ANK- OM system. Our results also partly agree with Gierus et al. (2008), who have shown that their automated pres- sure evaluation system produced significantly less gas after 24 h compared to HGT for grass silages but not for grass hay, while Elberg et al. (2018) have shown, that gas production in 24 h of incubation in the automated sys- tem compared to HGT, was significantly lower for corn silages and for grass hays, but not for grass silages. Gas production can be affected by the ratio between rumen fluid and buffer, the diet of donor animals, and the gen- eral variability of rumen fluid on collection day (Rymer et al., 2005). In this study, the incubation parameters were standardised across both methods, except in times of rumen fluid collection. Due to the smaller number of ANKOM modules available, we performed the in vi- tro incubation in a higher number of runs than with the HGT. Considering all these factors, we cannot fully explain the differences between the compared systems. Figure 1 shows the distribution of parameters for each sample comparing the ANKOM to the HGT. All the single values for each parameter were plotted. The coefficients of determination (R2) show a strong cor- relation between the methods across all samples in the parameters B, A, MFR, and Gas24, a moderate correla- tion for parameter C, and a very weak correlation for parameter TMFR. Bachmann et al. (2020) reported an R2 of 0.57 for gas produced after 24 h (Gas24) between the two methods from substrates used, however, they used a smaller number of substrates (n = 6), compared to our study (n = 30). 4 CONCLUSIONS The gas kinetic parameters C, MFR and Gas24 ob- tained with the ANKOM differed significantly from the HGT. Despite these differences, the rankings for each feed group in gas produced and gas kinetic parameters were equal between both methods and showed strong correlations between the methods in all parameters ex- cept TMFR. In this regard, the methods are comparable in terms of ranking, but not in terms of absolute values. 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