Some feed ingredients bind more acid in the stomach than others and for this reason may be best omitted from pig starter foods if gastric acidity is to be promoted. The objective of this study was to measure the acid-binding capacity (ABC) of ingredients commonly used in pig starter foods. Ingredients were categorised as follows: (i) milk products (n = 6), (ii) cereals (n = 10), (iii) root and pulp products (n = 5), (iv) vegetable proteins (n = 11), (v) meat and fish meal (n = 2), (vi) medication (n = 3), (vii) amino acids (n = 4), (viii) minerals (n = 16), (ix) acid salts (n = 4), (x) acids (n = 10). A 0.5 g sample of food was suspended in 50 ml distilled de-ionised water with continuous stirring. This suspension was titrated with 0.1 mol/L HCl or 0.1 mol/L NaOH so that approximately 10 additions of titrant was required to reach pH 3.0. The pH readings after each addition were recorded following equilibration for three minutes. ABC was calculated as the amount of acid in milliequivalents (meq) required to lower the pH of 1 kg food to (a) pH 4.0 (ABC-4) and (b) pH 3.0 (ABC-3). Categories of food had significantly different (P < 0.01) ABC values. Mean ABC-4 and ABC-3 values of the ten categories were: (i) 623 (s.d. 367.0) and 936 (s.d. 460.2), (ii) 142 (s.d. 79.2) and 324 (s.d. 146.4), (iii) 368 (s.d. 65.3) and 804 (s.d. 126.7), (iv) 381 (s.d. 186.1) and 746 (s.d. 227.0), (v) 749 (s.d. 211.6) and 1508 (s.d. 360.8), (vi) 120 (s.d. 95.6) and 261 (s.d. 163.2), (vii) 177 (s.d. 60.7) and 1078 (s.d. 359.0), (viii) 5064 (s.d. 5525.1) and 7051 (s.d. 5911.6), (ix) 5057 (s.d. 1336.6) and 8945 (s.d. 2654.1) and (x) -5883 (s.d. 4220.5) and -2591 (s.d. 2245.4) meq HCl per kg, respectively. Within category, ABC-3 and ABC- 4 values were highly correlated: R2 values of 0.80 and greater for food categories i, iv, v, vi, vii and viii. The correlation between predicted and observed ABC values of 34 mixed diets was 0.83 for ABC-4 and 0.71 for ABC-3. It was concluded that complete diets with low ABC values may be formulated through careful selection of ingredients. The final pH to which ABC is measured should matter little as ABC-3 and ABC-4 are highly correlated.

Eighteen Pediococcus strains were screened for their potential as silage inoculants. Pediococcus acidilactici G24 was found to be the most suitable, exhibiting a short lag phase on both glucose and fructose, a rapid rate of acid production, a high sugar-to-lactate conversion efficiency, no detectable breakdown of proteins or lactic acid, and the ability to grow within a broad range of pH and temperature. When tested in laboratory silos using grass with a water-soluble carbohydrate content of 24 gfkg of aqueous extract, P. acidilactici G24 stimulated the natural LactobaciUus plantarum population and accelerated the rates of lactic acid production and pH decrease. After 6 days of fermentation, the inoculated silage exhibited a 12% decrease in ammonia nitrogen and an 11% increase in crude protein levels compared with uninoculated controls. The use of an L. plantarum inoculant at a rate of 104 bacteria per g of grass in conjunction with P. acidilactici G24 produced no additional beneficial effect. Inoculation of grass with a water-soluble carbohydrate level of 8 g/kg of aqueous extract with P. acidilactici G24 led to no acceleration in the rate of L. plantarum growth or pH decrease. However, after 7 days of fermentation the inoculated silage had a 14% lower ammonia nitrogen protein content than did uninoculated controls. The results suggest that P. acidilactici G24 may be useful as a silage inoculant for crops with a sufficiently high water-soluble carbohydrate level.

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Expression of the inner membrane protein FoxB (PA2465) of Pseudomonas aeruginosa in mutants of Sinorhizobium meliloti that are defective in the utilization of ferrichrome, ferrioxamine B, and schizokinen resulted in the restoration of siderophore utilization. Mutagenesis of foxB in P. aeruginosa did not abolish siderophore utilization, suggesting that the function is redundant.

F. DUFFNER AND M. O'CONNELL. 1995. Seventy‐two Lactobacillus plantarum isolates were recovered from six uninoculated grass silages for the purposes of firstly evaluating the usefulness of (1) restriction endonuclease digestion of total genomic DNA, (2) plasmid profiling and (3) ribotyping in Lact. plantarum strain differentiation and secondly, examining the strain heterogeneity in well preserved silage. The three methods for differentiation were applied to 72 of the isolates and allowed at least 32 different strains to be identified. Twenty‐five different plasmid profiles were detected (26 if the absence of plasmids is included as a profile). Ribotyping with Eco RI identified only 11 patterns among the silage isolates. A variety of restriction enzymes was screened to increase the sensitivity of ribotyping to detect strain differences and Bam HI was used successfully for this purpose, differentiating all of the strains tested. Two dominant strains (I and II) were identified in one particular silage, comprising 47% and 17% respectively of the isolates, while strains III and V comprised 37% and 25% of the Lact. plantarum population isolated from another of the silages.

Three trials were conducted to determine the optimum dietary lysine concentration for maximum growth rate (ADG) or minimum food conversion ratio (FCR) of boars and gilts from 60 to 90 kg (in pairs) and 80 to 100 kg (in pairs or groups). Ninety pairs of pigs and six treatments (dietary lysine concentrations) were used in experiment 1 (60 to 90 kg), 144 pairs and eight treatments in experiment 2 (80 to 100 kg) and groups of 13 pigs (no.=42 groups) and six treatments in experiment 3 (80 to 100 kg). Experiments were arranged as randomized-block designs, blocked on the basis of sex and start weight. Isoenergetic diets (13·8 MJ digestible energy per kg) were based on barley, wheat, soya-bean meal, with added vitamins, minerals and amino acids. Dietary lysine concentrations were: 7·9, 8·8, 9·7, 10·7, 11·7 and 12·5 g/kg in experiment 1; 7·0, 7·9, 8·8, 9·7, 10·7, 11·7, 12·5 and 13·5 g/kg in experiment 2; and 7·0, 7·9, 8·8, 9·7, 10·7 and 11·7 g/kg in experiment 3. In experiment 1 (60 to 90 kg pairs), ADG increased (quadratic, P<0·01) and FCR improved (quadratic, P<0·001) with increased lysine concentration. Although boars grew faster (P<0·001) and were more efficient (P<0·001) than gilts, maximum ADG was predicted at 10·8 g lysine per kg and minimum FCR at 10·9 g lysine per kg for all pigs. In experiment 2 (80 to 100 kg pairs), a treatment×sex interaction for ADG (P<0·01) and FCR (P<0·05) indicated that boars grew faster and had better FCR than gilts at dietary lysine concentrations above 10·7 and 9·7 g/kg respectively, with no difference between the sexes below these lysine levels. Maximum ADG was predicted at 11·8 and 9·9 g lysine per kg and minimum FCR was predicted at 11·9 and 10·0 g lysine per kg for boars and gilts, respectively. In experiment 3 (80 to 100 kg groups) ADG increased (quadratic, P<0·01) and FCR improved (quadratic, P<0·001) as dietary lysine concentration increased. Boars had higher ADG (P<0·001) and better FCR (P<0·001) than gilts. Maximum ADG and minimum FCR were predicted at 9·3 and 9·6 g lysine per kg for all pigs. In conclusion, boars grew faster and more efficiently than gilts, with interactions in experiment 2 indicating a greater difference in performance at higher dietary lysine concentrations.

Changes in physical body size during gestation were monitored using 529 sets of sow measurements. All sows were from the same herd and production system with a range in parity from 1 to 8. Sows were individually weighed, P2 backfat thickness was determined by ultrasound and morphometric measurements of body size were taken five times during gestation: day 0 (at service), day 25, day 50, day 80 and day 110. The morphometric measurements included sow height (from floor to last rib at the midline, from floor to ventral surface and from floor to hip), heart girth, depth of last rib, length (from snout to tail and from anterior scapula to tail) and width (at ham, at last rib and at shoulder). Regression analyses were used to model the relationship between day of gestation or parity number and morphometric measurements of body size. Regression equations were also developed to estimate sow weight from physical measurements, day of gestation and parity. As expected, sow dimensions, in general, increased as pregnancy progressed and also with increasing parity number. The relationships between day of gestation and body dimensions were described by linear and quadratic regression models, which had a range of adjusted R 2 values up to 0.99. Similar relationships to parity number had a range of R 2 values between 0.51 and 0.96. Sow depth, which can be used as an estimate of the width of the sow when lying, equalled the maximum width of the gestation stall (650 mm) at day 103 of gestation. However, by day 40 of gestation, predicted mean sow depth (570 mm) equalled the width at the rear of the crate. The implication of this is that after day 40 of gestation, the average sow was too wide for the rear of the crate when lying in a recumbent position. On day 110 of gestation, 95% of the mean sow body depths would be accommodated in stalls that were 674 mm wide; however, the range in body sizes with increasing parity number suggests the use of more than one stall width would be appropriate. Sow weight could be estimated with an adjusted R 2 value of 0.81 and with a residual standard deviation (r.s.d.) of 16.5 kg using heart girth alone, or more accurately using a model with parity, day of gestation, P2 backfat depth and heart girth as the parameters (R 2 5 0.89, r.s.d. 12.4 kg).

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