Relationship between water hardness, pH, and organic acid requirement for effective water acidification in swine operations

A total of 45 water samples from swine production sites across six states were used to determine the amount of CitraSol (Northwest Livestock Distribution, Medina, MN), a citric acid product, required to reduce water pH to a common end point. Water samples were analyzed for pH, Ca, Mg, and hardness. Total hardness was calculated using Ca and Mg concentrations and expressed as mg of CaCO<sub>3</sub>/L. Water hardness ranged from 142 to 1,181 mg CaCO<sub>3</sub>/L with an average of 441.2 mg CaCO<sub>3</sub>/L. Initial pH ranged from 7.42 to 8.47 with an average of 7.91. In triplicate, CitraSol was added to 10 mL samples of each water source to reach a stable pH of 5.0 and 4.0 ± 0.05. An inverse relationship between water hardness and initial pH was observed (quadratic, <i>P = </i>0.002; R<sup>2</sup> = 0.22). The amount of CitraSol required to reach a stable pH of 4.0 increased (quadratic, <i>P <</i>0.001) as hardness, Ca, and Mg increased (R<sup>2 </sup>= 0.30, 0.27, 0.28, respectively). Surprisingly, high initial pH water required less (quadratic, <i>P <</i>0.001; R<sup>2</sup> = 0.31) CitraSol to reach a pH of 4.0. We hypothesize this was partially due to the reduction in the amount of free Ca ions as the water becomes more alkaline in nature. A sub sample of the water samples was titrated using Activate WD Max (Novus International, Chesterfield, MO) to determine if the amount of acid required to reduce water pH to the same common end point was acid specific. A direct relationship between the amount of CitraSol and Activate WD Max (linear, <i>P <</i>0.001; R<sup>2</sup> = 0.87) to reach a pH of 4.0 was observed, suggesting that data from one acid may allow prediction of the quantity required of another acid to reach the same target pH. Similarly, titrating to a pH of 5.0 can predict the amount of acid required to reach a pH of 4.0 (linear, <i>P <</i>0.001; R<sup>2</sup> = 0.99). In conclusion, pH, Ca, Mg, and hardness cannot fully predict the amount of acid required to reach a stable water pH of 4.0. However, relationships were observed that can partially explain the variation in the amount of acid required. This data suggests that acid titrations of individual water sources should be completed to determine the amount of acid required to reach a final pH of 4.0.

Authors

Institutions

Publication Details

Journal
Translational Animal Science
Published
2025-01-01
DOI
https://doi.org/10.1093/tas/txaf164
Primary Topic
Odor and Emission Control Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relationship between water hardness, pH, and organic acid requirement for effective water acidification in swine operations

Joel M DeRouchey, Mike D Tokach, Ganga M. Hettiarachchi, Robert D Goodband et al.
Translational Animal Science
Odor and Emission Control Technologies
article

Relationship between water hardness, pH, and organic acid requirement for effective water acidification in swine operations

Joel M DeRouchey, Mike D Tokach, Ganga M. Hettiarachchi, Robert D Goodband, Jordan T Gebhardt, Jason C Woodworth, Maxwell L Corso, Julian Arroyave
article en

Abstract

A total of 45 water samples from swine production sites across six states were used to determine the amount of CitraSol (Northwest Livestock Distribution, Medina, MN), a citric acid product, required to reduce water pH to a common end point. Water samples were analyzed for pH, Ca, Mg, and hardness. Total hardness was calculated using Ca and Mg concentrations and expressed as mg of CaCO<sub>3</sub>/L. Water hardness ranged from 142 to 1,181 mg CaCO<sub>3</sub>/L with an average of 441.2 mg CaCO<sub>3</sub>/L. Initial pH ranged from 7.42 to 8.47 with an average of 7.91. In triplicate, CitraSol was added to 10 mL samples of each water source to reach a stable pH of 5.0 and 4.0 ± 0.05. An inverse relationship between water hardness and initial pH was observed (quadratic, <i>P = </i>0.002; R<sup>2</sup> = 0.22). The amount of CitraSol required to reach a stable pH of 4.0 increased (quadratic, <i>P <</i>0.001) as hardness, Ca, and Mg increased (R<sup>2 </sup>= 0.30, 0.27, 0.28, respectively). Surprisingly, high initial pH water required less (quadratic, <i>P <</i>0.001; R<sup>2</sup> = 0.31) CitraSol to reach a pH of 4.0. We hypothesize this was partially due to the reduction in the amount of free Ca ions as the water becomes more alkaline in nature. A sub sample of the water samples was titrated using Activate WD Max (Novus International, Chesterfield, MO) to determine if the amount of acid required to reduce water pH to the same common end point was acid specific. A direct relationship between the amount of CitraSol and Activate WD Max (linear, <i>P <</i>0.001; R<sup>2</sup> = 0.87) to reach a pH of 4.0 was observed, suggesting that data from one acid may allow prediction of the quantity required of another acid to reach the same target pH. Similarly, titrating to a pH of 5.0 can predict the amount of acid required to reach a pH of 4.0 (linear, <i>P <</i>0.001; R<sup>2</sup> = 0.99). In conclusion, pH, Ca, Mg, and hardness cannot fully predict the amount of acid required to reach a stable water pH of 4.0. However, relationships were observed that can partially explain the variation in the amount of acid required. This data suggests that acid titrations of individual water sources should be completed to determine the amount of acid required to reach a final pH of 4.0.

Translational Animal ScienceVol. 9
Kansas State University (US)
Openalex Percentile: Top 68%
Odor and Emission Control Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.