Systems and methods for computer models of animal feed

1. A method for analyzing feed for swine or poultry comprising steps of:

(a) digesting in vitro a plurality of samples of animal feed each having an animal feed composition to generate a plurality of digested animal feed samples, wherein each of the plurality of digested animal feed samples comprises at least one residual component, wherein the at least one residual component is selected from the group consisting of protein, phosphorous, fat, gross energy, and carbohydrates, wherein the samples of animal feed consist of swine feed or poultry feed, wherein each animal feed composition comprises one or more of corn, soybean, grain(s), distiller grain(s), legumes, molasses, or a mixture of any thereof, wherein the digesting in vitro comprises at least two phases:

wherein for swine feed an in vitro digestion phase is conducted for 1 to 6 hours at a pH of less than about 7 and includes use of at least one enzyme comprising pepsin, and wherein another in vitro digestion phase is conducted for 18 hours to 48 hours at neutral pH to an acidic pH of at least 6.0 and includes use of at least one enzyme comprising pancreatin, to generate the plurality of digested animal feed samples,

wherein for poultry feed, an in vitro digestion phase is conducted that includes use of at least one enzyme comprising phytase, another in vitro digestion phase is conducted at a pH of less than about 7 for 30 minutes to 2 hours and includes use of at least one enzyme comprising pepsin, and an additional in vitro digestion phase is conducted at neutral pH to an acidic pH of at least 6.0 for 30 minutes to 2 hours and includes use of at least one enzyme comprising pancreatin, to generate the plurality of digested animal feed samples;

(b) separating each of the plurality of digested animal feed samples obtained in step (a) into a solid component and a liquid component;

(c) scanning the solid component of each of the plurality of digested animal feed samples obtained in step (b) using a near infrared (NIR) spectrophotometer to generate spectral data for each of the plurality of digested animal feed samples;

(d) determining the concentration of the at least one residual component in each of the plurality of digested animal feed samples using a wet chemistry method;

(e) generating a computer model comprising a computer implemented method comprising steps of:

i) receiving spectral data for each of the plurality of digested animal feed samples;

ii) relating the spectral data for each of the plurality of digested animal feed samples to the concentration of the at least one residual component in a corresponding sample of the plurality of digested animal feed samples; and

iii) establishing a predictive relationship based on the spectral data and the concentration of the at least one residual component of the plurality of digested animal feed samples to generate the computer model; and

(f) validating the computer model for analyzing feed for swine or poultry using validation samples, wherein the validation samples comprise a plurality of different samples of the animal feed that are different from the samples used in step (a), comprising comparing a concentration of at least one residual component in each of a plurality of digested samples obtained from the different samples of the animal feed that is predicted from the computer model to a corresponding measured concentration determined by wet chemistry for the at least one residual component in each of the plurality of digested samples obtained from the different samples of the animal feed.

2. The method of claim 1 , wherein the step of scanning the solid component of each of the plurality of digested feed samples further comprises the step of mathematically manipulating the spectral data of each of the plurality of digested animal feed samples.

3. The method of claim 1 , wherein the wet chemistry method comprises analyzing each sample of the digested feed for the concentration of the at least one residual component selected from the group consisting of protein, phosphorous, fat, gross energy, and carbohydrates.

4. The method of claim 1 , wherein each of the samples of animal feed is swine feed.

5. The method of claim 4 , wherein the pepsin is porcine pepsin and the pancreatin is porcine pancreatin.

6. The method of claim 4 , wherein the animal composition comprises corn.

7. The method of claim 4 , wherein the digestion phase and the other digestion phase further include use of an acetate buffer.

8. The method of claim 1 , wherein each of the samples of animal feed is poultry feed.

9. The method of claim 8 , wherein the animal composition comprises corn.

10. The method of claim 1 , wherein the at least one residual component is selected from the group consisting of protein, phosphorous, fat, and gross energy.

11. The method of claim 1 , wherein the at least one residual component is selected from the group consisting of protein, fat, and gross energy.

12. The method of claim 1 , wherein the validating in step (f) comprises:

(1) digesting in vitro the plurality of different samples of the animal feed wherein digesting comprises two phases, wherein a phase is conducted at a pH of less than about 7 and includes use of at least one enzyme comprising pepsin, and wherein another phase is conducted at a neutral to acidic pH and includes at least one enzyme comprising pancreatin;

(2) separating each of the plurality of digested different samples of animal feed obtained in step (1) into a solid component and a liquid component;

(3) scanning the solid component obtained in step (2) of the plurality of digested different samples of animal feed using a near infrared (NIR) spectrophotometer to generate spectral data for each of the plurality of digested different samples of animal feed;

(4) predicting the concentration of the at least one residual component in each of the plurality of digested different samples of animal feed using the computer model to obtain predicted concentrations thereof;

(5) determining the concentration of the at least one residual component in each of the plurality of digested different samples of animal feed using a wet chemistry method to obtain measured concentrations thereof; and

(6) comparing the predicted concentration of the at least one residual component in each of the plurality of digested different samples of animal feed to a corresponding measured concentration determined by the wet chemistry in making a validation determination on the computer model.

13. The method of claim 12 , wherein the separating in step (2) comprises centrifuging or filtering.

14. The method of claim 1 , further comprising:

(g) determining a coefficient of determination, R 2 value, of the computer model based on comparing a plurality of concentrations predicted for a plurality of validation samples using the computer model with actual concentrations of the validation samples determined by wet chemistry, and

(h) determining if the computer model is validated for analyzing feed for swine or poultry by determining if the R 2 value determined in step (g) is at least 50.

15. The method of claim 14 , wherein the determining in step (h) if the computer model is validated for analyzing feed for swine or poultry comprises determining if the R 2 value determined in step (g) is at least 70.

16. The method of claim 1 , wherein the separating in step (b) comprises centrifuging or filtering.

17. The method of claim 16 , further comprising freeze-drying the solid component obtained from the separating in step (b) to provide a final dry matter portion thereof prior to step (c), and wherein the solid component scanned in step (c) comprises the final dry matter portion thereof.

18. The method of claim 16 , wherein the determining using wet chemistry in step (d) is performed on the solid component of each of the plurality of digested animal feed samples.