1. Evaluation of beef cow-calf nutrition in Yucatan, Mexico: MS thesis progress report Animal Science Kotaro Baba January 2006

2. Situation Beef cattle farming is the main industry in Tizimín beef production systems in Yucatan are constrained by: –Declining forage quality as the forage production system progresses – Low quality and amount in the dry season –Long calving intervals and percentage of cows calving each year

3. Thesis objectives Predict nutrient balances during each stage of the reproductive cycle with forages available during each stage of the annual forage production cycle. Use this information to: –Identify weak links and their effect on the calving interval –Identify cost effective management strategies that can shorten the calving interval

4. Procedures Use panel of experts to describe current situation –Describe each group in the beef herd –Describe forage composition available during each season of the year Predict nutrient balances for each group in the herd when consuming forages available during each forage growth season

7. Forage growth periods

8. Grasses grazed by forage growth periods Season 1 grass ( June 1- July 31) Season 2 grass ( August 1-September 30) Season 3 grass ( October 1- January 30) Season 4 grass ( February 1-May 31)

9. Representative farms Farm 1: Calving on June 1 Farm 2: Calving on August 1 Farm 3: Calving on October 1 Farm 4: Calving on February 1 Physiological stages -Early lactation -Mid-late lactation -Early dry -Late Dry Parity and age - 1 st lactation cows - 2 nd lactation cows -Mature cows -heifers

10. Inputs for the CNCPS SBW -1 st =400 kg -2 nd =460 kg -Mature=500 kg Calf BW -male 33 kg -female 30 kg Weaning weight -male 210 kg (dry season) -female 180 kg (dry) - male 220 kg (rainy) - female 220 kg (rainy)

11. Inputs for the CNCPS Milk production early lactation -1 st= 4 kg -2 nd =4.5 kg -mature=5kg Mid late lactation -1 st =3 kg -2 nd=3.3 kg -Mature 3.7 kg Milk fat=4 % Milk CP=3.5 % True protein=3.3 % CI -1 st (rainy) 460 days -1 st (dry) 500 days -The others 420 days

12. BCS change in the rainy season Rainy season parity calving early lactation Mid-late lactationEarly drylate dry 1st 76456 2nd 65457 ≧3≧3 87667

13. BCS change in the dry season Dry season parity calving early lactation Mid-late lactationEarly drylate dry 1st 63.5345 2nd 54346 ≧3≧3 75456

14. Rations for simulations Rations -season of the year and physiological period. Example, Early lactation period =90 days Farm 1 (calving on June 1) The ration ; 60 days(June1-July 31 with season 1 grass): 30 days( August 1- August 31, season 2 grass)=2:1, (6 kg:3 kg for example)

15. Simulation 1: grazed grass composition based on CNCPS feed library

16. Predicted composition of forages grazed during each of 4 growth periods Assume forage quality progressively declines from beginning of growth in rainy season (season 1) to accumulated forage grazed in the dry season (season 4). Used CNCPS feed library to estimate composition of forage grazed during each season.

17. Estimated composition of grazed forage during each of 4 seasons 1 Forage CP % of DM NDF % in DM Lignin % in NDF Ash % in DM NDF rate %/hr Ether extract % in DM Season 1 grass 967612.78.63 Season 2 grass 8727126.82.6 Season 3 grass 774811.54.22.2 Season 4 grass 57791131.6 1 Based on CNCPS Feed Library

18. Simulation 1: early lactation with Grasss 1 and 2 Early lactation Mature with season 1 grass Inputed DMI9.94 kg Predicted DMI9.94 kg Inputed Milk5 kg ME allowable Milk6.1 kg MP allowable Milk5.7 kg ME Balance 0.33 Mcal MP Balance-6.82 g Day to BCS change694 days Early lactation Mature with season 2 grass Inputed DMI9.46 kg Predicted DMI9.46kg Inputed Milk5 kg ME allowable Milk2.9kg MP allowable Milk3.9 kg ME Balance -3.27 Mcal MP Balance-112g Day to BCS change 0

19. Simulation 1: early lactation with Grasses 3 and 4 Early lactation Mature with season 3 grass Inputed DMI7.37 kg Predicted DMI7.37 kg Inputed Milk5 kg ME allowable Milk-3.9kg MP allowable Milk0.1 kg ME Balance -11.06 Mcal MP Balance-331 g Day to BCS change0 days Early lactation Mature with season 4 grass Inputed DMI5.46 kg Predicted DMI5.46 kg Inputed Milk5 kg ME allowable Milk-10.7kg MP allowable Milk-1.5 kg ME Balance -18.87 Mcal MP Balance-427g Day to BCS change 0

20. Farm 1; Mature lactating cows calving on June 1 Early lactation (June 1- August 31); consuming grasses 1and 2 in ratio of 2:1 Grass1 :Grass 2 =6.5 kg:3.25 kg Inputed DMI9.75 kg Predicted DMI9.76 kg Inputed Milk5 kg ME allowable Milk5 kg MP allowable Milk5 kg ME Balance -0.91 Mcal MP Balance -44.3 g Mid-late lactation (Sep 1-January 31); consuming grasses 2 and 3 in ratio of 1:4 Grass 2 :Gras s 3 =(1.57 kg):(6. 28 kg) Inputed DMI7.85 kg Predicted DMI7.85 kg Inputed Milk3.7 kg ME allowable Milk-2.7 kg MP allowable Milk0.7 kg ME Balance -6.28 Mcal MP Balance -126 g

21. Farm 1; Mature lactation cows calving on June 1 Farm 1 early dry mature cows (Feb 1-April 30); consuming grass 4, 100% Grass 4 (100%)= 6.83 kg Inputed DMI6.83 kg Predicted DMI6.83 kg --- ME Balance -14.41 Mcal MP Balance -193 g Farm 1 late dry mature cows (May 1-July 31); consuming grasses 4 and 1in ratio of 1:2 Grass 4 :Grass 1 =3.375 kg:6.75 kg Inputed DMI10.125 kg Predicted DMI10.192 kg --- ME Balance-3.77 Mcal MP Balance

23. Conclusions: simulation 1 Negative energy balance through the entire calving interval; does not agree with observations of panel of experts. i) assumptions on milk amount and composition? ii) Do cows eat more than the predicted intake by the CNCPS? iii) Forage composition assumed.

24. Simulation 2: grazed grass composition based on data collected by Juarez at Veracruz and Rueda in Western Brazil

25. Predicted composition of grazed forages: simulation 2 Assume forage quality progressively declines from beginning of growth in rainy season (season 1) to accumulated forage grazed in the dry season (season 4). Used data from Mexico Gulf Coast (Juarez et al.) and Brazil Amazon region (Rueda et al.) to estimate composition of forage grazed during each season.

26. NDFLigninCP NDF rate, %/hour Rainiest71.75.67.86.6 Less rainy 68.66.18.16.6 mean70.155.857.956.6 Composition of grass grazed, Brazil Amazon region 1 1 Rueda et al., J. Animal Science 81:2923-2937.

27. Grass composition, Gulf of Mexico 1 NDF % of DM LIGNIN % of NDF CP % of DM NDF rate, %/hour 66.85.69.47.3 70.65.97.87.2 74.27.57.05.1 1 Juarez et al., J. Dairy Science 82:2136-2145. Averaged by 3 NDF ranges; 64-69, 70-72, and 73-75

28. Simulation 2 forage composition assumptions Forage CP % in DM NDF % in DM Lignin % in NDF Ash % in DM CHOB3 Kd %/hr Fat (Ether extract) (%DM) Season 1 grass 9675.512.78.63 Season 2 grass 8706126.82.6 Season 3 grass 8716.511.56.22.2 Season 4 grass 7737114.41.6

29. Simulation 2 (grasses one and two) Early lactation Mature with season 1 grass Inputted DMI 10.00 kg Predicted DMI 10 kg Inputted Milk 5 kg ME allowable Milk 6.5 kg MP allowable Milk 5.9 kg ME Balance 0.77 Mcal MP Balance 8.2 g Day to BCS change 297 days Early lactation Mature with season 2 grass Inputted DMI 9.59 kg Predicted DMI 9.6 kg Inputted Milk 5 kg ME allowable Milk 3.9 kg MP allowable Milk 4.2 kg ME Balance ‘-2.11 Mcal MP Balance -91 g Day to BCS change ---

30. Simulation 2 (grass three and four) Early lactation Mature with season 3 grass Inputted DMI 9.47 kg Predicted DMI 9.47 kg Inputted Milk 5 kg ME allowable Milk 3 kg MP allowable Milk 3.3 kg ME Balance -3.17 Mcal MP Balance -146 g Day to BCS change --- Early lactation Mature with season 4 grass Inputted DMI 8.08 kg Predicted DMI 8.08kg Inputted Milk 5 kg ME allowable Milk -1.8 kg MP allowable Milk 1.1 kg ME Balance -8.65Mcal MP Balance -275 g Day to BCS change ---

31. Simulation 2 (Farm 1; Lactating mature cows that calved on June 1) Early lactation (June 1- August 31); consuming grasses 1and 2 in ratio of 2:1 Grass1 : Grass 2 =6.58 kg:3.29k g Inputed DMI9.87 kg Predicted DMI9.87 kg Inputed Milk5 kg ME allowable Milk5.7 kg MP allowable Milk5.4 kg ME Balance-0.15 Mcal Day to BCS change0 days Mid-late lactation (Sep 1-January 31); grasses 2 and 3 in ratio of 1:4 Grass2 : Grass3= (1.897kg): 7.59kg) Inputed DMI9.487 kg Predicted DMI9.491 kg Inputed Milk3.7 kg ME allowable Milk2.9 kg MP allowable Milk3.4 kg ME Balance0.1 Mcal Day to BCS change2317 days

32. Simulation 2 (Farm 1; early and late dry Mature cows that calved on June 1) Farm 1 early dry mature cows (Feb 1-April 30) consuming grass 4, 100% Grass 4 (100%)=9. 17 kg Inputed DMI9.17 kg Predicted DMI9.174 kg --- ME allowable gain0 MP allowable gainN-A-N ME Balance -4.19 Mcal Day to BCS change0 Farm 1 late dry mature cows (May 1-July 31) consuming grasses 4 and 1 in ratio of 1:2 Grass 4 :Grass 1 =3.43 kg:6.86 kg Inputed DMI10.29 kg Predicted DMI10.31 kg --- ME allowable gain0.01 MP allowable gainInfinity ME Balance-1.58 Mcal Day to BCS change7356 days

38. Effect of body condition score on conception BCS 4.5-5 is needed for mature cows, 6 for heifers at calving, for conception (Herd et al, 1995 Randel, 1990) Need BCS inputs for Farm 1 and 3 simulations whose calving time is in the beginning of the dry season.

39. Conclusions. The CNCPS simulations are very sensitive to forage chemical composition (Juarez et al. J. Dairy Science) Farm 1 (Calving on June) looks closer to average of zero energy balance for the reproductive cycle than that of Farm 4(Calving on February 4) Farm 4 has two energy balance nadirs

40. Conclusions about forage composition for accurate simulation Need actual values for forage consumed. Grass samples need to represent what cows are observed to select. Need samples for each month of year. Analysis should include NDF, lignin, CP, and available NDF digestion rate.

41. Goals for shortening the CI Reach nadir as soon as possible after calving. Have cows in optimum BCS at calving. Need to achieve zero energy balance over the reproductive cycle.