Energy and protein gap analysis in dairy cows kept under fodder based diet with cut and carry feeding system

Published: 13 March 2024| Version 2 | DOI: 10.17632/jh4cjm4ftw.2
Olive Umunezero


Study hypothesis: There is a gap in dry matter, water, energy and protein intake of dairy cows kept in fodder- based diet under cut and carry feeding system in Sub- Saharan countries, Rwanda included. A study was done in small holder dairy farmers and 111 lactating dairy cows were used for observational data. Parameters analyzed included nutritive value of offered fodder, which was 25% of dry matter, 58% neutral detergent fibre, 9% crude protein and of 5.6 mega joules per kg DM. Mean land size was 0.5ha, area for fodder was 0.1ha, number of cattle was 1.7, mean body weight of cows was 430kg, days in milk was 145; cow age was 7 and parity was 3. Data on feeds characterization were computed with Groot et al., models while data for the production requirement of dairy cows under lactation were computed using LIGAPS dairy models. Statistical analysis was conducted using the SPSS Statistical package for social sciences (SPSS) version 26.0 (George and Malley, 2019). After testing the normality of data, data were grouped. Grouping variables were lowlands and highlands regions, breed types and lactation periods. Test between groups was done by means comparisons and their variances were tested using one way analysis of variance test. Means were significantly different at P<0.05. Tested variables were dry matter intake, dry matter requirement, dry matter gap, body weight, metabolically weight, water intake, water requirement, water gap; milk yield, attainable milk, milk yield gap, protein intake, protein requirement, protein gap; energy intake, energy requirement, energy gap. Results showed that daily intake was 9kg DM; 35 liters of water; 898gr of crude protein and 55 MJ ME with current milk production of 6kg. The daily requirement for both maintenance and 16 kg milk production were 15kg DM: 56 liters of water, 1908 g CP and 137 MJ. The daily gap was 4.52kg DM, 22litres of water, 1109 gr of crude protein and 84 mega joules ME with 10 kg gap in milk yield per day. Results from this analysis will serve as instruments for researchers in developing dairy diet models to improve dairy cow productivity at household level. Demonstrating the gap of available feeds resources would trigger the uptake of new feeding technologies by farmers. Extension agents should focus in knowledge transfer on optimal harvesting time of existing fodder when their nutritive value content is optimal. For dairy feeds manufacturers, this would serve as a guide for proper rationing of high concentrates ingredients rich in energy and protein in consideration of their requirements. Policy makers need to facilitate farmers to have access to facilities for upgrading the available low-quality roughages to enhance their energy and protein content. Adopting best feeding management based on enhanced energy, protein and water intake would contribute to improved milk production resulting to better remuneration to farmers, increased national milk pool and per capita milk consumption.


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Samples were analyzed for dry matter (DM) content at 60oC for 3 days. Protein was analyzed by Kjeldhal method (AOAC, 2023). Neutral detergent fibre (NDF) was determined using ANKOM fibre bags F57, 25 micro porosities where samples were rinsed using neutral detergent solution (NDS) for two hours. For digestibility attributes, mixed ingredients samples of approximately 2gr each were transferred to an airtight graduated gas syringe. Inoculum was prepared according to modified procedure of Tilley and Terry by mixing different rumen liquor from slaughterhouse (Mutimura et al., 2013). A buffer solution was prepared identical to cattle saliva according to Jayanegara et al., (2019). It was mixed with rumen liquor at 2:1 volume. A diffusion of carbon dioxide (CO2) was thoroughly connected to the system to maintain the anaerobic fermentation. Approximately 100 ml of the mixture was mixed with the samples previously placed in syringes using a lab revolver (AOAC, 2023). The syringes were transferred in an oven set at 39oC similar to rumen conditions for 24 hours according to Jayanegara et al., (2019). Me in feeds was computed by Groot et al. (2016) where ME in feeds (MJ/kg DM) = 2.2 + 0.136 G24 + 0.057CP + 0.0029CP^CP. dry matter intake of feeds per body weight=120/NDF x BW/100 DMI requirement=BW x 3.5/100. FWI =12.3+2.15xDMIR+0.73 x PM. Where FWI=free water intake; DMIR: dry matter intake requirement and PM: Potential milk. Water intake gap=FWI-current water intake ME in feeds (MJ/kg DM) = 2.2 + 0.136 G24 + 0.057CP + 0.0029CP2. Equation (1). Where GV24 = gas volume generated after 24 h of substrate incubation. Required ME for both maintenance and production was estimated according to LIGAPs-dairy model by Van der Linden et al. (2021) where 0.589 MJ per kg metabolic weight is required for maintenance, and 5.023 MJ are required per kg milk. Metabolizable energy intake=ME in feeds x DMI. Energy maintenance = BW0.75 x 0.589. Where BW=body weight; BW0.75= is the metabolically weight; DMI=dry matter intake Energy for attainable milk=5.023 x attainable milk. Total energy for production=energy for maintenance + energy for attainable milk. Energy intake gaps was obtained by subtracting their daily intake from the requirements values. Therefore, Gap Energy= Energy Requirement-Energy intake CP in feeds (gr/kg) = % CP x 1000/100. CP intake=CP in feeds x DMI. Where DMI=dry matter intake. Required protein for both maintenance and production was estimated according to LIGAPs-dairy model by Van der Linden et al. (2021). In the model, 6.27g CP per kg metabolic weight is required for maintenance and 82g CP is required per kg milk. Therefore, CP requirement for maintenance = 6.23 x MW. Where; MW= metabolically weight; CP requirement for attainable milk=82g x attainable milk; Total CP requirement for production=CP maintenance + CP attainable milk. Gap CP= Total CP required for attainable milk production - CP intake


Dairy Cattle Nutrition


This material is based on work supported by the United States Agency for International Development(USAID), as part of the Feed the Future initiative, under the CGIAR Fund, award number BFS-G-11-00002,

award number EEM-G-00-04-00013.