Muu App Nutrition LLC was established in 2021 by a team comprising experts in animal nutrition and programming professionals. Their collective objective was to provide a practical tool for addressing feeding challenges in various species.
“Those who are crazy enough to think they can change the world are the ones who do” – Steve Jobs.
The global population has experienced significant growth over the past two centuries, and although the rate is slowing down, it is projected to surpass 9 trillion by 2050 (4, 5, 7). World hunger remains a pressing issue, with an estimated 690 million people experiencing hunger in 2019, accounting for 8.9% of the global population before the Covid-19 pandemic (6). Efforts to address this problem include the UN’s Zero Hunger project, which emphasizes the importance of promoting food security while also considering environmental sustainability and reducing greenhouse gas emissions (6).
The increased consumption of meat and dairy products is driven not only by population growth but also by changing dietary patterns, particularly among the emerging middle classes in various countries. This trend is expected to continue without a foreseeable slowdown. Additionally, the decline in arable land poses a further challenge, as future food production will need to increase despite limited land availability, even potentially on smaller areas (7, 8).
According to the FAO, the global demand for milk and dairy is projected to increase by 74% by 2050, while the demand for meat is expected to increase by 58%. A significant portion of this demand will originate from developing countries (21). However, imbalanced feeding practices in many developing countries contribute to lower productivity in farm animals. It is well-documented that imbalanced nutrition negatively affects animal productivity and can lead to health-related issues (21).
A case study conducted in India (21) provides evidence of the impact of balanced nutrition on milk yield. Initially, an imbalanced ration resulted in an average milk yield of 7.51 kg/day, which increased to 9.26 kg/day after implementing a balanced ration. Not only did the milk yield increase, but the economic implications were also positive. The study reported that the overall cost of the ration per day increased by 20% compared to the baseline cost (P < 0.05). However, the net daily profit improved from 104.46 INR/day to 135.80 INR/day, representing a 30% improvement.
This 30% increase in net daily profit resulting from the shift from an imbalanced ration to a balanced one is significant for developing countries. It not only translates into more income but also has broader implications for global food production, emissions reduction, and nutrient efficiency, leading to a more sustainable agricultural system.
Balancing the ration of animals nutritionally not only leads to an increase in daily milk yield and/or milk fat level but also improves the profitability of farms. In many cases, it can reduce the cost of feeding per kilogram of milk production. Furthermore, balanced feeding practices contribute to the reduction of CH4 emissions per kilogram of milk, minimize nitrogen content in manure, enhance immunity, and decrease the incidence of parasitism (1, 2, 3, 13, 20).
Efficiency is crucial for both economic benefit and sustainable production, particularly unless there is a reversal in the consumption patterns of animal protein (9).
The global food systems suffer from significant losses and inefficiencies, and reversing this trend will require the acquisition and application of new knowledge on a large scale (12).
Human aversion to risk and loss is a common trait (14, 15, 16). When implementing new technologies, two central factors must be considered: the risk associated with trying something new for primary producers and the availability of information during the learning process. While innovations introduce uncertainty, access to information regarding the capabilities and profitability of new technologies plays a vital role. Adoption of a new technology depends on its perceived net benefits. Thus, the dissemination of knowledge related to the innovation and its user-friendliness are crucial, provided that users have access to this information and the ability to learn (10, 11).
For creators and disseminators of new knowledge, it is not enough to generate wisdom; its dissemination is essential. Knowledge that remains unshared is non-existent, and individuals with fewer resources have limited opportunities to access it. In this regard, digital technologies play and will continue to play a central role in disseminating and utilizing scientific knowledge. The current landscape presents a great opportunity, with 3.9 billion people having smartphones and data connections at their disposal (22). Breaking down the barriers of information inequality and reaching areas where production efficiency can make a significant impact is crucial, unless we accept its decline (18, 19).
These topics will inevitably be subject to discussions, and governments will assume responsibility for addressing them. In fact, many progressive nations have already taken action (17, 1, 22).
The purpose of this publication is not to provide a romantic or critical analysis of current events but to present a tool that empowers individuals to initiate change in the world, with the sole requirement of owning a smartphone and having the intention to make a difference.
Basic bibliography Muu App Nutrition Cattle
– Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001.
– Nutrient Requirements of Beef Cattle: Seventh Revised Edition: Update 2000
– Using ADF and NDF in dairy cattle diet formulation-a western Canadian perspective Karen A. Beauchemin.
– Evaluation of the Importance of the Digestibility of Neutral Detergent Fiber from Forage: Effects on Dry Matter Intake and Milk Yield of Dairy Cows. M. OBA and M. S. ALLEN Department of Animal Science, Michigan State University.
– Effect of cereal grain type and corn grain harvesting and processing methods on intake, digestion, and milk production by dairy cows through a meta-analysis L. F. Ferraretto , P. M. Crump and R. D. Shaver
– Balancing diets for physically effective fibre and ruminally degradable starch: A key to lower the risk of sub-acute rumen acidosis and improve productivity of dairy cattle. Q. Zebeli D. Mansmann a,b , H. Steingass, B.N. Ametaj
– Effects of rumen undegradable protein supplementation on productive performance and indicators of protein and energy metabolism in Holstein fresh cows. H. Amanlou, T. Amirabadi Farahani and N. Eslamian Farsuni.
– Optimizing Starch Concentrations in Dairy Rations. Rick Grant.
– Starch in ruminant diets: a review. Luis M Gómez, MVZ, MSc, Dr. Sc; Sandra L Posada, Zoot, MSc, Dr. Sc; Martha Olivera, MV, Dr. Sc.
– Creating a System for Meeting the Fiber Requirements of Dairy Cows. D. R. MERTENS US Dairy Forage Research Center, USDA-Agricultural Research Service, Madison.
– Dietary Forage Concentration Affects the Feed Sorting Behavior of Lactating Dairy Cows. T. J. DeVries,K. A. Beauchemin and M. A. G. von Keyserlingk
– Rumen Acid Load from Feed and Forage Particle Size on Ruminal pH and Dry Matter Intake in the Lactating Dairy Cow. B. Rustomo, O. AlZahal, N. E. Odongo, T. F. Duffield, and B. W. McBride.
– Increasing the Physically Effective Fiber Content of Dairy Cow Diets May Lower Efficiency of Feed Use. W. Z. Yang and K. A. Beauchemin.
– Effect of cereal grain type and corn grain harvesting and processing methods on intake, digestion, and milk production by dairy cows through a meta-analysis. L. F. Ferraretto , P. M. Crump and R. D. Shaver.
– Update on Trace Mineral Requirements for Dairy Cattle. Bill Weiss. Department of Animal Sciences Ohio Agricultural Research and Development Center The Ohio State University.
– Investigations on the water intake of lactating dairy cows. Ulrich Meyer, Matthias Everinghoff, Dieter Ga¨deken, Gerhard Flachowsky.
– Methane Emissions from Cattle K. A. Johnson and D. E. Johnson. Departments of Animal Science, Washington State University.
– Methane Production in Dairy Cows. P.W. MOE and H. F. TYRRELL. US Department of Agriculture Science and Education Administration Agricultural Research Animal Science Institute.
– Animal and Dietary Factors Affecting Feed Intake During the Prefresh Transition Period in Holsteins A. Hayirli, R. R. Grummer, E. V. Nordheim, and P. M. Crump.
– Nutritional Management of Transition Dairy Cows: Strategies to Optimize Metabolic Health, T. R. Overton and M. R. Waldron.
– A herd health approach to dairy cow nutrition and production diseases of the transition cow F.J. Mulligan a, L. O’Grady a, D.A. Rice b, M.L. Doherty.
– A snapshot of management practices and nutritional recommendations used by feedlot nutritionists in Brazil D. D. Millen, R. D. L. Pacheco, M. D. B. Arrigoni, M. L. Galyean, and J. T. Vasconcelos.
– Nutritional recommendations of feedlot consulting nutritionists: The 2015 New Mexico State and Texas Tech University survey K. L. Samuelson, M. E. Hubbert, M. L. Galyean, and C. A. Löest.
– Nutritional recommendations of feedlot consulting nutritionists: The 2007 Texas Tech University survey J. T. Vasconcelos and M. L. Galyean.
– Review of Some Aspects of Growth and Development of Feedlot Cattle. Fredric N. Owens, Donald R. Gill, David S. Secrist and S. W. Coleman. – Effects of Rumen Acid Load from Feed and Forage Particle Size on Ruminal pH and Dry Matter Intake in the Lactating Dairy Cow. B. Rustomo, O. AlZahal, N. E. Odongo, T. F. Duffield and B. W. McBride.
Food energy formula:
All food energy calculations are resolved at X1 consumption and in mega calories of metabolic energy per kilogram of dry matter. The discount on X maintenance and net energy are calculated and applied in the formulation process of the final total ration.
Pastures and forages: in vitro digestibility of dry matter * 3.61. => Dig in vitro = ((88.9-((FDA100)0.779)))/100
Energy concentrates: University of Pennsylvania equation for energy concentrates.
Protein concentrates, pre mix and bulky feeds: Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001 and Nutrient Requirements of Beef Cattle: Seventh Revised Edition: Update 2000
Food database:
Tables of chemical composition of feeds for ruminants. INTA, Argentina.
Nutrient Requirements of Beef Cattle: Eighth Revised Edition 2016.
www.feedipedia.org
Basic bibliography Muu App Nutrition Pets
– Nutrient Requirements of Dogs and Cats, National Research Council 2006
-Nutrient Requirements of Dogs, National Research Council 1974.
-Nutrient Requirements of Dogs, National Research Council 1985.
-Nutrient Requirements of Cats, National Research Council 1986.
-Adaptation to different calcium intakes in dogs: Stanley N. Gershoff, M. A. Legg and D. M. Hegsted.
-Calcium Intake and Health Gabriela Cormick and Jose M Belizán
Food database:
https://fdc.nal.usda.gov/
Basic bibliography Muu App Nutrition Livestock (swine and poultry)
Purpose Bibliography
*1- Effects of feeding nutritionally balanced rations on animal productivity, feed conversion efficiency, feed nitrogen use efficiency, rumen microbial protein supply, parasitic load, immunity and enteric methane emissions of milking animals under field conditions. M.R. Garga, P.L. Sherasiaa, B.M. Bhanderi, B.T. Phondbaa, S.K. Shelkea, H.P.S. Makkar.
*2 – Biuret versus urea and cottonseed meal for wintering and finishing steers – R. R. Oltjen, W. C. Burns and C. B. Ammerman.
*3- Methane Emissions from Cattle – K. A. Johnson and D. E. Johnson.
4* Human population growth and the demographic transition John Bongaarts The Population Council, One Dag Hammarskjold Plaza, New York, NY 10017, USA.
5*- World population stabilization unlikely this century Patrick Gerland, Adrian E. Raftery, Hana Ševčíková, Nan Li, Danan Gu, Thomas Spoorenberg, Leontine Alkema, Bailey K. Fosdick, Jennifer Chunn, Nevena Lalic, Guiomar Bay, Thomas Buettner, Gerhard K. Heilig, John Wilmoth.
6* – https://www.un.org/en/global-issues/food
7* – http://www.fao.org/faostat/en/#compare
8* – World meat consumption patterns: An overview of the last fifty years (1961–2011) P. Sans, P. Combris.
9* The Sustainability Challenges of Our Meat and Dairy Diets Susanne Stoll-Kleemann & Tim O’Riordan
10* Uncertainty, Learning, and Technology Adoption in Agriculture Jean-Paul Chavas, and Céline Nauges
11* Learning from Six Reasons Why Farmers Do Not Adopt Innovations Intended to Improve Sustainability of Upland Agriculture Sam Fujisaka.
12* Losses, inefficiencies and waste in the global food system Peter Alexander, Calum Brown , Almut Arneth , John Finnigan, Dominic Moran, Mark D.A. Rounsevell.
13* Nutrition Management of Dairy Cows as a Contribution to Pollution Control s. TAMMINGA.
14* Anomalies Risk Aversion Matthew Rabin and Richard H. Thaler
15* The effect of myopia and loss aversion on risk taking: an experimental test richard h. Thaler amos tversky daniel kahneman alan schwartz.
16* Misbehaving: The Making of Behavioral Economics – Richard H. Thaler.
17* The Role of Regional Governments in Climate Change Policy Ibon Galarraga, Mikel Gonzalez‐Eguino and Anil Markandya.
18* Multiplying Inequalities: The Effects of Race, Social Class, and Tracking on Opportunities to Learn Mathematics and Science. Oakes, Jeannie; And Others
19* Facilitating agricultural technology adoption among the poor: The role of service delivery through mobile phones – Heike Baumüller.
20* Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001.
21* Feeding balanced ration can improve the productivity and economics of milk production in dairy cattle: a comprehensive field study Asgar Ud Deen, Nitin Tyagi, Ram Dav Yadav, Sachin Kumar, A. K. Tyagi & Sunil Kumar Singh.
22* https://yiminshum.com/mobile-movil-app-2020/
