livestock

NUTBAL: Livestock nutrition balance decision support system

gabe.saldana · April 25, 2022 ·

NUTBAL: Livestock nutrition balance decision support system

A decision support system that monitors animal diet nutrient concentrations for diet optimization toward producer goals

Animal nutrition-based decision making

NUTBAL’s primary purpose is to provide the livestock industry with the means to monitor the nutrient concentration in the animal’s diet and determine if the current diet is sufficient to meet performance goals set by the producer. NUTBAL is a decision support system that models the crude protein and net energy status of cattle. This computerized decision aid lets the user their herd, environmental conditions, and establish weight performance targets. This information is then coupled with results from a near-infrared reflectance spectroscopy, or NIRS fecal analysis, by scientists at the Grazingland Animal Nutrition Laboratory (GAN Lab). From this, the lab produces an animal performance report and the least-cost nutrition management plan.

NIRS/NUTBAL Reports include the following information:

plane of nutrition
weight gain or loss
the nutrient most limiting animal performance
least cost feeding solution
amount of feed and forage consumed

Go To NUTBAL Online

Fecal sample submission and services

Learn more about the GANLAB

Learn more about NIRS

Unlike many nutritional balance packages geared toward pen-fed animals, NUTBAL calculates what animals will consume ad libitum under grazing conditions. In many cases, voluntary intake of ruminants in free-ranging conditions differs from that predicted by published equations.

Applications

As part of the NIRS/NUTBAL system, NUTBAL is an effective nutritional monitoring tool designed for ranchers and other free-grazing managers. The system generates valuable information that enables the user to make informed and timely decisions regarding animal nutrition and grazing management. Private enterprise applications of the NIRS/NUTBAL system are varied and can be custom designed to meet the goals of the individual user. Most private users employ NUTBAL to assist in one or a combination of:

Improving body condition more economically
Managing weight loss during drought or dormant forage periods
Maintaining desired body condition during critical periods to enhance productivity
Enhancing effectiveness of supplement feeding by identifying when forage is inadequate, when forage quality recovers and how much feed is needed to meet goals

Various agencies and groups also use the NIRS/NUTBAL system as a research tool in developing guidelines for the public, collecting data, and facilitating environmental conservation, to name a few. Such programs include EQIP, CSP, and the Forage Quality & Animal Well-being Program.

Availability

Access to NUTBAL is available via the interactive website, NUTBAL online. The online application allows users to submit their information for NIRS analysis on a livestock fecal sample which is then mailed to the GAN Lab. Once the GAN Lab completes and records the sample’s NIR analysis, the interactive website automatically generates NUTBAL reports for the sample based on data entered by a user. The NUTBAL software is available in a metric unit of measure version as well as the English unit version.

Model Systems

The NUTBAL model uses a combination of published systems including the NRC’s 1984, 1987, 1996 basic nutrient requirements formulas, Fox et al. (1988) adjustments to the NRC equations, McCollum’s rumen degradable protein thresholds and DOM/CP ratio concepts and Moore and Kunkel’s concept of intake change rate and deviation of metabolizable energy due to associative effects in growing animals. Where NUTBAL deviates from other systems is in the application of a quasi-metabolic fill system to predict dry matter intake of the animal. This approach allows modeling of fecal output processes, which consider more than just the digestion process. Other factors are derived from literature review, expert opinion and unpublished data extrapolated from prior studies. Impacts of forage availability, appetite drive, and associative effects can be characterized in both fecal output as a proportion of fat-corrected body weight and metabolizability of ingested forage.

CNRIT Projects

NUTBAL and the NIRS/NUTBAL monitoring system are an important part of several CNRIT projects that include, East Africa LEWS, FRAMS, Mali Livestock, and Pastoralist Initiative, and Mongolia LEWS. While US-based projects tend to focus towards conservation or efficiency issues, international projects benefit from the ability to evaluate and project changes in animal well-being which can be closely followed by changes in the people’s well-being in a region.

Browse CNRIT Projects

Mali Livestock and Pastoralist Initiative

gabe.saldana · April 25, 2022 ·

Mali Livestock and Pastoralist Initiative

Access to technology, capacity building for a stronger livestock system in Mali

Mali livestock and pastoralist initiative logo

A mission to improve the Mali livestock system

USAID-Mali has identified an overall goal to “improve the productivity and income of the producers in Mali by enabling them to access technologies and build the capacity of all actors involved in the development of an extensive livestock system”. To meet this goal, USAID-Mali has outlined these specific objectives:

Promote the development of the extensive livestock sector,
Empower pastoralists and improve their capacity for risk management,
Create equitable livestock information and communication systems that provide monitoring and analysis technology to foster strategic partnerships between pastoral communities, markets, and policy,
Markets development and integration,
Build capacity of Mali to sustain the new techniques and technologies.

To meet this overall goal and the specific objectives, the Mali Livestock and Pastoralist Initiative project was initiated in 2008. The project is led by Texas AgriLife Research with US partners that include Syracuse University, University of Arizona, University of Wisconsin, and South Dakota State University. Government and educational partner organizations in Mali include Observatoire du Marche Agricole (OMA), Direction Nationale des Productions et des Industries Animales (DNPIA), Institut d’Economie Rurale (IER), and l’Institut Polytechnique Rural (IPR).

Mongolia LEWS: Livestock Early Warning System

gabe.saldana · April 25, 2022 ·

Mongolia LEWS: Livestock Early Warning System

Preparing pastoralists and decision-makers with critical, timely information in the face of drought

Early warning for livestock in Mongolia’s Gobi Region

Mongolia pastoralists and horses near lake

During the period from 1999 to 2002, Mongolia experienced a series of droughts and severe winters that lowered livestock numbers by approximately 30% countrywide. In the Gobi region, livestock mortality reached as much as 50% with many households losing entire herds. Due to these extreme losses of livestock and its impact on pastoral livelihoods, the USAID mission in Mongolia and the Global Livestock-CRSP (GL-CRSP) initiated the Gobi Forage program with the goal of transferring Livestock Early Warning System (LEWS) technology developed by the GL-CRSP in East Africa to Mongolia. The Livestock Early Warning System technology combines near real-time weather, computer modeling, and satellite imagery to monitor and forecast livestock forage conditions so that pastoralists and other decision-makers have needed information for timely decision making in the face of drought. Under the Gobi Forage program, three major activities have been conducted:

infusion of forage monitoring technology to assess regional forage quantity.
development of nutritional profiling technology to assess forage quality.
information delivery and outreach.

Implementing forage monitoring

Through the GL-CRSP program, Texas A&M University and Mercy Corps partnered to implement the forage monitoring technology in 8 aimags (provinces) that encompass the area where previous drought impacts were greatest. A series of 297 monitoring sites have been established across the region to provide inputs to the computer modeling and ground-truth data. Computer model simulations are developed for each monitoring site and are driven by climate data (rainfall and temperature) provided by the US National Oceanic and Atmospheric Administration (NOAA) to predict forage availability. This information is then combined with satellite greenness imagery (Normalized Difference Vegetation Index) provided by the National Aeronautics and Space Administration (NASA) to produce regional maps of forage production. These regional maps provide a spatial and temporal assessment of forage conditions and can highlight areas of significantly low forage availability. A sophisticated statistical forecasting technique is used to predict forage conditions for 60 days into the future. The current and forecast forage maps can be compared to long-term average maps to allow herders and decision makers to assess how bad or good conditions are compared to the average, and the level of risk they are willing to accept based on projected forage conditions. Map validation has indicated an overall accuracy level of 70% and successful identification of drought-stricken areas in the Dundgobi and Gobi Altai aimags in 2007.

Nutritional profiling with Near-Infrared Reflectance Spectroscopy, NIRS

The nutritional profiling technology has been implemented to allow near-real-time assessment of forage quality. Knowledge of forage quality is especially important in Mongolia given the short growing season and the extremely cold winter months that can lead to loss of body condition if animals have poor quality forages. The nutritional profiling technology uses Near-Infrared Reflectance Spectroscopy (NIRS) to scan the manure of livestock. These scans examine the reflectance of near-infrared wavelengths and compare them to wavelengths from known diets of livestock, therefore allowing a prediction to be made about the amount of protein and digestibility of the forage. This information can then be used in a computer model to determine whether the animal is losing or gaining weight and what forage or supplements can be fed to the animal to allow it to maintain weight or nurse offspring. As part of Gobi Forage, a laboratory has been established in Mongolia for conducting nutritional profiling and a mobile laboratory is being tested to allow this technology to be brought directly to herders. The NIRS technology is also being examined for several value-added analyses such as feedstuff quality, and cashmere and wool grading.

Information delivery successes

The Gobi Forage program has made significant progress in the information delivery and outreach for Gobi Forage products. Current, forecast and long-term deviation forage maps are produced bi-monthly and are distributed via http://www.mongolialews.net/ and email. The maps are also printed in color and mailed to soum (district) governments for local government use and for posting on the local government bulletin boards. Radio bulletins are produced weekly and reported on Mongolian National Public Radio. A recent survey in the region has indicated that the program has been exceedingly well received, with over 70% of herders having some degree of familiarity with Gobi Forage products. Almost half of the surveyed herders reported that they had used Gobi Forage information to guide livestock movements (51%), provide supplemental feed (49%) or change their rotational grazing strategy (40%). Almost one-third reported a net profit resulting from these actions. An overwhelming majority (93%) of government officials found Gobi Forage products to be very useful in advising herders on grazing management and livestock movement. One provincial governor described how the system helped him manage the influx of almost 50,000 herders and their families from a neighboring drought-stricken aimag and prevent conflict with local herders.

The future

The Gobi Forage program is now in the process of becoming institutionalized in Mongolia to incorporate the program within a national government research and extension agency. Discussions are also underway with the World Bank to acquire funding to maintain the current system and expand it to the entire country. The expansion of the program, as well as institutionalization in a Mongolian government agency, will build the foundation for long-term sustainability of the system and make these GL-CRSP forage monitoring technologies available to all Mongolians.

East Africa LEWS: Livestock Early Warning System

gabe.saldana · April 25, 2022 ·

East Africa LEWS: Livestock Early Warning System

Understanding and communicating the emergence of drought — allowing pastoral communities to cope with a rapidly changing environment

Striking a balance

The delicate balance between selecting and maintaining a stocking rate that meets the short-term economic goals needed for ranch or pastoral household survival versus one that sustains long-term livestock carrying capacity has long dominated the decision-making process of livestock producers worldwide. This process is driven by the level of human needs of the decision-maker in relation to the level of risk an individual is willing to undertake under any livelihood.

With emerging problems associated with the increasing population, erratic climatic patterns with a higher frequency of drought, limited marketing opportunities, changing land tenure patterns, rising social conflict, limited water supply, and greater incidences of disease transmission, the traditional coping strategies of farmers, ranchers and pastoralists have become inappropriate. More uncertainties require new innovations in characterizing, monitoring, analyzing and communicating the emergence of drought to allow pastoral communities to cope with a rapidly changing environment.

East Africa LEWS: A collaborative solution

Map showing predicted quantity of forage in the East Africa LEWS program area

In collaboration with National Agricultural Research System in Kenya, Ethiopia, Uganda and Tanzania, scientists at Texas A&M University funded by USAID (1997-2003) through the Global Livestock Collaborative Research Support Program developed the Livestock Early Warning System (LEWS).
The LEWS was designed to provide an early warning system for monitoring rangeland forage conditions, livestock nutrition and health for maintaining the food security of pastoralists. The program framework is an integral part of the existing system for drought and famine in pastoral areas of Ethiopia, Djibouti, Somaliland, Kenya, Uganda, and Tanzania. The development and implementation of LEWS include spatial characterization, the establishment of monitoring sites, biophysical modeling, model analysis, and field verification and automation of information dissemination.

The central thrust of the LEWS project is to provide information on impending drought insufficient lead-time to allow the government, NGOs and pastoral communities to react to the conditions in a timely manner to prevent resource degradation and loss of assets. Timely decision making by livestock owners concerning the availability of forage supply, movement, destocking, and restocking of livestock will be valuable for sustainable livestock production in eastern Africa.

The indigenous knowledge of the pastoral societies regarding range and livestock is much more effective if they can have access to near real-time information on impending forage shortages for livestock and location of forage supplies. This minimizes conflict during periods of restrictive conditions. A combination of this indigenous knowledge and modern science is used by decision-makers to formulate clear mitigation strategies to reduce risk from extremes of weather conditions.

The project contributes to this noble venture by generating country-specific forage situation and deviation status reports updated every 10 days, a monthly advisory for Kenya, Tanzania, Ethiopia and Uganda, and a regional forecast report for the same countries. These reports are posted via e-mail to an array of users that include government agencies, NGOs, UN agencies, and livestock stakeholder groups.

LMIS: Livestock Marketing Information System

gabe.saldana · April 25, 2022 ·

LMIS: Livestock Marketing Information System

Developing reliable, timely livestock market information for the development of East African countries

A need for reliable, timely market information

The livelihood of a vast majority of people in eastern Africa is highly dependent on income from livestock and livestock products. Therefore, the development of reliable and timely livestock market information is vital for the development of the countries in the region and provides a basis for livestock producers and traders to make marketing decisions.

The Problem

In the past few years, the urgency to address the needs of livestock-keeping communities in eastern Africa has risen dramatically, prompting national governments, NGOs and international donors to explore high impact interventions. Given the high dependency of livestock keepers’ family livelihoods on cash income from the sale of livestock and livestock products, the institutional focus has been directed toward improving livestock market information, infrastructure, and efficiency.

An extensive review of the wide array of livestock market development activities in eastern Africa revealed a lack of viable livestock market information system to support decision making of traders, producers and policymakers. A reliable market information system creates transparency and a basis for the livestock keepers to make marketing decisions.

Steps Toward A Solution

With funding support from USAID, the Livestock Information Network and Knowledge System (LINKS) of the Global Livestock Collaborative Research Support Program (GL-CRSP) has developed an Information Communication and Technology (ICT) system to extend the technical and human capacity to meet livestock information needs to support decision-making for livestock producers, traders, and policymakers in East Africa.

Using a partnership approach with existing livestock marketing institutions in the eastern Africa region, LINKS has designed and is delivering a livestock information and communication technology that provides monitoring and analysis technology to foster strategic partnerships between livestock keepers, markets and policy. Autonomous systems with near real-time databases have been established in Kenya (http://www.lmiske.net) Tanzania (http://www.lmistz.net) and Ethiopia (http://www.lmiset.net). Additionally, given the cross-border nature of livestock trade, the project offers a regional framework where countries involved can collaborate, network and share experiences.

How it Works

One of the major aims of the LINKS project is to determine the application of and usefulness of integrated spatial, information, and communications technologies in improving the livestock market information infrastructure in eastern Africa.

The LINKS project is built around emerging information technology coupled with spatial models of livestock movement and expected prices and volumes at secondary and terminal markets to add value to the market information system.

The spatial information and communication toolkit includes Global Positioning System (GPS), mobile phones, Worldspace radios, computing analysis, and web-based platforms. Integration of these tools makes it possible for the system to carry out market chain analysis indicating the source of animals, the time taken to truck them and the associated costs of getting them to designated markets.

Obtaining Market Data

Market monitors are trained in the use of livestock market data collection formats and are given instructions and guidance on the proper ways of approaching sellers, brokers, and traders to collect reliable data in an effective way. The monitors are provided with mobile phones and scratch cards to enable them to send the collected data to the database system.

Livestock prices and volumes are collected through interviews during the peak of a market day. A trained livestock market monitor interviews five cases of each of the dominant breed, class and grade combination of animal species on that market day. Average prices by animal kind, breed, class, and grade is then calculated along with the total volumes of livestock by animal kind and the information is coded and sent into the database system using SMS, e-mail or posted directly on the web into the database system.