Chapter 1
1. Introduction
1.1 Background
In ruminant-based extensive livestock systems, pastures are essential components and the
primary feeding source due to their economic viability. They play a crucial role in the
sustainability of animal production, end-product quality, animal welfare, and food security
(Serano et al., 2024). Accurate data on standing biomass in pastures is vital for effective
grazing management. Pasture yield (DM, in kg ha⁻¹) is a key parameter in managerial
decision-making, providing critical insights for adjusting systems and managing pastures,
particularly in calculating stocking rates and supplementation needs (Begna and Masho,
2024).
Creating a livestock feed balance allows for an examination of the needs of the existing
livestock population alongside the available feedstock. This enables the identification of
production-level constraints and the calculation of necessary feed to enhance output.
Depending on legislative requirements and precision needs, livestock feed balancing can
occur locally, regionally, or nationally. A feed balance compares the available feed (supply)
and livestock needs (demand) at any time, offering a ‘snapshot’ of the current situation.
Identifying feed shortages or surpluses can help in planning and ensuring food security.
Feed constitutes a significant input in the livestock industry, accounting for approximately
60%–70% of total production costs for meat, milk, and eggs. Insufficient feed, in both quality
and quantity, leads to reduced livestock performance (Begna and Masho, 2024). The
sustainability of livestock production is often compromised by limited availability and
fluctuating quality of feed resources. Livestock keepers face challenges in managing fodder
flow to ensure a consistent supply of nutritious feed year-round. Although progress has been
made in enhancing the resilience of agro-pastoralists' livelihoods, the feed resource gap
remains significant, leading to considerable losses during droughts (70–90% in 2016–2017)
due to insufficient feed.
To support sustainable growth in the national livestock sector, feed resources must be
assessed and monitored. Information from livestock feed inventories is invaluable for
policymakers, NGOs, and development agencies in formulating sustainable livestock
development strategies and coping with climatic variations such as droughts and floods
(FAO, 2018). The feed inventory provides data on the types, quantities, and locations of
various feed resources, while the feed balance compares availability and demand.
Feed assessments inform decisions about commodity types, potential trade markets, and
imported and exported feed resources. Despite the impacts of feed shortages on productivity,
national-level assessments remain scarce. Information on feed ingredients at the national
level can improve efficiency and profitability in the animal feed industry and help researchers
formulate sustainable feeding strategies. Estimating feed resources nationally will enhance
estimates of livestock's environmental impacts and carbon sequestration potential. Generating
feed balance data at the national level will facilitate proper planning, such as determining
livestock numbers that can be supported by existing feed resources and identifying necessary
feed resources to achieve targets, ultimately enhancing food security.
This research aims to address these challenges by developing a decision support system
(DSS) that integrates information on rangeland resources, crop residues, and both non-
conventional and conventional feed sources to assist livestock keepers in optimizing their
fodder flow planning and evaluating the carrying capacity of their production systems.
1.2 Problem Statement
Farm animal feed and fodder inventory, feed balance, and feed outlook are critical
components when livestock are viewed as productive assets. However, there is a disconnect
in Zimbabwe between knowledge on feed and fodder inventory, feed balance, and feed
outlook at both national and farm levels. A decision support system can aid livestock
producers in balancing forage biomass production with the requirements of grazing livestock.
1.3 Justification
Overgrazing in Zimbabwe, resulting from mismatched forage supply and livestock demand,
leads to decreased forage growth and reduced livestock productivity (e.g., lower weights,
slower growth, decreased fertility). A decision support system can balance supply and
demand, promoting sustainable grazing and aiding decisions about feed imports and
emergency feed procurement.
1.4 Objectives
1.4.1 Main Objective
To develop a decision support system for fodder flow planning at the University of
Zimbabwe Agro Industrial Park, integrating spatial and temporal biomass availability,
livestock dry matter requirements, and a mathematical model to optimize forage supply and
demand throughout the production year.
1.4.2 Specific Objectives
1. Estimate spatial forage biomass availability at the University of Zimbabwe Agro
Industrial Park.
2. Determine the livestock dry matter requirement per year.
3. Use quadratic regression models to estimate potential available aboveground forage
biomass.
1.4.3 Hypotheses
Hypothesis (H1): The decision support system developed in this study can
significantly improve fodder flow planning and carrying capacity assessment of
livestock keepers compared to their current practices.
Null Hypothesis (H0): The decision support system developed in this study cannot
significantly improve fodder flow planning and carrying capacity assessment of
livestock keepers compared to their current practices.
Chapter 2
2.0 Literature Review
2.1 Introduction
Management often states, "If you cannot measure it, you cannot manage it." Accurate
assessment of feed resources at the national level, including their availability and nutritive
value, is crucial for effective management. The University of Zimbabwe Agro Industrial
Park, like many agricultural establishments, faces challenges in managing forage resources,
especially during droughts or fluctuating weather patterns.
Integrated agro-industrial parks process crops and generate substantial by-products for animal
feed. Effective integration creates a win-win situation in terms of supply and demand.
Accurate estimation of forage biomass availability and livestock carrying capacity is vital for
informed decision-making to ensure sustainable livestock production and range management.
Spatial and temporal assessments of current and forecasted feed resources will assist in
disaster management, especially during floods and droughts (FAO, 2018). However, the
complexity of forage dynamics and environmental variability poses challenges for timely and
informed decisions. A decision support system (DSS) that integrates forage flow planning
and carrying capacity estimation can bridge this gap.
2.2 Fodder Flow Planning
Fodder is crucial in livestock farming, determining both land and animal productivity (Husain
et al., 2024). Animal feed sources include rangeland vegetation, fodder crops, crop residues,
and non-conventional feeds. Rangeland vegetation is significant, constituting over 60% of all
feed resources.
Fodder flow refers to the production and consumption of roughage feed used in livestock
feeding over an annual cycle. Planning aims to provide adequate feed quantities of the
required quality to achieve specific animal performance levels. The goal is to produce all feed
requirements from farm-grown forages with minimal supplementation at the least cost.
2.2.1 Fodder Flow Planning Procedure
A good fodder flow plan is essential for successful livestock farming, preventing feed
shortages during critical times. Procedures include:
1. Determine Herd/Flock Feed Requirements: Assess seasonal animal feed
requirements based on breed, animal classes, number of animals, and average mass.
2. Determine Animal Units (AU) in Terms of Dry Matter (DM) Requirements: Use
the livestock unit (LU) concept, equating an animal weighing 450 kg to a DM intake
of 12 kg/day.
3. Assess DM Forage Production Capability: Evaluate production patterns of various
forages month by month and estimate available crop residues.
2.3 Rangeland Forage Biomass Production Systems in Zimbabwe
Rangelands are significant ecosystems for grazing livestock and wildlife, covering 30-75% of
the Earth's land surface. They produce diverse goods and services, including livestock forage
and habitat. However, one-third of rangelands are degraded due to over-exploitation and land
conversion. Climate change further exacerbates rangeland degradation, necessitating effective
management practices.
2.3.1 Characteristics of Rangeland Forage Biomass Production in Zimbabwe
Rangelands, comprising grassland, savanna, and shrubland, account for 50% of the Earth's
surface and provide 70% of forage for ruminant livestock. Livestock in Zimbabwe primarily
graze on native pastures and crop residues, which are often in short supply and of poor
nutritional value during the dry season. Increasing rural resettlement has further reduced
grazing land, while seasonal climate changes affect feed quality. The introduction of
commercial smallholder dairy farming has led to more established forage species,
complementing natural grazing.
2.4 Livestock Dry Matter Requirements
2.4.1 Determination of DM Requirements for Grazing Livestock
Dry matter intake (DMI) is critical for understanding livestock nutrition and grazing
behavior. Predicting DMI requires consideration of various factors, including animal class,
stage of life, and body weight. Grazing management ensures that DMI requirements align
with available forage.
2.5 Carrying Capacity
2.5.1 Definition and Concept
Carrying capacity (CC) is the maximum stocking rate for a grazing unit that can be
sustainably supported throughout the grazing season. It requires considering available forage
and livestock nutrient requirements.
2.6 Decision Support Systems for Rangelands
2.6.1 Integration of Models in Rangeland Decision Support Tools
Farmers rely on natural forage for livestock grazing. Decision support tools help predict
seasonal variability in forage production, improving management practices and stocking
rates.
3. Methodology
3.1 Research Design
The study will employ a stratified random sampling design at the University of Zimbabwe
Agro-Industrial Park, integrating ecological site descriptions and spatial data collection.
3.2 Research Site
The study will occur in Mazowe District, Zimbabwe, covering 1800 hectares, with 800
hectares designated as rangelands.
3.3 Data Collection Procedures
Transect Layout: Each transect will be 50 meters long, with quadrats measuring 1m x 1m
placed at 5m intervals. Data collected will include basal cover, bare ground, and plant counts.
3.4 Crop Residue Estimation
Crop residue estimation will follow a three-step process: calculating primary crop yield,
using the residue-to-product ratio, and deriving final residue yield estimates.
3.5 Decision Support System Development
The DSS will facilitate data storage, processing, and user interaction, allowing livestock
producers to input data and receive informed recommendations.
3.6 Expected Outcomes
The DSS will enable better planning and management of fodder flow, contributing to
sustainable livestock production in Zimbabwe.
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