The Zoo Diet Navigator (ZDN) is a software designed to manage and analyze animal diets in zoos and related institutions. It is designed to be flexible and adaptable to the unique needs of each institution. This article provides a comprehensive overview of ZDN, including its features, benefits, and best practices.
Introduction
Effective animal nutrition is crucial for the health, well-being, and conservation of species in zoos and wildlife facilities. The Zoo Diet Navigator (ZDN) is a software tool designed to streamline and optimize the management of animal diets. From tracking food items and nutrient values to generating shopping lists and analyzing dietary impacts, ZDN offers a range of features to support zoo nutrition teams.
Core Concepts of Zoo Diet Navigator
ZDN operates on the principle that all dietary records are institutional records. Even if a particular food item is no longer part of an animal's diet, the historical data remains to ensure a complete and accurate record of the animal's dietary history. For this reason, animal diets can only be inactivated, not deleted. This ensures that past feeding practices are always available for reference.
Avoiding Data Overwriting
It is crucial to avoid overwriting existing data with new information. For instance, if an institution switches from Brand X to Brand Y Unicorn Chow, renaming the food item in ZDN will erase the historical data associated with Brand X. Instead, create a new entry for Brand Y to maintain the integrity of the historical record.
Data Storage
ZDN is not meant to be a system for tracking body weights. It is bad data practice to store active data in more than one location. Your institution almost certainly has a system for tracking body weights, and you would end up with two animal weight histories in two locations, which may or may not be the same.
Read also: The Hoxsey Diet
Setting Up Foods in NaviGator
Setting up foods is perhaps the most fundamental first step you can take in NaviGator.
Nutrient Units
At this moment, you can’t change the nutrient units
Food Information
- Who eats this food?
- Price per g: Enter the price for this food.
- Notes: You can enter notes here about a food. They don’t really show anywhere except if this food is a Recipe, then these are the recipe instructions.
- Average vs. Most Recent Nutrient Values: When analyzing diets, you can choose between average and the most recent nutrient values. For general diet balancing, it is best to use “average”.
- Active: Is this food in use or not?
- Include in shopping list: In the Touchscreen window, kitchen staff can stock their station using information in the shopping list. Check this box to include this food item in those reports.
- Standard hardware bin
- Include in bin labels: If you pre-bag some feeds (i.e. To print bin labels, use 4×6″ index cards inserted into your printer skinny-side first
Custom Units
Although you can create any custom unit you like (“cup”, “scoop”, “handful”), there are two custom units that are special because they are used in some reports.
- “ea”: This means one whole item. 1 ea apple = 1 whole apple. This is used in shopping (e.g. table prep) and ordering/usage reports, and is a common unit when preparing diets, especially for things we generally don’t divide further (mouse, worm, fish, etc.).
- “case”: This means one whole package or box (case of apples, flat of fish, bundle of browse, bag of carrots, etc.). The Custom Units box (Settings > Edit Foods > Details tab) has a space for both amount and the gram weight (Gm_Wgt). Although Amount defaults to 1, you can put other amounts in there.
Units for food items on diet cards can be in any units. If not a standard unit of weight (g, oz, kg, lbs, etc.), then you must define a custom unit for that food. For example, you might put “1 ea” carrot on a diet, but you will need to define the weight of an “ea” carrot in Settings > Edit Foods. Some reports will then convert the calculated gram total to units of “ea” and “case” using those conversion values whenever available.
Units on Reports
If those units are showing up as blanks on your shopping or ordering reports, you do NOT need to convert your animal diets to units of “ea” or “case”. To reiterate - diets do not need to be fed in units of ea or case ever (but can be if you want). They can be in any (defined) unit. But, for reports to show all possible data, you will need to define “ea” and “case” for all foods that you want to see converted TO those units on reports.
Read also: Walnut Keto Guide
Replacing Foods
If you switch brands of a product, or completely globally replace one product with another, you can use this to do so. This saves you the hassle of opening up 30+ diets that ate the old food to switch to the new food.
Microsoft Access
ZDN was initially developed using Microsoft Access due to its simplicity, ease of use, and widespread availability. Access allows users with limited database experience to customize reports, queries, and features according to their institution's specific needs. The flexibility of Access supports the diverse feed operations across different zoos.
Customization
The uncompiled .accdb file format allows users to easily build their own reports and queries, modify existing reports, and create new buttons to run these new reports. Access is easy to learn. It may look intimidating at first, but if you are reasonably familiar with Office products and regularly use Excel formulas (as most folks working in nutrition tend to be), it’s actually quite easy to make changes and do some really cool things with it.
Integration with Other Systems
There are hopes that ZDN will eventually become integrated into ZIMS and/or other zoo management systems. Much of the design has already been incorporated into the wonderful nutrition module and touchscreen interface of Tracks. If other systems adopt its design, ZDN will get rewritten, so there seems little point in writing it for a new platform only to have it get re-written AGAIN.
Diets vs. Animals
Diets, rather than animals, are the central organizing principle because this was started as a diet prep system, and largely still centers around that function. Using diets as the organizing unit is more flexible for managing diets because often our animals change more frequently than our diets do (internal moves, accessions and deaccessions, births and deaths).
Read also: Weight Loss with Low-FODMAP
Zoo nutrition teams are often asked to prepare diets for animals who don’t yet or may never be accessioned into a formal records system. We may prepare diets for animals expected to arrive in the next day or two or who may not be accessioned yet. We may prepare diets for animals being temporarily held while in transit or wildlife rehab animals. We may prepare fruit bowls for display, food items for summer camp kids to turn into enrichment, or even create hypothetical diets for animals being considered for our collection so that we can get a cost estimate.
Layout of Diet Cards
The days are printed on the left on paper diet cards because it is much faster to prep from “days on the left” because you only scan down one column (days) and move your eyes right only for the items that occur today. If you list the food first (on the left), then you read every food, even if you don’t need that food today, and then must scan every line to the right to see if it should be prepped today.
Nutritional Composition of Horse Milk
To demonstrate the importance of understanding nutritional composition in zoo animals, let's consider the example of horse milk. While not directly related to ZDN, the principles of analyzing and managing nutritional data are similar.
Microquantity Analysis of Horse Milk
Research into the nutritional composition of horse milk has been conducted for three budding industries: (1) human consumption, (2) foal milk replacers for horse rearing, and (3) horse meat production. Mare milk has become an increasingly recognized ingredient in health beverages for human consumption, leading to an increase in mare milk production. Certain factors have helped spur this trend, including the production of cheese from mares’ milk and the potential reduced allergic reactions humans may have to horse milk relative to traditional cow’s milk. Mares’ milk has also been researched for foal milk replacers in case of orphanage, sickness, or general need of supplementation.
Analyzing mare’s milk is conducted using a variety of methods, with the most common being conducted by large-scale milk analysis companies. These laboratories analyze milk samples effectively, but require a minimum of 20 mL of milk for each sample. In addition, most milk testing facilities are calibrated by cow milk standards, reflecting the dominance of cow milk in the industry.
When researchers have investigated the macronutrient composition of non-cattle milks, particularly from threatened species, the sample quantities are often small (<5 mL). This is due to the collection opportunities being restricted by species access, milk being vital for the neonate, and the inability to train and/or obtain willing samples from dams.
Study Design
To better understand microquantity milk laboratory analyses, quarter horse (Equus caballus) milk from North Carolina State University (females = 4, n = 43) and California Polytechnic State University (females = 4, n = 42) equine centers was compared to investigate differences in macronutrient composition from 4 to 130 days after parturition. All mares were healthy, but consumed different diets.
Major milk macronutrients were measured at the Smithsonian National Zoo and Conservation Biology Institute using a microquantity analysis of ash, crude protein (CP), dry matter (DM), crude fat, sugar, and gross energy. Of the six measured nutrients, only CP and crude fat differed (p < 0.05) by location, while sugar and crude fat had differences among individual mares.
Results
Californian mares had greater fat concentration means on a dry matter basis (DMB) than the North Carolinian mares (ANCOVA, p = 0.003). North Carolinian mares had greater CP concentration means than Californian mares. These findings indicate that dietary differences and/or environmental factors may play a role in CP and crude fat milk macronutrient composition within horse breeds. However, despite the differences noted, the microquantity analyses for nutritional means for all eight mares were within macroquantity horses ranges available in the previous literature.
The results indicate that micro versus macroassays are comparable and supports clinical and scientific research on milk from species where large sample quantities are difficult to obtain.
Implications
Based on the results presented, microquantity measurement methods are effective for analyzing milk from mares and potentially related species. Milk assays for ash, fat, and CP were performed without traditional milk standardization protocols, which reduces dependency on machine calibrations. In addition, these assays were performed in duplicates using less than 2 mL of milk. The general methods themselves also required minimal instrumentation and did not involve expensive equipment, making them accessible for laboratories or institutions that have limited resources. The microquantity measurements appeared to reliably execute mare milk macronutrient values that were within the estimated and normal ranges expected based on previous studies.