What are the frustrations in using feed databases?
The troubles caused by feed databases
This post was last edited by Han Youwen on 2009-11-25 13:37
The troubles caused by feed databases
Han Youwen
In the "Nutrition and Formulation" section of the forum, quite a few people are looking for the "feed data" they favor, with the focus on confirming the "effective energy values" of feeds. Among them, most are feed formulation workers (formulators), and a few are "formulation software developers," all of whom want to match them to their own work. When they find that the feed data are unsatisfactory, grumbling and complaints often show up in posts, and occasionally one can even see the odd ranting post: "So many professors and PhDs, what do they do all day? They can't even produce China's own feed database!"
It seems, "salt is salty because of that"? "Vinegar is sour because of that"? As for the origin of databases? It is worth examining carefully!
No data can "fall from the sky"; someone has to do the analysis, measurement, and statistics to obtain them. Unless it is a "feed database" released as a public-interest national undertaking, generally speaking, there is no [free lunch]. Who has ever seen any feed company publish its own corrected and developed exact "feed data" for free, for peers and others to use?
The most commonly seen is our country's "feed database," which lists more than 80 kinds of feed, and still lacks forage data. In addition, the US NRC feed database is relatively complete, and the corresponding databases of the UK, France, Japan and other countries can also be consulted. However, this type of official feed database consists of broadly representative average values, that is, what is called "run-of-the-mill goods." To use them for a specific feed in our country and have them match exactly is not very easily done.
When feed companies and the livestock industry use the average values given by the database in their own formulation work, can they match their own raw materials? This is precisely the most vexing problem. Lacking practical grounding in animal nutrition and feed science, when using them, how to correct the data so that they fit the current situation and conditions inevitably leaves one feeling very uncertain.
The difficult points in feed databases are not the conventional components (the major proximate analyses) and other laboratory-measured items (amino acid and vitamin components). For these, as long as there is instrumentation and equipment, standard methods, and people who analyze and measure conscientiously, given some funding and time, the data will be obtained, and the error will not be very large.
The key point of feed data still lies in their effective energy values for various types of animals. That is, according to current requirements: for pigs it is digestible energy [DE] or metabolizable energy [ME]; for poultry it is metabolizable energy [ME]; for ruminants it is net energy [NE]; for aquatic fish and shrimp it still remains at gross energy [GE]. For the same feed and animals of the same name, because of differences in species, sex, and age, sometimes the effective energy values cannot be used interchangeably; for example, among ruminants, dairy cattle, beef cattle, and sheep; among poultry, chickens, geese, and rare birds.
Generally speaking, gross energy [GE] is the easiest to measure. Digestible energy [DE] and metabolizable energy [ME], relative to net energy [NE], are still relatively simple, and can also be done by actual measurement with animals. However, for the net energy values of feeds and forages for ruminants (dairy cattle, beef cattle, sheep), apart from the limited number of feeds whose [net energy for fat deposition] was measured by the German Kellner school in the first half of the last century, to date there is not a single case, in the substantive sense, of net energy for milk production [NEL] or net energy for gain [NEg] of a feed or forage being measured with cattle and sheep.
The effective energy value of a feed differs from its analytical measurement data; it is manifested in the interaction between the feed and the animal. Therefore, the various effective energy values measured with representative animals are only universally applicable within the animal groups they represent. They cannot be like the conventional analytical components of a feed or other measured values, which are properties of the feed itself and are the same for all animals.
The current situation of feed data is this: the composition of traditional "old" feeds has changed greatly because of breeding selection, such as high-oil corn; high-protein, high-lysine corn; high-oil and high-protein transgenic soybeans; various polyploid hybrid crops, and so on. The effective energy values of these themselves and their processing by-products already differ noticeably from those of feeds of the same name before.
In addition, with the refinement of processing of grain and agricultural products, there is a wide variety of processing by-products from food, brewing, fruit juice, and so on, constantly being renewed in variety. To obtain their feed-use data, including laboratory analysis and measurement and effective energy values, one usually has to start from scratch, because much of this is still a blank.
It seems that establishing a relatively complete and applicable feed database is indeed "a heavy task and a long way to go." From the responsible leaders to the relevant scholars and the elite of enterprises, no one can come up with a feasible plan. What should be done? Let everyone discuss it!
--------------------------------------
Looking forward to new breakthroughs in China in research on ruminant nutrition and feeds
--------------------------------------
This kind of perplexity has existed for a very long time; this is the greatest distress for those of us who do feed formulation technical work!
--------------------------------------
Indeed, many people encounter the same problem!
--------------------------------------
Yes, for those doing formulation, the most headache-inducing thing is the database
--------------------------------------
Study it slowly
--------------------------------------
If funding allows, using near-infrared analysis should be a good method.
--------------------------------------
At present, near-infrared detection means are the most advanced; it is fast and accurate, but the key is to have a set of standard database support.
In addition, as for animal nutrient requirement models, at present those for dairy cattle and laying hens are relatively mature, while that for pigs still needs to be perfected as much as possible.
--------------------------------------
This problem cannot be thoroughly solved for the time being. From the perspective of detection means, the original conventional methods are too slow; at present, near-infrared seems to be the best choice for on-site application, but near-infrared detection works very well for substances in a homogeneous state, while it is not very easy for ordinary feeds to be made homogeneous, and as Dr. Wang said, it also needs standard data to support it.
Actual measurement of effective energy values is unrealistic in real production; the highest level that current energy measurement technology can achieve is metabolizable energy, and those who advocate net energy for formulation all day long probably do not quite understand this point.
In fact, the significance of actual measurement of the effective energy values of conventional feeds is not as great as imagined. The reason is simple: the energy value of a raw material ultimately comes from the content of energy-containing nutrients in the feed (mainly reflected in sugars, fats, and proteins), and these indicators can be reflected through existing detection means. Therefore, the so-called database problem is better described as a raw material control problem
--------------------------------------
Database, the core
--------------------------------------
According to your own company's raw material procurement channels, measure it yourself and build your own database. That is what our company does
--------------------------------------
In the aquatic sector, one issue is environmental factors; currently the digestibility method is still controversial; another is that there are too many species, and the same species differs at different stages. The task is heavy and the road is long... looking forward to colleagues working hard together!
The troubles caused by feed databases
Han Youwen
In the "Nutrition and Formulation" section of the forum, quite a few people are looking for the "feed data" they favor, with the focus on confirming the "effective energy values" of feeds. Among them, most are feed formulation workers (formulators), and a few are "formulation software developers," all of whom want to match them to their own work. When they find that the feed data are unsatisfactory, grumbling and complaints often show up in posts, and occasionally one can even see the odd ranting post: "So many professors and PhDs, what do they do all day? They can't even produce China's own feed database!"
It seems, "salt is salty because of that"? "Vinegar is sour because of that"? As for the origin of databases? It is worth examining carefully!
No data can "fall from the sky"; someone has to do the analysis, measurement, and statistics to obtain them. Unless it is a "feed database" released as a public-interest national undertaking, generally speaking, there is no [free lunch]. Who has ever seen any feed company publish its own corrected and developed exact "feed data" for free, for peers and others to use?
The most commonly seen is our country's "feed database," which lists more than 80 kinds of feed, and still lacks forage data. In addition, the US NRC feed database is relatively complete, and the corresponding databases of the UK, France, Japan and other countries can also be consulted. However, this type of official feed database consists of broadly representative average values, that is, what is called "run-of-the-mill goods." To use them for a specific feed in our country and have them match exactly is not very easily done.
When feed companies and the livestock industry use the average values given by the database in their own formulation work, can they match their own raw materials? This is precisely the most vexing problem. Lacking practical grounding in animal nutrition and feed science, when using them, how to correct the data so that they fit the current situation and conditions inevitably leaves one feeling very uncertain.
The difficult points in feed databases are not the conventional components (the major proximate analyses) and other laboratory-measured items (amino acid and vitamin components). For these, as long as there is instrumentation and equipment, standard methods, and people who analyze and measure conscientiously, given some funding and time, the data will be obtained, and the error will not be very large.
The key point of feed data still lies in their effective energy values for various types of animals. That is, according to current requirements: for pigs it is digestible energy [DE] or metabolizable energy [ME]; for poultry it is metabolizable energy [ME]; for ruminants it is net energy [NE]; for aquatic fish and shrimp it still remains at gross energy [GE]. For the same feed and animals of the same name, because of differences in species, sex, and age, sometimes the effective energy values cannot be used interchangeably; for example, among ruminants, dairy cattle, beef cattle, and sheep; among poultry, chickens, geese, and rare birds.
Generally speaking, gross energy [GE] is the easiest to measure. Digestible energy [DE] and metabolizable energy [ME], relative to net energy [NE], are still relatively simple, and can also be done by actual measurement with animals. However, for the net energy values of feeds and forages for ruminants (dairy cattle, beef cattle, sheep), apart from the limited number of feeds whose [net energy for fat deposition] was measured by the German Kellner school in the first half of the last century, to date there is not a single case, in the substantive sense, of net energy for milk production [NEL] or net energy for gain [NEg] of a feed or forage being measured with cattle and sheep.
The effective energy value of a feed differs from its analytical measurement data; it is manifested in the interaction between the feed and the animal. Therefore, the various effective energy values measured with representative animals are only universally applicable within the animal groups they represent. They cannot be like the conventional analytical components of a feed or other measured values, which are properties of the feed itself and are the same for all animals.
The current situation of feed data is this: the composition of traditional "old" feeds has changed greatly because of breeding selection, such as high-oil corn; high-protein, high-lysine corn; high-oil and high-protein transgenic soybeans; various polyploid hybrid crops, and so on. The effective energy values of these themselves and their processing by-products already differ noticeably from those of feeds of the same name before.
In addition, with the refinement of processing of grain and agricultural products, there is a wide variety of processing by-products from food, brewing, fruit juice, and so on, constantly being renewed in variety. To obtain their feed-use data, including laboratory analysis and measurement and effective energy values, one usually has to start from scratch, because much of this is still a blank.
It seems that establishing a relatively complete and applicable feed database is indeed "a heavy task and a long way to go." From the responsible leaders to the relevant scholars and the elite of enterprises, no one can come up with a feasible plan. What should be done? Let everyone discuss it!
--------------------------------------
Looking forward to new breakthroughs in China in research on ruminant nutrition and feeds
--------------------------------------
This kind of perplexity has existed for a very long time; this is the greatest distress for those of us who do feed formulation technical work!
--------------------------------------
Indeed, many people encounter the same problem!
--------------------------------------
Yes, for those doing formulation, the most headache-inducing thing is the database
--------------------------------------
Study it slowly
--------------------------------------
If funding allows, using near-infrared analysis should be a good method.
--------------------------------------
At present, near-infrared detection means are the most advanced; it is fast and accurate, but the key is to have a set of standard database support.
In addition, as for animal nutrient requirement models, at present those for dairy cattle and laying hens are relatively mature, while that for pigs still needs to be perfected as much as possible.
--------------------------------------
This problem cannot be thoroughly solved for the time being. From the perspective of detection means, the original conventional methods are too slow; at present, near-infrared seems to be the best choice for on-site application, but near-infrared detection works very well for substances in a homogeneous state, while it is not very easy for ordinary feeds to be made homogeneous, and as Dr. Wang said, it also needs standard data to support it.
Actual measurement of effective energy values is unrealistic in real production; the highest level that current energy measurement technology can achieve is metabolizable energy, and those who advocate net energy for formulation all day long probably do not quite understand this point.
In fact, the significance of actual measurement of the effective energy values of conventional feeds is not as great as imagined. The reason is simple: the energy value of a raw material ultimately comes from the content of energy-containing nutrients in the feed (mainly reflected in sugars, fats, and proteins), and these indicators can be reflected through existing detection means. Therefore, the so-called database problem is better described as a raw material control problem
--------------------------------------
Database, the core
--------------------------------------
According to your own company's raw material procurement channels, measure it yourself and build your own database. That is what our company does
--------------------------------------
In the aquatic sector, one issue is environmental factors; currently the digestibility method is still controversial; another is that there are too many species, and the same species differs at different stages. The task is heavy and the road is long... looking forward to colleagues working hard together!