Section 1

Dairy Herd Health & Production Management Programme to Optimise Farm Profits


Ideal Dairy Farm, comprising 200 HF crossbred cows and 100 buffaloes, is a family-managed dual objective dairy operation. It supplies milk to neighboring dairy cooperatives, and the excess pregnant heifers are sold to prospective farmers through a bank tie-up. The farm however faces numerous problems such as variations in daily milk yield (sometimes as high as 20 per cent); many cases of milk fever, low peak yield and days-to-peak and low milk fat going down to as low as 2 per cent. These are in fact the signs that the problems have now become severe. Unaware of the precise causes of the persistent problems, the farmer has spent heavily on medicines, supplements and veterinary costs. The farmer is unhappy with the situation as the farm is not making any profit but because of investment made in infrastructure (which has no alternate utility) and animal purchases, liquidation has become difficult.

These are common issues faced by most of the intensive farmers who have invested money and time in establishing a farm. Typically even in this type of intensive operation, the veterinarians are called for help when there is incidence of mastitis, endometritis, fever, loss of production, etc.

Let us see what happens at a large organisation level. The Vasudha Milk Union is a block level cooperative organisation, a federation of around 150 village cooperative societies. Farmers have availed bank loans to purchase buffaloes and crossbred cows. The Union has 25 para-veterinarians and three veterinarians who have been assigned fixed daily visit routes to treat sick animals, mostly based on clinical presentation since laboratory facilities are not available. The treatment revolves around use of antibiotics, hormones as well as other chemicals/drugs and no attention is paid to drug withdrawal period. The farmers get their animals examined by veterinarians when they observe sickness whereas for insemination the farmers call the para-vets when estrus is detected.

Whenever farmers recollect, a veterinarian is called for pregnancy check and in a significant proportion pregnancy tests are negative. The farmers are not usually aware of the way to monitor animal productivity due to lack of knowledge and information, such as peak milk yield, lactation yield, cost of milk production, genetic value of animal. The systems to detect sub-clinical diseases are almost non-existent. The veterinary costs are high, and due to low productivity, profit margin is negligible. To boost milk production for the processing plant, large number of animals are regularly purchased from outside because of which many diseases that otherwise were not present have been recorded. The Milk Union management is uncertain on measures to tackle these problems and achieve sustainable dairy development.

The intention is not to paint an overall grim picture but majority farms and dairy cooperatives are ridden with above-mentioned problems. From the available data on per animal productivity and fertility, it is evident that compared to other countries India still lags behind as during last few decades average productivity performance has remained more or less static. Although sufficient infrastructure has been created and veterinary knowledge generated, the dairy farms and cooperatives are still struggling to adopt a suitable service delivery model. In general the predominant service structure is passive, discontinuous and mostly caters to curative needs. Except for artificial insemination, productivity improvement has not yet been fully integrated with animal health delivery. For example, animals are purchased from sources where no performance records are available and so the basic input quality is not assured. The farm management is largely observation-based and there are no long-term herd improvement plans and programmes. Rarely, there are systems in place to evaluate impact of the strategies adopted and if the programmes have yielded any results. It is well known that by the time a sick animal is identified, the animal’s physiology is already compromised. With crisis at hand, the only option left is to fight with the help of drugs, hormones, supplements which are expensive and excreted in milk. The government and NGOs organise treatment camps every year to address health and fertility issues but due to lack of diagnostic tools and data these ultimately turn out to be mineral mixture and medicine distribution camps. In large number of cases there is no follow up and it is difficult to evaluate how far these measures have helped the farmer.

If we consider the scenario in dairy-developed countries, it is observed that they had similar problems and difficulties a few decades ago but they realised that an alternate preventive system is necessary if animal productivity is to be increased and safe residue-free milk is to be produced as per the government standards. Evolving such alternate proactive system became easy when it dawned that most diseases are caused by interaction between several factors and that nutrition, sanitation, farm hygiene, environment were prominent predisposing ones which if properly managed could prevent diseases and increase animal productivity. This coupled with genetic improvement programmes brought about revolution in their dairy industry.

The objective of this new proactive system is to keep animals healthy, productive and economically rewarding to the farmer. This system is commonly known as ‘Herd Health and Productivity Management’ programme (HHPM).



The primary objective of the programme is to optimise dairy farm output by improving general health, reproductive efficiency, udder health and calf health using available resources with an ultimate goal to meet economic targets of the farm.

The performance is assessed by analysis of animal data that is continually updated and periodically analysed. The monitoring of the programme looks for detection of underlying problems and underperformances with reference to set targets, establish association of different factors with problems (such as disease, nutrition, management, source of animal purchases, sanitation, genetics) leading to evaluation of different solution options, implementation, monitoring and impact assessment. Although the programme appears complex, once implemented it becomes hassle free and beneficial to all the stakeholders.

 Components of the HHPM programme

The various components of this programme are as follows:

  1. Identification of individual animals

The accurate identification of every animal in the farm with a unique number system is prerequisite to keeping valid records. Without dynamic data, this programme cannot be implemented. Although India is a signatory and part of the international Committee on Animal Records (IntCAR), yet there are no publicised national policies and systems on animal identification, registration and traceability.

Many state governments and dairy organisations have launched performance recording programmes for which local animal identification systems are followed, but international standard is that all animals should be registered and identified with globally unique identification number to permit traceability. The premises where animals are reared (even if transit, such as, hospital) should be registered with unique premises number. In response to a report submitted by the author of this article, the Government of Maharashtra constituted and notified ‘Maharashtra Animal Identification and Recording Authority (MAIRA)’, with initial programme focused on premises registration, streamlining of animal identification, breeding bull registration with an aim to initiate traceability in the public programmes.

The most common identification device is plastic ear tag laser printed with permanent ink which can be fixed to the animal’s ear. A novel ear tag has now been developed and patented which could become an integral part of the data recording system. In these tags, the linear bar code has been replaced with unique two-dimensional bar code (also called Quick Response-QR code) (Figure 1).

Figure 1.Sample of QR-coded plastic ear tag.The square inside the tag is the QR bar code which is generated using free software incorporating encrypted animal information and URL/SMS access code.


Nowadays electronic RFID (Radio-Frequency IDentification) ear tags for animals are also manufactured and available in the country. These are of three types:

  • three-way ear tag in which unique identification number is encrypted on the RFID microchip implanted in the plastic ear tag. These tags also have laser printed identification number and linear bar code;
  • injectable identification RFID chip is inserted in a small device which can be implanted under the skin through a syringe and needle and an additional plastic ear tag is also affixed to assist in case of non-machine reading;
  • RFID bolus encrypted with unique animal identification number that can be fed for lodging in rumen.

In contrast QR-coded ear tags are advantageous for following reasons: (a) These are inexpensive around 25 per cent higher than simple plastic but one-fifth to one-tenth of the cost of RFID tags, (b) QR tags have permanent animal information, such as parent details and performance as well as details of the animal such as birth farm and date, etc, (c) RFID tags require readers to decode the ID number whereas QR-tags can be read with camera-equipped cell phone using free-download software, (d) Post-QR code scan the cell phone gets connected to the animal’s URL and its performance file for data update can be accessed, (e) In non-android phones post-scan SMS template can be generated and data can be send in coded form for update, (f) QR-code ear tag can be used to ascertain the authenticity of the services and the captured data which is not possible with RFID unless an active transponder is used. Figure 2 describes the scheme of dairy animal data management using web-server based software platform. The novel ear tags, cell phone based data capturing, data warehousing and mining and analytical algorithm have been developed as an integrated web-based system that is available now commercially in India.


Figure 2: Scheme of data management system. The animals need to be uniquely identified and ear tagged with QR coded or simple plastic ear code. The registration of animals is on web-server wherein individual farmer and his animal’s files are created to maintain life-time records. The web-server system is interfaced with messaging system which sends daily action and alerts to the farmers and the identified service provider of the farmer. The data from the farm can be updated in real time by sending either SMS or directly using the Tablet version of the software. In case QR coded ear tag is used the data entry form or SMS template gets opened only after scanning of the code. This ensures data credibility.


  1. Animal data recording for herd health management

In dairy herd health and productivity programmes, the basic data-recording unit is the individual cow or buffalo. The data recording could be manual on cow card but the disadvantage is that for data analysis these cards need to be handed over to the veterinarian who has to re-enter the data in the computer or do it manually. In general, where data is kept on cow cards, the data is not of much use for day-to-day management as periodic analysis is neglected.

With recent revolution in smart phones, and other hand-held devices like Tablets, iPad and developments in cloud computing, data warehousing and mining has become cost effective and universal. Even a farmer living in a remote area can register his animals and get benefits of data management services. To meet the requirements of the small and medium scale dairy farmers, a computer programme ‘Herdman’ was developed in India. The earlier desktop version had several limitations such as individual installation, sharing of data and difficulties in data update from far-off villages. To address these issues, a new web-server based version of ‘Herdman’ software has been recently launched. This has made the system affordable to even small farmers and dairy cooperatives. Since the software is now available on per year per animal license basis. The farmers can pay a nominal yearly fee and register their animals.

Once registered, the farmers and his veterinary service providers receive daily action and under-performing animal alerts which helps the farmer to manage the animals scientifically. The programme is also useful for dairy organisations since farmers can collectively subscribe the server space and SMS services. Medium range intensive farmers having more than 20 animals and using smart Android phones can obtain user name and password to download the programme on their cell phone and generate alerts, action lists, browse reports and performances of their animals. Figure 2 describes the novel data management system.

The unique feature of the software is that it also shares the animal data in real time with the service providing veterinarians. The farmers can also update milk records by either using smart phone or small farmers can send coded SMS to the server. The system has elaborate backend validation processes to ensure that the data is updated correctly. The system is especially useful for public veterinary services since the data on vaccination, disease testing, disease reporting, AI and other related work can be updated from the farm-side only as the data entry form gets opened when the QR code on ear tag (or the premises card) is scanned. This is probably the only such system available globally wherein all the stakeholders are part of the data management system and the farmers are not required to maintain any hardware. This network can also be used for product education and marketing as the programme sends information to the farmers when they need depending upon the status of animals. For example, when the animal is supposed to reach peak yield but the milk production trend predicts a possible concern, information about a product that would help in addressing the problem can be sent to the farmers. Further details are available on

The ‘Herdman’ data management system is compatible to RFID and simple plastic ear tag. The data from the RFID enabled hand-held device can be updated to the server using a handheld device especially developed for the purpose. In this system the data entry form is opened only when the RFID ear tag is scanned and after entering the new records the data can be updated on the server directly. In case the farmer is using milk parlour, data from the parlour can be imported in the system directly. Since data management is a core activity of herd health and productivity management programme, the operating system of the software is described in brief.

  1. Fixing parameters and dairy farm targets

Every programme must have objectives and goals. The farmer in consultation with his veterinarian should set up farm targets. These should be in line with economic goals of the farm. These targets can be defined as default values for each herd in the software programme. Table 1 elaborates common parameters and their target values for cows and buffaloes separately.

Table 1: Parameters and activities targets and goals for cow and buffalo.


Suggested Target*



Calf weight records

Every 15-30 days

Every 15-30 days

Heat interval

18-21 days

18-21 days

Pregnancy diagnosis

45-60 days

45-60 days

Reconfirmation pregnancy diagnosis exam

75-90 days

75-90 days

Days to first heat after calving

30-35 days

35-40 days

Days to first breeding

75-90 days

80-95 days

Steaming up before calving

One month

One month

Milk recording interval

25-30 days

25-30 days

Brucella, TB, JD, testing

Every year

Every year

Milk testing for sub-clinical mastitis

Every six months

Every six months

FMD vaccination

Every six months

Every year

HS / BQ vaccination

Every year

Every year


Every six months

Every year

*The farmer should develop own targets based on the local conditions.
  1. Setting up farm activity schedule and general farm policies:
  • Set up general farm policies: Information on total number of animals to be purchased, source of purchase, examinations to be conducted before the purchase, quarantine and other parameters needs to be entered as default values in the software for each herd.
  • Optimise feeding system: Since feed constitutes over 60 per cent of the recurring expenses of the farm, it is important to optimise the system both in terms of meeting nutrients and energy requirements of the animals and cost.
  • Breeding programme: It is important to set up genetic improvement plans for the farm for which individual cow can be assigned breeding bulls for mating. The bull assignment could be based on trait type, genetic superiority in terms of gain, cow fertility and cow performance. The software can be interfaced with ‘Genetic Mating Systems’ available commercially.
  • Decide on target levels of performance: This need not be industry standards but should be realistic and attainable with available resources. The production and health indices levels should be fixed for comparative assessment.

Once the animal data is built up and the parameters are decided, the herd health software application can be used to understand the individual animal and group performance. Figure 3 shows a screen of the registered animal’s details. On a single screen all the lifetime events can be seen and breeding, production and health records can be accessed for perusal as well as for data entry in case the data is being filled in the desktop version. The software would generate farm activity lists. There are two types of lists:

  1. Daily farm activity list, and,
  2. Alarm list, that is the list of animals that are not performing compared to the set targets.


Figure 3: Individual animal file screen. Through this screen the data can entered and browsed. The lifetime details of health, breeding and milk production can be accessed through this screen. Similar screen can also be seen in cell phone version of ‘Herdman’ software.


The daily action list includes: (a) animals expected in heat, (b) animals non-return, (c) animals due for pregnancy check and reconfirmation, (d) animals due for drying off, (e) animals due for calving, (f) animals due for disease testing, vaccination, etc. The farm activity then can be scheduled accordingly. Even in dairy cooperatives this list helps the paravet or the veterinary officer to organise visits. The advantage is that the dairy operations are no more dependent on farmer observations or memory. The ‘Alarm List’ includes: (a) animals which have not expressed estrus after calving, (b) animals unbred after calving, (c) long open period, (d) animals with abnormal estrus interval, (e) low peak yield, (f) low 100 days milk yield, etc. This enables the veterinarians to concentrate on the group of animals mentioned in the list above and order investigations to understand the primary cause.

  1. Monitoring the herd profile to forecast production

Monitoring herd profile for various attributes is an important part of the strategy planning. ‘Herdman’ generates variety of profile reports with flexible sorting limits. Once the data is generated, it can be analysed from variety of angles to understand the problems and associated factors. Figure 4 depicts screen of general herd profile generated in the herd management software. This farm has cows and buffaloes, but the buffaloes are predominant. The pie chart illustrates the proportion of calves, heifers, pregnant animals, milking animals. For example, in a close herd where replacement animals are farm-bred, the standard herd profile recommended is: heifer 20-30 per cent, calves 15-20 per cent. Amongst breedable animals, 65-70 per cent should be pregnant and around 70-75 per cent adult animals should be milking.


Figure 4: Herd profile screen. The extreme lest column lists herds and lots registered and the selected herd is seen highlighted. The second column gives list of the animals’ identification number and current status which can be printed. The graphs give the summary of the profile for various attributes, such as, species (cow/buffalo). The pie chart depicts the proportion of age groups of animals in the herd and the bar graph physiological status of animals in the selected herds (with percentage).


Periodic profiling would help in understanding if the farm is running as per standard plans. Herd profiling can also be done for milking, pregnant and open animals. For example, if milk production is to be maintained throughout the year to meet the demand of the market, the breeding programme should ensure uniform distribution of animals on average days-in-milk (DIM). Similarly, in that case proportion of pregnant animals and the calving should be evenly distributed throughout the year.

6. Monitoring health and productivity through simple but critical observation rounds of the farm:

  1. Daily farm rounds: It is expected from a large as well as small farmer that he/she visits the farm every day and observes the animals for health and performance. There are simple indicators of health and productivity, which can be monitored, if properly understood: Ensure that animals’ dry matter requirements are fulfilled. Dry matter of a feed is calculated by deducting moisture content. Some farmers misconstrue this as dry fodder. An animal should receive at least 2.5 per cent of the body weight as dry matter. For example, an animal weighing 500 kg is expected to receive 12 kg dry matter, which should be met by feeding green, dry and concentrate depending upon the energy and other constituent content of each.
  2. Check for rumen function efficiency: The second important parameter to monitor is rumen function. This can be done by observing animals in their natural setup while taking round. Ideally the feeding bunk or manger should never be empty, it should always contain forages. In such farms the animals either should be eating or ruminating. The proportion of the animal ruminating should be more than 50 per cent. There should be enough froth while ruminating which indicates good salivation. In case the proportion is less the reasons should be investigated.

Visually observe fresh feces. It should be of normal consistency and there should not be undigested forage or grain particles. This can also be ascertained quantitatively. Take around 10 gram feces and add about 100 ml of water, and mix to slurry, and pass it through a mesh sieve. Presence of undigested grain and forage can be ascertained. If lots of (more than 10 per cent) undigested forage particles are seen, it could either be because long staple forage is not being fed or the size of the chaffed forage is less than one inch. Recurrent cases of animals going off feed or reduced dry matter intake must be investigated. The herd health and productivity management software can do these calculations with a click of mouse, if the data is already entered.

  1. Milk production and milk composition analysis

It is always better to record daily milk output of individual animals. But if milking machines are not being used, this is time-consuming. In such cases, milk records can be taken once in 30 days so as to collect at least 11 records in lactation. This milk record is called test day milk record. A sample of milk should also be collected for estimating butter fat and protein.

  1. Interpretation of lactation curve

The milk records should be converted into lactation curve and analysed (Figure 5). Analysing the composite lactation curve of all the animals in the farm or different groups (lots) of animals or individual animals permit identifying problem areas and the level at which the problem is present. The lactation curve should be examined for: (a) initial yield, (b) peak milk yield, and (c) consistency. If the initial milk yield is lower than expected, the problem could either be feeding of low energy dry ration or hence lower body score at parturition or peri-parturient problems, such as dystocia, prolapse and resultant endometritis, hypocalcemia, etc.


Figure 5: Lactation curve generated in ‘Herdman’ software. There are three lactation curves, the top most is standard for the species and breed, the middle one actual lactation curve for the herd, and the third one down the lowest is the lactation curve for the animal. This enables to compare the performance of an animal to standard and herd. There is also facility to generate lifetime lactation curves on the same graph to compare performance of this animal in different lactations. Column in the right enumerates the days on which milk record was collected and the yield recorded.



Different groups of animals’ lactation curve or individual animal lactation curve can be examined to identify problematic animals. The day during first 100 days (40-70 days) of lactation when milk yield is highest is called peak day and quantity is the peak yield. The index average yield per peak yield enables correct analysis of lactation curve. This is calculated by dividing the 305 days milk yield in kg by peak yield in kg. For example, if an animal has given 5,000 kg milk in 305 days and the peak yield was 25 kg, the index value would be 200. Genetically superior and persistent yielder would have this index ranging between 200-220 kg. A number of post-parturient diseases affect milk production reflected as abnormal index.

Figure 6: Lactation curve of an animal with peri-parturient problem – See the decline and then again rise in milk yield.

Lactation persistency: It is an important consideration while examining lactation curve. It is calculated as percentage of production (in kg milk) on the current sample day compared with that of previous sample day. The persistency then can be depicted graphically. Sharp fall in persistency indicates point in lactations that are associated with the changes. Like lactation curve it increases initially and then falls slowly. A good yielder would not have sharp fall in persistency. The animals can be grouped in four groups and the lactation curve can be generated for different lactation groups: (a) 10-40 lactation days, (b) 41-100 lactation days, (c) 101-200 lactation days, and (d) longer than 200 lactation days. In middle and late lactation, lower persistency is mainly due to lactation related diseases or genetics of the animals. The above two lactation curves have been obtained from Herdman database for two buffaloes. The lactation curve depicted in Figure 6 shows increase in milk production was normal in first 10 days, but this was followed by sudden drop in the production which could be due to ketosis, metritis or other causes common in post-parturient period. Because of this drop, the buffalo did not reach the expected milk yield and the loss of milk production in this animal can be predicted to be around 400 kg.


Figure 7: Lactation curve of an animal that had problem in mid lactation. It is not connected with breeding of animal.


The lactation curve of a buffalo depicted in Figure 7 also shows that this animal reached the peak (about 40 DIM) and continued until day 70 during which it was served following which the milk yield started decling sharply. The second estrus in this animal was recorded on around 50 days followed by upward trend and after third insemination on about 160 days milk production declined irreversibly. The nature of the curve suggests that this animal has shown delayed first heat (may be endometritis) and irregular elongated inter-estrus period indicating early embryonic mortality. Investigations revealed that many buffaloes in this farm had this problem. As a strategic intervention, all open animals in the farm were administered antibiotic for uterine treatment and impact analysis revealed good response. Thus, if milk records are available, the lactation curve analysis can help in taking rational approach to problem solving.

  1. Periodic data analysis

The data should be analysed periodically. In case of small-hold farms (up to 50 animals), it could be every month whereas for large-hold farms it could be every fortnight. This should include printing various administrative reports to understand the herd profile on breeding, production and lactation. The data should also be analysed for generating various health, production, and reproduction performance indices. The software also provides facility to undertake data sorting for establishing association of the problems with different factors. For example, if there are more number of repeat breeders and the veterinarian is interested in finding association with high milk peak yield and 100-days production, such a report can be generated using the custom report option. To generate such a report first select all animals then sort for open animals more than three AI and then from milk production menu, select peak yield (you may sort for > 20 kg) and 100 days milk yield (again sort for say >1000 kg). A list will be generated giving details of how many repeat breeding animals are associated with high milk production. The software provides facility of such data sorting for more than 150 variables.

1. Herd production indices: The data can be analysed to generate milk production indices described in Table 2 and Figure 5. The index average days-in-milk is important as it reflects the herd profile in respect of animals in different stages of lactation. In case the proportion of animals in late lactation is more, the index will increase whereas with more freshly calved cows or buffaloes, the index value would be low. The index average milk yield per lactation day is more specific since it adjusts the effect of ups and downs in lactation. By using herd management computer programme, one can generate the production indices for any period.

Table 2: Herd production indices in dairy operations.


Suggested target index values
Crossbred Cow


Average days in milk

150-170 days

120-140 days

Average milk yield per lactation day

15 kg

8-9 kg

Average days to peak

30-40 days

40-50 days

Average peak milk yield

22-25 kg

12-14 kg

Average 100 days yield


1000-1100 kg

Average 305 days yield

4500 kg

2500 kg


  1. Health targets: Presence of clinical or sub-clinical diseases in the farm or in the operational area of the dairy organisation is an important cause of loss in production (see box for list). It is therefore important to fix up health targets of the farm and monitor these targets as well as indices (Table 3).

Table 3: Dairy animal health targets.


Suggested targets*
Crossbred cow


Calf mortality

< 5%


Average weight gain in calf

500 g/day

500 g/day

Adult mortality



Average expected life of adult in the farm

5-6 years

3-4 years

Average number of lactations in the farm



Annual culling rate due to diseases



Incidence of clinical milk fever



Incidence of clinical ketosis



*These are only suggested targets and not industry standards; each farm should set up such targets as per local conditions.
  1. Scheduled Veterinarian visits

The veterinarian should be preferably retained not only for providing curative services but also to guide the farm in fixing targets, to get expert assistance to formulate ration for the farm, analyse data to find out problems and underperformances, develop genetic improvement and breeding plans for the farm and assist the farm in achieving economic targets. The veterinarian should be encouraged to develop preventive programmes so that the curative workload is not more than 5 per cent of the total work. A farm having number of animals with a disease or performance problem also indicates that the origin of the problem could be common source. Since some diseases are likely to recur in subsequent lactations such animals should be kept under close observation. For example, if a cow has suffered from milk fever, in the next lactation immediately after calving, calcium salts can be fed and care can be taken not to remove all milk from the udder. Such management decisions are possible only when the attending veterinarian has access to complete information on the animal.

Detecting disease problems at sub-clinical stage in the farm is an important aspect of herd health practice. Any increased frequency of clinical disease should be investigated by finding out if there are sub-clinical cases. In consultation with farm management, the sub-clinical disease testing plan should be worked out.

  1. Metabolic profiling

This is a scientific way to monitor health and productivity status of the animals in the farm or in the operational area of the dairy cooperatives. The principle is that by determining the biochemical markers of the health and productivity, the status of the herd can be ascertained. For this, animals must be randomly selected from either different physiological groups such as, early lactation, mid lactation, late lactation, pregnant, dry, or from different production groups, such as high, moderate and low milk yielder and their blood, serum, milk, feces are taken for examination.

Initially two rounds of major metabolic profiling should be carried out and later minor metabolic profiling can be undertaken. Profiling can also be done in animal groups with production and fertility problems. Currently there is a growing interest in milk urea determination since it can predict problems related with protein feeding.

Metabolic profiling is a sound method to monitor the adequacy of nutrition formulation. The major constraint is cost and the labour and time involved in undertaking the test. But, considering the benefits, this exercise is worth undertaking. It is also equally important to establish health diagnostic facility for undertaking routine hematology, biochemical analysis, milk component testing and sub-clinical disease investigation facilities. In subsequent sections, other components of the HHPM are described.