GROWTH IN NON VEGETERIAN FOOD CONSUMPTION BY 2014 AND IT’S IMPACT ON ANIMAL HEALTH INPUTS

WITH PARTICULAR REFERENCE TO PROBIOTICS

I. PREAMBLE

Production and consumption of Non vegetarian food are increasing every year in spite of some health conscious by birth non vegetarians are avoiding non vegetarian food

Kalyan Chakravarthy, country head of the food and agriculture division of Yes Bank says that in China and India, the youth and high-income population is adapting to meat.

Current global livestock production is growing more dynamically than any other agricultural sector around the world; livestock are now the world's largest land user (FAOa 2001).

According to the agriculture ministry, meat production in India has been growing at a compounded annual growth rate (CAGR) of 5 per cent over the past 15 years.

Trends have shown that non vegetarian food consumption in India has gone up from once a week to three times.

According to International Food Policy Research Institute (IFPRI), per capita meat consumption in India could reach 18 kg in 2020, compared to 10-12 kg now.

At present, in India Per capita availability of meat is 1.6 kg. Per capita availability of egg is 1.8 kg or 42 eggs. Average consumption of eggs in major cities is 170 eggs Average consumption of eggs in smaller cities is 40 eggs Average consumption of developed rural areas is 20 eggs Average consumption of undeveloped rural areas is only 5 eggs. While 20% of Indian population is vegetarian. 

Driven by population, income increases, rapid urbanization, and changing dietary habits, there is an unprecedented expansion of the livestock industry throughout the developing world where per capita meat production is expected to increase by nearly 50% between 2000 and 2020. Global meat demand is expected to grow by 35% and milk demand by 25% over the same period.

The increase in consumption of non vegetarian food is largely owing to the following facts.1. In developing countries, Governments are providing midday meal to school going children where Eggs are provided periodically.2. Compared to Vegetables, prices of Eggs are low in several countries.3. Dining out is becoming a regular habit and while dining in restaurants people try several non vegetarian dishes.4. With the increase in earning and purchasing capacities, people are tending towards Non vegetarian food.5. Urbanization. Rural folk moving to cities are more prone for increased intake of meat and eggs.

Demand for meat worldwide is forecast to rise more than 55 per cent between 1997 and 2020, with China alone accounting for more than 40 per cent of this increase, and India, 4 per cent, according to IFPRI. (http://www.businessworld.in/index.php/Commodities/Meat-Of-The-Matter.html) By the year 2020, it is estimated that there will be some 800 million additional people to feed on the planet. This together with higher income for food spending will put a tremendous demand on crop production.

The USDA reports that animals cycled through the U.S. meat industry produce 61 milliontons of waste each year, which is 130 times the volume of human waste, or .2 tons forevery US citizen (Horrigan et al. 1999). In the United States, waste from every type oflivestock increased between 1987 and 1997, with the largest increases in waste fromsheep and poultry. Large manure volumes will continue to be produced and distributedon less land in the coming years (Beegle and Lanyon 1994). These consequences ofanimal waste can be divided into three primary categories: water degradation, landdegradation, and air pollution.

Hence the need arises to put efforts in the following.1. Achieving more quantity and quality of meat, eggs and milk employing less land,

water and time.This can be achieved by

Encouraging high yielding varieties of animals Improving pre and post harvest technologies to avoid losses in transit. Improving the disease resistance and disease curing to reduce mortality

rates and to curb any weight falls during ailments Improving the quality of feed, FCR. Reducing the quantities og inputs by increasing TDN, reducing excreta,

employing newer technologies like DFM (Direct Fed Microbes to produce Amino Acids, Organic Acids, Enzymes, Growth promoters, Toxin degraders etc)

2. Achieve agricultural production without damaging the environment by

Employing greener technologies Preferring organic farming

3. Biodegrade all the wastes and pollutants of the industry like litter and make them more environment friendly.

4. Convert the poultry litter and cow dung into fit animal feeding stuff rather than usage of the same as manure.

Probiotics are live microorganisms which, when administered in adequate amounts, confer a health benefit on the host.Prebiotics are nondigestible substances that provide a beneficial physiological effect for the host by selectively stimulating the favorable growth or activity of a limited number of indigenous bacteriaSynbiotics are products that contain both probiotics and probiotics.

At the start of the 20th century, probiotics were thought to beneficially affect the host by improving its intestinal microbial balance, thus inhibiting pathogens and toxin producing bacteria. Today, specific health effects are being investigated and documented including alleviation of chronic intestinal inflammatory diseases, prevention and treatment of pathogen-induced diarrhea, urogenital infections, and atopic diseases.

Today, Scientists and Industry has recognized the important role of probiotics In improving

The survival rate, Weight gain FCR Egg laying capacity, Milk yielding capacity,

And in reducing Residual antibiotics, hormones, pesticides, dewormers Mortality rate Crop time Pollution Damage to Mother Earth.

According to a new market research report, 'Probiotics Market (2009-2014)' (www.marketsandmarkets.com/Market-Reports/probiotic-market-advanced-technologies-and-global-market-69.html), published by MarketsandMarkets(www.marketsandmarkets.com), the global probiotics market is expectedto be worth US$ 32.6 billion by 2014, with the Europe and Asia accounting fornearly 42% and 30% of the total revenues respectively. The global market isexpected to record a CAGR of 12.6% from 2009 to 2014.

Probiotics, belonging to the functional group of gut flora stabilisers within the category of zootechnical feed additives (according to the Regulation EC No 1831/2003) is a fast growing marketIn 2004, the global market value of probiotics was €32 million, with a forecasted annual growth of approximately 3%. However, due to the ban of antimicrobial feed additives, the probiotic market in Western Europe showed an annual growth of more than 7%. In 2006, Western Europe produced around 296 tons of probiotics, with a value of €15.5 million. With 1012 CFU (equivalent to about 100g) usually added to a ton of mixed feed, approximately 3 million tons of feed containing probiotics was produced last year.(www.allaboutfeed.net/article-database/potenti...)

Probiotic Foods & Beverages segment is expected to command over 75% of the overall probiotics market in 2009.Probiotic dairy products are accounting for almost 70% in the year 2009 and reaching a market size of almost $24 billion by the end of 2014.Probiotic dairy products market in USA is expected to grow at a CAGR of 17% from 2009 to 2014.Probiotic chocolates, probiotic ice creams and probiotic baked products areexpected to enjoy a much larger market share.Europe market for probiotics is estimated at $13.5 billion by 2014. Its 12.2% CAGR from 2009 to 2014 is driven by consumer demand for health-enhancing probiotic products, such as probiotic yogurts, other probiotic dairy products and probiotic dietary supplements.Asia is the second largest segment, growing at with an estimated CAGR of 11.2% to reach $9.0 billion by 2014.

Animals can be classified as follows.1. Companion animals2. Animals used in Agriculture3. Human food product (Milk, Eggs) producing Animals4. Animals used as Human Food5. Animals used in Industry( Wool bearing)6. Laboratory Animals7. Wild Animals

Beneficial microorganisms can be used in food, feed, drinking water; over pond water mediums; in the environment.

Beneficial microorganisms can be used in controlling Bacterial, fungal and viral infections Cancer Cholesterol External parasites Insects Internal parasites Obesity Pests

Beneficial microorganisms can be used as alternate antibiotics, pesticides, insecticides, growth promoters.

Beneficial microorganisms can be used as Anifungals Antibiotic s Antivirals Enzyme producers FCR Improvers Growth promoters Gut acidifiers Immuno modulators Insecticides Meat tenderizers Oxygen liberators Parasiticides Pesticides Pollutant degraders Protozoacides Toxin binders Zoothamnicides

Role of Probiotics To combat diseases like as Irritable Bowel Syndrome (IBS), dyspepsia, chronic

diarrhea or constipation. To curdle milk To detoxify To eliminate pathogens To exist symbiotically To fight against certain cancers. To help in Lactic intolerance To help in producing short chain fatty acids (SCFAs) To help liver and kidneys in discharging their functions To help regulate the immune response To improve mineral absorption To improve Total digestible Nutrients (TDN) of the food intake. To inhibit LDL accumulation To maintain optimum micro flora

To reduce Triglycerides To reduce the stress owing to high levels of Antibiotics

Activities of Probiotic Bacteria Anti colon cancer effects Anti Milk allergy Anti-diarrheal effects Cholesterol lowering Correction of Hypertension Immune system modulation Improved tolerance to milk Intestinal health maintenance Reduction of Lactose intolerance Suppression of harmful intestinal microbe activities Suppression of pathogen translocation Vaginal/urinary tract health maintenance

Of the 18 authorised probiotics in the EU, 12 are authorised for pig feed (10 are approved for  piglets, 6 for sows and 5 for fattening pigs). The micro-organisms for pig feed are of various origins. Most preparations contain defined strains of bacteria and only three of them contain yeasts. Bacillus strains are spore forming bacteria and are applied as spore preparations while enterococci and pediococci do not form spores and are applied as desiccated vegetative cells. Therefore, Bacillus probiotics are much more stable during feed processing (including pelleting and during in-feed storage). We have found that the recovery of B. cereus var. toyoi was 95% after pelleting (conditioner 80°C, dye 87°C), while the recovery of viable counts of an E. faecium strain decreased with increasing treatment temperature (Figure 1). However, the stability of vegetative cells can be improved by various techniques (soaking on globuli, coating). Although viability losses can be compensated by initial overdosing during feed production if the rate of inactivation is known, storage of the complete feed is still a matter of concern. Bacterial spores, on the other hand, are remarkably stable during storage in pelleted feed (Figure 2 ). Yeasts are the most sensitive to heat treatment. Probably influenced by their stability characteristics, sales volume of used probiotic organisms in pig feeding can be categorised as follows: Bacillus spore probiotics > Enterococcus strains (lactic acid bacteria) > yeast probiotics (viable cells).

The European Union has not yet implemented regulations for the risk assessment of genetically modified microorganisms (GMO) in animal nutrition.Especially when GMOs are used to deliver drugs or vaccines, they could not be regulated as feed additives but have to be treated as therapeutic agents.(http://www.allaboutfeed.net/article-database/potentials-of-probiotics-in-pig-nutrition-id1140.html)

In Japan a standard was developed by the Fermented Milks and Lactic Acid Bacteria Beverages Association stipulating that a product contain 1 x 107 viable bifidobacteria/g or mL product to be considered a probiotic food.

Complete Ban on All Growth-promoting Antimicrobials in the EU Drives Growth in the Animal Feed Probiotics Market.

A huge demand for phytase is predicted in the future. This is a result of the Environmental Protection Agency's (EPA) concerns about chemical emissions from the agricultural industry. Farmers are also looking to reduce phosphate content in animal wastes. Thus, the most rapid growth is expected in the area of animal feed enzymes led by phytase.

Global market for chemotherapeutic drugs which either kill parasite populations or prevent the development of immature parasites into adult forms, is worth almost $4.7 billion, making it the single most valuable sector of the animal health products market.At the moment very few companies like DVS BioLife Ltd employ probiotics for controlling internal and external parasites.

The global market for nutraceuticals for companion animals was estimated in excess of $1 billion in 2006. Several algae like spirulina, chlorella, Dunaliella Salina are employed.

The global probiotics market is estimated to grow at a CAGR of around 13% from 2009-2014 and Europe and Asia would be occupying the maximum market share by the end of 2014.

There is good in vitro evidence that certain probiotic strains can inhibit thegrowth and adhesion of a range of enteropathogens (Coconnier et al., 1993, 1997;Hudault et al., 1997; Gopal et al., 2001; Bernet Camard et al., 1997), and animal studieshave indicated beneficial effects against pathogens such as Salmonella (Ogawa et al.,2001; Shu et al., 2000).

The intestinal microflora likely plays a critical role in inflammatory conditions inthe gut, and potentially probiotics could remediate such conditions through modulation ofthe microflora.

Administration of lactobacilli and bifidobacteria could theoretically modify the flora leading to decreased β-glucuronidase and carcinogen levels (Hosada et al., 1996). Furthermore, there is some evidence that cancer recurrences at other sites, such as the urinary bladder can be reduced by intestinal instillation of probiotics including L. casei Shirota (Aso et al., 1995). In vitro studies with L. rhamnosus GG and bifidobacteria and an in vivo study using L. rhamnosus strains GG and LC-705 as well as Propionibacterium sp. showed a decrease in availability of carcinogenic aflatoxin in the lumen (El-Nezami et al., 2000; Oatley et al., 2000).(http://www.who.int/foodsafety/publications/fs_management/en/probiotics.pdf)

Intravenous, intraperitoneal and intrapleural injection of L. casei Shirota into mice significantly increased NK activity of mesenteric node cells but not of Peyer's patch cells or of spleen cells (Matsuzaki and Chin, 2000), supporting the concept that some probiotic strains can enhance the innate immune response.(Joint FAO/WHO Expert Consultation on Evaluation of Health and Nutritional Properties of Probiotics in Food Including Powder Milk with Live Lactic Acid Bacteria, October 2001)

In a series of randomized, double blind, placebo controlled clinical trials, it was demonstrated that dietary consumption of B.lactis HN019 and L. rhamnosus HN001 resulted in measurable enhancement of immune parameters in the elderly

(Arunachalam et al., 2000; Gill et al., 2001; Sheih et al., 2001).

Some probiotic strains were shown to inhibit the growth of enteropathogens, such as Salmonella enteritidis, enterotoxigenic Escherichia coli, and Serratia marcesens, in vitro (48, 49) and in this respect may offer considerable therapeutic potential. This finding,

together with more recent evidence showing that Lactobacillus GG exerts antagonist activity against Salmonella typhimurium C5 infection both in vitro and in vivo (50), provides a basis for the clinical use of probiotics in suppression of pathogens.(http://www.ajcn.org/cgi/content/full/73/2/476S)

Potential for probiotics microorganisms to modulate the immune response and prevent onset of allergic diseases has been demonstrated.

Ability of lactobacilli to reverse increased intestinal permeability, enhance gut-specific IgA responses, promote gut barrier function through restoration of normal microbes, and enhance transforming growth factor beta and interleukin 10 production as well as cytokines that promote production of IgE antibodies (Kalliomaki et al., 2001; Isolauri, 2001).

Certain microorganisms can contribute to the generation of counter-regulatory T-helper cell immune responses, indicating that use of specific probiotic microorganisms could redirect the polarized immunological memory to a healthy one (McCracken and Lorenz, 2001).

There is preliminary evidence that use of probiotic lactobacilli and metabolic by-productspotentially confer benefits to the heart, including prevention and therapy of variousischemic heart syndromes (Oxman et al., 2001) and lowering serum cholesterol (De Roos and Katan, 2000).

There is some clinical evidence to suggest that oral and vaginal administration of lactobacilli can eradicate asymptomatic (Reid et al., 2001a; 2001b) and symptomatic Bacterial vaginosis(Hilton et al., 1995; Sieber and Dietz, 1998).

One study of day care centres in Finland showed that probiotic use reduced the incidence of respiratory infections and days absent due to ill health (Hatakka et al., 2001).

Probiotic bacteria containing β-galactosidase can be added to food to improve lactosemaldigestion (Kim and Gilliland, 1983).

The global market estimate of functional foods has been up to 73 Billion € and an annular growth rate of 8-16%. In a recent study undertaken by Leatherhead Food RA, the market for functional foods in the United Kingdom, France, Germany, Spain, Belgium, Netherlands, Denmark, Finland, and Sweden was reviewed. The results of the

study showed that the probiotic yogurt market in these 9 countries totalled >250 million kg in 1997 (11), with France representing the largest market, having sales of 90 million kg, valued at US$219 million. The German market for probiotic yogurts is growing

rapidly; for example, during 1996–1997, it increased by 150%, whereas the UK market grew by a more modest 26% during the same period. On average, probiotic yogurts

accounted for 10% of all yogurts sold in the 9 countries studied, with Denmark having the highest proportion (20%) of probiotic yogurts, followed by Germany and the United Kingdom (both at 13%) and then France (11%). On the lower end of the scale were the Netherlands and Belgium (both at 6%) and then Finland and Sweden (both at 5%) (11). Seen as crucial to market expansion in Europe is further clarity on the use of health claims. The market for functional foods in Europe could ultimately account for 5% of total food expenditure in Europe, which, based on current prices, would equate to US$30 billion (5).

This study on the envisaged growth in the consumption of Non Vegetarian Foods and the role of probiotics in improving the scenario is based on the assumptions narrated below.Several factors may influence these observations. Some of them are listed below.

I.II. ASSUMPTIONS IN PREPARING THIS REPORT1. Agricultural support and trade policies influence markets

2. Agricultural production continues to expand, but more slowly

In spite of reduction in the Acreage; production will improve owing to the improved Seeds, fertilizers, pesticides and due to the better package of practices in pre and post harvesting including storage and transporting.

3. Agricultural lands are becoming scarce day by day owing to Submerging in oncoming projects on rivers Conversion into residential and industrial usage Immersion into sea owing to rise in mean sea level caused by ice glacier

melting (Due to Global Warming)

4. Consumption to grow faster in developing countries due to higher earning capacities

5. Despite rekindled fears, inflation expected to remain low

6. Diseases like Asian soya bean rust could change the outlook for oilseed markets

7. Population growth rates to decline World population is projected to soar from 6.1 billion in 2000 to 7.9 billion in 2025 and9.3 billion in 2050 (Sadik 2001).

8. Sustained, broad-based growth in farm animals is expected in the medium to longer term

I. III. FACTORS THAT MAY INFLUENCE THE DEMAND OF NON VEGETARIAN FOOD

1. Climatic changes2. Changes in Food habits

3. Increase in Population 4. Urbanization

I. IV. FACTORS THAT MAY INFLUENCE THE SUPPLY OF NON VEGETARIAN FOOD

1. Climatic changes2. Improvements in Feed Technology4. GM in Poultry and other Breeds6. Change in the Priorities in feeding stuff7. Change of size and concept of operators like a shift from small families to small companies8. Better usage of land and water resources

I. V. FACTORS THAT MAY INFLUENCE THE AVAILABILITY OF FEEDING STUFF FOR USE IN ANIMAL FEEDS

1. Demand for biofuels such as ethanol from grain 2. Demand for biodiesel from edible oil 3. Demand for human consumption.4. Conversion of Lands used to produce Grains and Oil Seeds to better

remunerating crops like Horticulture, Flowers, Vegetables, Medicinal Herbs etc.

I. VI. FACTORS THAT MAKE USAGE OF PROBIOTICS AS THE ONLY BEST ALTERNATIVE

Abuse of Antibiotics Abuse of Growth promoting antibiotics and chemicals Abuse of Hormones Abuse of Pesticides, insecticides Abuse of dewormers, parasiticides, disinfectants, sanitizers etc

Table I.01.

When GDP increases to developing country status, growth in meat consumption rises quickly reflecting consumer desires. In many countries, per capita income levels have more than doubled over the past two decades.

Table I. 02. Average annual percentage increase over 10 year period

1995-2004 2005-2014 1995-2004 2005-2014Population Income% % % %

World 1.27 1.01 2.62 3.10Africa 2.28 1.83 3.37 3.80America 1.36 1.04 3.02 3.24Asia 1.29 1.02 2.61 3.56Europe 0.01 -0.07 2.13 2.40Oceania 1.15 0.73 3.51 3.53Note: Income is at 1995 USD market prices.Source: World Bank, December 2004.

World population is projected to soar from 6.1 billion in 2000 to 7.9 billion in 2025 and 9.3 billion in 2050

(Sadik 2001). Countries with large population bases and high growth rates are Indonesia- 240 m, 1.5%, India -

1,065 m, 1.4%, Pakistan - 161 m, 2.0%, Bangladesh -143 m , 2.1% and Brazil - 185 m 1.1% (Anon, 2007).

A 10% increase in income would result in a 1% increase in food expenditure in the U.S., a 6.5% increase in the Philippines and 18% in Tanzania (Seale and Bernstein, 2003).

Table I.03As per CFLMA, Indian feed production details are as follows.

Species Year Feed in KgBroiler 2004 6.2 x 109

Layer 2004 8.1 x 109

Cattle 2004 4 x 109

Shrimp 2005 0.307 x 109

Fish 2004 0.01 x 109

It is estimated that the real productions by 2014 will be enhanced at an average growth rate of 9.25%

The top 15 countries that produce animal feed accounted for 73% of a total production of 625 mmt in 2005 (Gill, 2007).

Table I. 04. Production and consumption average annual growth rates, 2004-2014PRODUCTION CONSUMPTIONTotal OECD NON-OECD Total OECD NON-OECD

% %Beef 1.6 0.7 2.6 1.6 0.6 2.3Pig meat 1.8 0.8 2.6 1.8 0.8 2.3Poultry meat 2.2 1.8 3.0 2.2 1.8 2.5Milk 1.9 0.9 3.0 .. .. ..Butter 1.7 -0.3 3.4 1.8 -0.3 2.9Cheese 1.8 1.8 2.8 1.9 1.6 2.7Skim milk powder -0.5 -1.3 2.5 -0.9 -2.5 1.3Whole milk powder 2.0 1.2 3.4 2.0 -0.3 2.6Source: OECD and FAO Secretariats

Table I. 05. Per capita consumption for selected commoditiesAverage annual growth (%) (1)

2002-04 2014 1995-04 2005-14WorldMeat 31.2 34.5 3.38 0.88

OECDMeat 64.5 69.9 7.03 0.73

Non-OECDMeat 23.2 26.5 1.64 1.18

Note: (1) The least squares growth rate, r is estimated by fitting a linear regression trend line as follows:Ln(xt)=a+r*tEconometrics and models and Econometrics forecasts, Robert S. Pindyck.Source: OECD and FAO Secretariats.

Table I.06.

Table I.07. Production of Milk and EggsFAO

Statistical Yearbook

PRODUCTION OF MILK PRODUCTION OF EGGS

2009 (1000 tonnes) (1000 tonnes)

COUNTRIES 1994-1996

1999-2001

2005 2006 2007 1994-1996

1999-2001

2005 2006 2007

Afghanistan 2 1379.866

71745.033 1730.7 1627.9 1673.9 15.86666

715.47 21.824 14.688 16.858

Albania 3 938.38367

946.34033

1076.007 1102.007 1016.007 14.143333

21.733333

27.3 26.5 27.2

Algeria 4 1148.1333

1513.218 1694.209 1995.693 2045 110.66667

100.66667

175 178 185

American Samoa

5 0.016 0.016 0.016 0.016 0.022 0.03 0.03 0.03 0.03 0.03

Angola 7 151.66667

193.66667

195 195 195 4.1333333

4.3333333

5.2 4.3 4.3

Antigua and Barbuda

8 5.8333333

5.3 5.35 5.35 5.4 0.19 0.22 0.25 0.25 0.25

Argentina 9 8642.873 10179.752

9908.941 10493.569

10500 281.12333

315.907 310 484.2 480

Armenia 1 424.96 457.882 594.6 620 642 11.067667

21.666333

29.053 25.98 29.442

Australia 10 8591 10849.667

10089 9583 9223 138.6 144.33333

138.6 180.3 170.2

Austria 11 3173.6173

3353.7447

3135.852 3168.555 3179.995 102.338 88.082667

89.271 90.613 95.197

Azerbaijan 52 817.83333

1032.7333

1251.935 1299.509 1341.278 27.300333

30.473667

49.167 45.831 52.66

Bahamas 12 1.59 1.575 1.8 1.75 1.75 0.66 0.9336667

0.85 0.9 0.9

Bahrain 13 17.145667

16.063667

15.224 13.13 10.93 2.9966667

2.6213333

2.45 2.45 2.45

Bangladesh 16 1989.8533

2133.2767

2615.93 2752.54 2897.15 131.36667

178.46667

263.7 253.9 256

Barbados 14 7.839 8.0566667

6.785 6.85 6.9 1.221 1.25 1.95 2 2.05

Belarus 57 5162.8333

4688.1667

5675.6 5895.4 5903.5 190.80467

183.695 173.98 187.18 181.1

Belgium 255 3691.5 3025 3012 3000 203.375 179.81 194 174.2Belize 23 1.276 1.441333

33.786 3.014 2.706 1.488 1.717666

71.472 1.616 1.805

Benin 53 24.213333

29.371667

34.722 35.638 36.53 6.444 7.2 9.36 10.08 10.845

Bhutan 18 41.288667

41.448 41.44 41.42 41.42 0.3566667

0.3466667

0.24 0.24 0.24

Bolivia 19 215.64567

251.06567

355.65 294.839 301.709 65.666667

39.617333

53.89 59.315 62.585

Bosnia and Herzegovina

80 360.36667

550.03333

667.7 703.52 767.826 9.3 17.266667

17.619 17 20.34

Botswana 20 100.91667

114.375 116.75 105.35 105.4 2.0333333

3.2 4.2 3.15 3.15

Brazil 21 17590.6 20537.669

25519.106

26320.564

27080.564

1421.1823

1561.5357

1749.747 1834.564 1857.817

Brunei Darussalam

26 0.04 0.1463333

0.103 0.077 0.075 3.99 4.7666667

5.703 6.512 7.35

Bulgaria 27 1448.3 1587.8303

1508.069 1515.673 1327.461 101.94367

87.036667

97.546 100.584 98.821

Burkina Faso

233 139.61267

173.16 214.775 224.153 233.947 34.379333

39.357333

45.045 46.27 47.53

Burundi 29 37.71333 29.32666 25.2 20.919 28.692 3.516666 3.133333 3.05 3 3

3 7 7 3Cambodia 115 19.074 20.4 21.658 22.746 23.12 13.31666

714.95 17.05 17.05 17.05

Cameroon 32 182.33333

188.36667

194.3 194.3 194.3 13 12.933333

13.4 13.4 13.4

Canada 33 7853.3333

8143.6667

7806 8041 8145 326.13 370.60033

399.26 399.612 398.436

Cape Verde 35 8.4726667

10.033333

14.6 16.6 18.55 1.9333333

1.9 1.77 1.835 1.95

Central African Republic

37 52.691667

62.766667

66.5 66.5 65 1.38 1.4366667

1.48 1.48 1.48

Chad 39 173.9 219.78333

243.459 248.628 254.52 3.6 3.552 3.744 3.78 3.888

Chile 40 1864.6667

2086.5667

2309.9 2409.9 2460 94.323333

109.94167

126.4 124.35 137.2

China 351 9443.5513

12711.035

32022.646

36471.845

39823.66 17385.327

22149.827

24725.89 24598.325

25654.35

Colombia 44 5059.4267

6061.2133

6770 5500 4225 319.4 362.19133

491.977 525.5 489.794

Comoros 45 4.4 4.5333333

4.5 4.55 4.55 0.7 0.752 0.776 0.776 0.776

Congo 46 0.9833333

1.05 1.15 1.1 1.1 1.14 1.16 1.2 1.2 1.2

Congo, Democratic Republic of the

250 6.5666667

5.2 5 5 5 8.3 6.9 7 7 7

Costa Rica 48 566.03333

721.90967

779.478 823.814 889.974 45.710333

42.414667

48.167 47.211 41.887

Côte d'Ivoire 107 22.108333

26.465667

29.265 29.85 26.473 16.174667

34.000667

28.712 27.918 25.03

Croatia 98 610.08633

636.14567

812.864 870.135 883.226 49.685 47.606333

49.38 50.736 48.2

Cuba 49 638.20733

618.53933

354.834 416.734 486.98 67.502667

73.321 90.917 103.017 103.475

Cyprus 50 176.26667

190.4 193.42 187.8 183.48 9.5966667

10.794667

9.087 9.5 9.4

Czech Republic

167 3149.6263

2812.2477

2828.297 2768.887 2757.862 151.688 194.35033

89.465 86.675 92.992

Denmark 54 4604.4667

4642.6667

4584 4627 4600 90.9 77.729 79.8 77 78

Dominica 55 6.1066667

6.1 6.1 6.1 6.1 0.225 0.225 0.225 0.225 0.225

Dominican Republic

56 382.985 409.71 751.662 868 872 45.013 59.403667

80.219 86.097 86.042

Ecuador 58 1908.307 2132.6863

4578.78 5188.069 4768.418 55.953333

66.705333

75.014 76 77.5

Egypt 59 2814.7627

3812.817 4508.1 4558.1 4608.1 159.39167

176.522 240 240 240

El Salvador 60 315.70967

376.816 447.6 492.478 535.664 44.22 58.297 67.409 69.228 70

Equatorial Guinea

61 0.19 0.19 0.19 0.19 0.19

Eritrea 178 48.819667

69.183333

58.8 56.725 56.8 4.6013333

1.768 2 1.978 2

Estonia 63 718.264 646.976 670.427 691.966 692.416 20.56 16.764667

13.063 11.414 9.848

Ethiopia 238 1038.1997

1448.5787

1827.7 1931.55 1931.2 28.493 31.724333

36.624 36.624 38

Fiji 66 63.987 56 57 57.5 58 2.6486667

3.002 3.791 3.522 3.438

Finland 67 2470.2033

2460.9667

2433.19 2412.981 2355.6 72.4 57.986667

58.2 56.7 56.9

France 68 25954.222

25679.766

25713.949

25040.681

25216.7 1000.12 1036.1333

930.1 908.3 878.4

French Polynesia

70 1.4593333

1.246 1.096 1.35 1.35 1.5573333

1.7513333

2.5 2.042 2.043

Gabon 74 1.4416667

1.575 1.575 1.575 1.6 1.74 1.98 1.98 1.98 2

Gambia 75 7.3496667

7.618 7.7 7.8 7.9 0.5906667

0.715 0.748 0.78 0.83

Georgia 73 478.33333

663.117 787.73 617.3 638.8 16.271 21.445333

28.3 14.2 24.43

Germany 79 28440.295

28307.476

28487.95 28030 28438 840.33333

887.33333

795 787 786

Ghana 81 27.148333

33.8 36.01 36.53 37.12 13.559 21.288333

25.175 25.71 26.37

Greece 84 1960.4737

2012.501 2054.398 2077.007 2019.633 117.07167

115.31867

110.1 99.48 96.9

Guatemala 89 307.39933

264.97167

297.449 337.239 340 92.405667

81.31 85 85 85

Guinea 90 61.560667

79.022667

100.961 99.309 104.648 9.66 12.285 18.585 19.705 20.895

Guinea-Bissau

175 16.922 17.660667

19.03 19.83 20.817 0.608 0.96 1.128 1.2 1.248

Guyana 91 18.253333

30 30 30 30 1.4486667

1.3586667

1.206 0.27 0.492

Haiti 93 57.763333

63.05 70.35 69.5 69.5 4.25 4.5833333

5.045 5.05 5.05

Honduras 95 465.58167

575.84933

663.05 661.8 661.8 35.583333

42.150333

40.912 41 41

Hungary 97 1976.5153

2142.6783

1936.928 1851.069 1848.564 197.118 181.47467

168.845 168.421 160.665

Iceland 99 105.42267

105.78 109.445 117.541 126.358 2.207 2.4876667

2.8 2.634 2.91

India 100 65040.333

80440.333

95619 100900 106100 1479 1940 2539 2604 2670

Indonesia 101 732.26333

760.90067

850.45 944.249 923.883 734.83633

757.91733

1051.54 1204.417 1382.134

Iran, Islamic Republic of

102 4603.003 5807.41 7002.432 7488.467 7635.5 500.66667

576.56667

758 677 711

Iraq 103 402.40667

653.175 767.08 538.675 629.765 22.966667

26.93 77.12 51.7 50

Ireland 104 5326.8 5220.896 5378 5400 5200 32.633333

31.787 37.5 34 33

Israel 105 1175.5833

1222.9677

1216.274 1188.2 1226.201 101.08667

88.116667

92.4 93.52 93.5

Italy 106 12207 12871.854

11862.634

11868.176

11865 718.93333

709.16667

722.2 690 700

Jamaica 109 167.82533

180.799 178.821 178.466 179.094 6.017 7.012 5.096 8.636 6.32

Japan 110 8476 8419.2313

8285.215 8133.907 8024 2560.8433

2531.323 2482.643 2496.648 2525

Jordan 112 154.85233

193.441 277.887 309.879 313.4 47.779333

49.431333

40.614 44.68 45

Kazakhstan 108 4514.079 3729.436 4749 4926.9 5073.2 107.39667

94.491667

140.57 139.813 149.24

Kenya 114 2134.5 2505.0167

2835.2 3668.2 4401.5 48.833333

58.483333

57.85 66.7 68.6

Korea, Democratic People's Republic of

116 85 89.333333

94 96 96 69.666667

104.16667

140 142 142

Korea, Republic of

117 1989.6287

2282.6783

2233.991 2189.197 2193.225 461.559 511.63467

542.862 583 573.5

Kuwait 118 35.871 39.309333

47.63 45.04 45.04 10.782667

21.177333

26 22 22

Kyrgyzstan 113 873.7 1103.888 1197.66 1212.156 1240.035 9.509 11.741 17.795 19.232 20.945Lao People's Democratic Republic

120 5.6 5.9333333

6.4 6.6 6.7 5.1066667

10.264 12.806 13.105 13.105

Latvia 119 957.17833

823.88467

810.284 815.072 841.646 23.426 24.996333

33.445 35.76 42.236

Lebanon 121 210.08767

208.10733

251.9 241 241 27.286667

43.6 45.48 47 47

Lesotho 122 26.196667

32.5 35 24 25 1.2566667

1.4666667

1.55 1.5 1.6

Liberia 123 0.715 0.715 0.715 0.735 0.745 4.05 4.2833333

4.35 4.7 4.97

Libyan Arab Jamahiriya

124 160.03 196.84733

203.408 203.4 203.4 42.333333

56.28 60 60 60

Lithuania 126 1857.5667

1722.9067

1861.57 1891.295 1936.612 42.153333

43.250667

53.246 56.815 58.6

Luxembourg 256 267.115 269.711 268.073 274.243 1 1.291 1.24 1.227Macedonia, The Former Yugoslav Republic of

154 194.807 252.186 276.164 321.29 451.79 23.81 22.866667

19.02 18.51 17.98

Madagascar 129 508.33333

515 510 520 520 15.601333

18.985333

19.436 19.5 19.5

Malawi 130 31.5 34.666667

42.541 25.472 29.739 17.633333

19.4 20.2 19.5 19.5

Malaysia 131 43.925 36.541 45.735 46.2 46.8 365.623 402.83433

453 464 476

Mali 133 420.47567

487.87267

627.432 669.704 717.398 11.88 11.88 10.08 10.36 10.5

Malta 134 33.283333

51.862333

44.497 44.415 43.962 7.0233333

6.0023333

5.884 7.285 7.638

Mauritania 136 287.58333

323.98333

356.549 354.8 355 4.5933333

5.0433333

5.27 5.27 5.27

Mauritius 137 7.3666667

4.5666667

4 4 3.5 4.7 5.55 7 6.9 7

Mexico 138 7569.5123

9354.3653

10032.548

10252.509

10513.405

1241.3607

1771.625 2024.723 2290.062 2290.833

Moldova, Republic of

146 829.77133

580.74867

658.57 627.491 603.906 19.654667

32.617 42.65 42.835 39.435

Mongolia 141 321.059 436.28667

359 398.6 414.1 0.224 0.4313333

0.45 0.4 0.4

Montenegro 273 183.3 178.02 2.34 3.565Morocco 143 923.4333

31226.566

71464.7 1564.8 1664.8 193.3333

3238.3333

3195 168 200

Mozambique 144 65.808333

69.319667

77.85 76.5 74.8 11.9 14 14.6 14 14

Myanmar 28 556.91267

619.32867

989.8 1094.815 1215.626 53.706 109.58733

200.839 226.724 248.962

Namibia 147 73.333333

87.666667

150 110 110 2.0913333

2.4866667

3.54 3.44 3.44

Nepal 149 1007.514 1171.9333

1352.428 1390.64 1432.394 19.601667

24.658667

29.776 30.31 30.998

Netherlands 150 11059.727

11099.667

10847 10500 10750 607.33333

657.33333

607 611 621

New Caledonia

153 3.42 3.1 0.804 0.789 0.8 1.351 1.52 1.853 1.951 2

New Zealand 156 9702.3333

12078.737

14637.894

15332.067

15841.624

44 45.423333

53.382 53.5 71.842

Nicaragua 157 190.111 541.492 614.118 664.545 708.405 27.524667

19.308333

20.357 21.053 21.456

Niger 158 396.76667

500.76667

631.76 656 683.6 7.285 7.77 8.29 7.46 7.56

Nigeria 159 380 388.05833

438.5 462.7 468.24 377.66667

425 500.4 526.4 552.8

Norway 162 1939.3 1811.1667

1588.188 1574.599 1616.479 50.036333

47.448 50.702 50.815 52.831

Occupied Palestinian Territory

299 112.69567

135.66933

186.875 190.642 204 21.321667

34.688667

37.393 37.94 38.49

Oman 221 94.112 108.95533

134.72 136 136.63 6.22 7.1883333

9.5 9 9

Pakistan 165 19994 25575.333

29438 31214 32219 279.48333

347.27333

408.063 463.664 486.459

Panama 166 156.72767

169.82933

181.048 178.592 180.225 13.098333

16.731333

28.141 25.657 27.3

Papua New Guinea

168 0.164 0.1716667

0.2 0.2 0.2 4.4633333

5.65 6.2 4.91 4.91

Paraguay 169 350.88367

368.6 372.38 372.38 375 44.1 79.223 100.82 100.82 100.82

Peru 170 883.17633

1084.755 1350.335 1503.923 1600.834 119.76567

158.60433

182.291 245.451 257.621

Philippines 171 11.903333

10.286667

13 13 13 450.66667

514.93333

594 592 603

Poland 173 11855.289

12020.28 11945.565

12003.415

12117.311

355.04367

429.32033

535.995 537.232 546.748

Portugal 174 1785.163 2102.1403

2119.926 1976.107 2049.264 104.62233

117.55033

120.908 121.65 119.569

Qatar 179 33.219 32.361667

19.75 20.15 21.1 3.4873333

3.1773333

4.142 4.2 4.2

Romania 183 4931.3013

4701.5357

5552.2 6662.242 6289.845 285.21 301.30967

365.5 371.45 326.124

Russian Federation

185 39098.856

32493.698

31147.165

31436.278

32175.485

1928.7667

1910.2367

2065.4 2116.8 2122.93

Rwanda 184 96.76 125.7 147.1 143.92 143.92 1.95 2.2 2.3 2.3 2.3Saint Kitts and Nevis

188 0.3333333

0.24 0.22 0.22 0.22

Saint Lucia 189 1.1166667

0.9333333

1 1 1.05 0.542 0.516 1.4 1.05 1.1

Saint Vincent and the Grenadines

191 1.3566667

1.3666667

1.2 1.2 1.3 0.64 0.64 0.625 0.63 0.65

Samoa 244 1.3 1.4833333

1.5 1.5 1.5 0.2333333

0.2716667

0.33 0.26 0.26

Sao Tome and Principe

193 0.1286667

0.1393333

0.146 0.146 0.147 0.2623333

0.3673333

0.472 0.472 0.49

Saudi Arabia 194 657.94867

919.7 1196 1216 1242 127.805 134.03433

169.548 170.5 174

Senegal 195 106.50467

117.99667

116.131 120.152 122.329 11.266667

17.266667

27 28 31.5

Serbia 272 1651.333 1634.5 72.8 68Serbia and Montenegro

186 1998.0333

1866.1333

1858.665 87.233333

73.076 76.598

Seychelles 196 0.3833333

0.31 0.31 0.31 0.31 1.8086667

2.1586667

2.217 2.182 2.212

Sierra Leone 197 17.666667

9.3333333

13.25 18.5 18.5 6.91 7.7486667

8.865 8.865 8.865

Singapore 200 18.617 17.2 21.811 22.455 23.605Slovakia 199 1185.36 1149.21 1118.254 1108.611 1091.664 91.01333

365.08133

367.366 75.3 77.45

Slovenia 198 594.26833

648.08033

661.414 644.634 668.95 19.905 23.020667

14.33 15.801 19.345

Solomon Islands

25 1.235 1.3 1.365 1.4 1.4 0.34 0.4426667

0.48 0.5 0.51

Somalia 201 2213.6667

2102.8333

2210.86 2168.14 2166 2.3166667

2.48 2.687 2.54 2.54

South Africa 202 2627.3333

2655.3333

2870.87 2970.965 3000 258.66667

323.65 365.5 414 435

Spain 203 6762.34 7067.974 7469.409 7323.136 6998.5 588.12667

634.64267

710.456 709.305 706.84

Sri Lanka 38 286.69567

158.53333

167.524 171.17 175.61 48.852333

52.371 49.072 51.153 51.963

Sudan 206 4345.25 5773 7586 7308 7356 38.816667

44.833333

47 47 47

Suriname 207 18 9.8333333

8.5 8.5 8.5 3.5 2.7666667

2.5 2.5 2.5

Swaziland 209 38.466667

36.333333

38.7 37.5 39 0.3383333

0.9666667

1.25 1.05 1.05

Sweden 210 3327.6667

3328.6667

3206 3175 3200 106.03733

102.3 102 99 102

Switzerland 211 3903.3333

3914.4 3957 3957.5 4008.2 36.526 36.686667

38.879 38.77 38.932

Syrian Arab Republic

212 1383.0447

1635.6897

2354.13 2532.485 2678.1 105.659 128.26933

155.205 189.04 171.5

Tajikistan 208 343.63333

331.56667

533.03 544.9 583.6 3.2336667

1.4966667

5.53 5.89 6.18

Tanzania, United Republic of

215 670.18667

833.26667

944 944 955 36.162667

35.398333

36.745 36.75 36.75

Thailand 216 285.34133

524.10967

888.22 826.464 822.211 776.5 792.40033

778.709 823.274 570.4

Timor-Leste 176 1.075 0.6916667

0.475 0.475 0.375 1.1866667

1.36 2.8 1.6 1.6

Togo 217 7.6046667

7.815 9.022 9.292 9.585 6.325 6.325 6.44 7.25 8.05

Tonga 219 0.175 0.3063333

0.37 0.37 0.37 0.2733333

0.28 0.28 0.28 0.3

Trinidad and Tobago

220 9.3896667

10.357 10.5 10.5 11 2.9623333

3.3106667

3.8 3.8 3.85

Tunisia 222 594.33333

908.26667

931.1 988.5 1013.8 59.966667

82.666667

84 80 85

Turkey 223 10641.127

9790.504 11107.896

11952.1 12329.789

558.23333

770.31333

753.278 733.348 795.31

Turkmenistan

213 732.36667

1038.1333

1869 1197 1332.8 15.239 20.566667

45.43 37.265 34.155

Uganda 226 456.16667

510.41667

735 735 735 17.4 19.866667

20 20 21

Ukraine 230 17075.5 13149.467

13714.36 13287 12262.15 545.91133

520.37467

756.3 825.7 814.8

United Arab Emirates

225 59.515 82.44 98.85 100 100 12.394333

14.898 17 17 17.2

United Kingdom

229 14881.1 14736.333

14473 14316 14023 636.83333

600.50667

625 610.648 593.171

United States of America

231 69989 74940.333

80254.464

82463.032

84189.064

4440 4998.8 5333.4 5360 5308

Uruguay 234 1248.9203

1468.9103

1619 1620 1576 31.531333

35.2 41.558 42.295 43.6

Uzbekistan 235 3554.6333

3593.4 4554.879 4855.781 5097.65 72.437 70.828333

110.931 119.624 124.43

Vanuatu 155 2.9 2.9666667

3 3.1 3.2 0.28 0.32 0.36 0.36 0.37

Venezuela 236 1415.9717

1388.972 1347.662 1431.152 1703.544 143.13367

177.00833

173.6 160.514 149.648

Viet Nam 237 66.133333

82.950333

228.679 246.953 266.438 141.1 186.02433

197 226 254

Yemen 249 206.92867

249.01733

299.028 308.402 318.1 18.55 31.411333

48.36 50.752 51.6

Zambia 251 81 72 84 81 84 32.266667

43.866667

46.8 46.4 46.9

Zimbabwe 181 346.66667

306.66667

242 250 250 19 21.366667

26.8 22 22

World 5001

539787.21

579847.35

647794.07

665277.41

679206.93

47210.534

55137.817

61137.334

62154.977

63410.639

Table I.08. Production of Pig Meat and Chicken Meat

FAO Statistical Yearbook

PRODUCTION OF PIG

MEAT

PRODUCTION OF

CHICKEN MEAT

2009 (1000 tonnes) (1000 tonnes)

COUNTRIES 1994-1996 1999-2001

2005 2006 2007 1994-1996 1999-2001

2005 2006 2007

Afghanistan 2 12 13 32 34 18

Albania 3 11 7 11 11 10 4 4 9 10 10

Algeria 4 0 0 0 0 0 211 236 253 253 250

American Samoa 5 0 0 0 0 0 0 0 0 0 0

Angola 7 26 29 28 28 28 7 8 9 9 9

Antigua and Barbuda 8 0 0 0 0 0 0 0 0 0 0

Argentina 9 207 209 185 225 230 743 950 1,010 1,159 1,160

Armenia 1 6 9 9 14 13 5 3 5 5 6

Australia 10 343 364 391 386 384 472 601 760 773 812

Austria 11 586 639 642 514 536 82 87 89 85 95

Azerbaijan 52 2 1 2 1 1 15 18 35 36 49

Bahamas 12 0 0 0 0 0 7 8 8 8 8

Bahrain 13 5 5 5 6 5

Bangladesh 16 83 94 130 138 147

Barbados 14 3 2 3 3 3 11 11 14 14 14

Belarus 57 263 305 321 346 372 77 77 115 145 165

Belgium 255 1,052 1,013 1,006 1,063 403 450 484 448

Belize 23 1 1 1 1 1 7 9 14 14 13

Benin 53 7 3 4 4 4 11 12 15 16 17

Bhutan 18 1 1 1 1 1 0 0 0 0 0

Bolivia 19 63 82 108 108 108 96 133 154 133 133

Bosnia and Herzegovina

80 10 6 9 10 9 11 6 12 14 20

Botswana 20 0 1 0 0 0 7 8 5 5 5

Brazil 21 2,600 2,546 3,110 2,298 2,480 3,838 5,905 8,830 8,164 8,988

Brunei Darussalam 26 0 0 0 0 0 4 11 14 16 18

Bulgaria 27 239 249 75 75 76 91 107 80 87 98

Burkina Faso 233 12 20 33 36 40 23 26 31 32 33

Burundi 29 5 4 6 1 2 6 6 7 6 6

Cambodia 115 83 105 135 139 141 16 20 17 17 17

Cameroon 32 12 15 16 16 16 22 27 30 30 30

Canada 33 1,244 1,646 1,920 1,898 1,894 729 908 1,000 997 1,030

Cape Verde 35 5 7 7 7 8 1 0 0 0 0

Central African Republic

37 10 12 14 14 14 3 3 4 4 4

Chad 39 0 0 0 1 1 4 5 5 5 5

Chile 40 173 269 411 468 499 291 377 457 523 486

China 351 33,010 40,769 46,622 47,591 43,951 5,783 8,695 9,964 10,164 10,617

Colombia 44 132 103 128 135 158 505 532 763 836 910

Comoros 45 0 1 1 1 1

Congo 46 2 2 2 2 2 6 6 6 6 6

Congo, Democratic Republic of the

250 28 26 24 24 24 14 12 11 11 11

Costa Rica 48 22 32 39 41 48 60 75 91 98 107

Côte d'Ivoire 107 11 6 7 7 7 24 21 23 22 23

Croatia 98 57 64 58 58 66 26 25 45 40 42

Cuba 49 113 90 97 100 177 56 73 29 31 34

Cyprus 50 44 51 55 53 55 28 33 33 27 28

Czech Republic 167 492 428 380 359 360 125 201 213 207 201

Denmark 54 1,503 1,661 1,793 1,749 1,802 158 191 183 166 170

Dominica 55 0 0 0 0 0 0 0 0 0 0

Dominican Republic 56 61 61 78 79 79 139 199 297 346 346

Ecuador 58 91 115 165 165 165 119 183 210 300 336

Egypt 59 3 3 2 2 2 306 512 560 616 560

El Salvador 60 12 11 11 14 17 39 65 99 101 107

Equatorial Guinea 61 0 0 0 0 0 0 0 0 0 0

Eritrea 178 4 2 2 2 2

Estonia 63 32 32 40 42 43 5 8 14 12 12

Ethiopia 238 1 1 2 2 2 36 42 43 45 48

Fiji 66 3 4 4 4 4 9 8 12 14 14

Finland 67 170 176 204 208 213 44 69 87 88 95

France 68 2,140 2,327 2,274 2,261 2,281 1,275 1,249 921 819 800

French Polynesia 70 1 1 1 1 1 1 1 1 1 1

Gabon 74 3 3 3 3 3 3 4 4 4 4

Gambia 75 0 0 0 1 1 1 1 1 1 1

Georgia 73 46 37 33 31 21 9 13 17 11 12

Germany 79 3,614 4,053 4,500 4,662 4,985 415 458 605 608 688

Ghana 81 11 10 5 4 4 12 19 29 30 30

Greece 84 136 139 109 108 110 153 108 159 120 145

Guatemala 89 12 24 26 26 27 105 140 151 168 170

Guinea 90 1 2 2 1 1 3 4 6 5 6

Guinea-Bissau 175 10 11 12 12 12 1 1 1 2 2

Guyana 91 1 1 1 1 1 8 12 23 21 25

Haiti 93 23 29 33 33 33 7 8 8 8 8

Honduras 95 8 10 9 9 10 50 70 141 141 145

Hungary 97 619 598 454 489 499 264 267 246 211 196

Iceland 99 3 5 5 6 6 2 3 6 7 8

India 100 495 477 497 497 497 583 1,050 1,900 2,000 2,240

Indonesia 101 611 460 550 588 597 861 770 1,126 1,260 1,296

Iran, Islamic Republic of

102 633 804 1,237 1,360 1,423

Iraq 103 36 69 85 60 97

Ireland 104 213 240 205 209 205 70 89 78 97 100

Israel 105 10 13 19 18 18 163 259 370 402 420

Italy 106 1,375 1,487 1,515 1,559 1,603 810 782 695 628 733

Jamaica 109 7 7 9 8 7 48 78 102 105 107

Japan 110 1,318 1,255 1,245 1,247 1,251 1,248 1,208 1,273 1,367 1,366

Jordan 112 101 115 133 116 133

Kazakhstan 108 127 137 197 193 194 58 32 46 65 64

Kenya 114 9 13 13 17 16 18 16 18 22 24

Korea, Democratic People's Republic of

116 118 140 168 170 175 23 27 35 34 33

Korea, Republic of 117 824 947 899 1,000 1,043 380 380 484 510 513

Kuwait 118 27 38 32 42 42

Kyrgyzstan 113 25 26 19 20 16 4 5 5 5 7

Lao People's Democratic Republic

120 28 30 39 43 47 9 10 15 16 17

Latvia 119 52 33 38 38 40 10 7 17 21 21

Lebanon 121 4 2 1 1 1 59 107 130 137 130

Lesotho 122 2 3 6 4 4 2 2 2 2 2

Liberia 123 4 4 4 5 6 5 6 8 9 9

Libyan Arab Jamahiriya 124 96 99 99 99 100

Lithuania 126 88 83 119 106 99 25 26 57 61 63

Luxembourg 256 12 11 10 10 15 0 0 0

Macedonia, The Former Yugoslav Republic of

154 9 9 9 9 9 5 5 4 4 4

Madagascar 129 63 27 51 53 54 23 32 36 40 40

Malawi 130 14 20 22 21 25 14 15 16 15 15

Malaysia 131 282 168 197 197 192 657 670 860 922 931

Mali 133 2 2 3 3 2 25 29 36 37 38

Malta 134 9 10 9 8 8 5 6 5 4 5

Mauritania 136 4 4 4 4 4

Mauritius 137 1 1 1 1 1 20 23 33 36 40

Mexico 138 902 1,027 1,103 1,109 1,152 1,225 1,828 2,437 2,464 2,542

Moldova, Republic of 146 61 51 40 48 59 22 17 28 31 32

Mongolia 141 1 1 0 0 0 0 0 0 0 0

Montenegro 273 2 2

Morocco 143 1 1 1 1 1 190 255 370 370 380

Mozambique 144 12 13 14 13 13 30 31 34 40 40

Myanmar 28 115 127 328 370 411 98 210 561 650 726

Namibia 147 2 2 2 2 2 3 8 10 5 5

Nepal 149 11 15 16 16 16 9 13 15 16 16

Netherlands 150 1,640 1,589 1,297 1,265 1,290 611 699 628 621 610

New Caledonia 153 1 1 2 2 2 1 1 1 1 1

New Zealand 156 50 47 50 51 51 83 108 157 149 147

Nicaragua 157 5 6 7 7 7 28 47 71 84 90

Niger 158 1 1 1 1 1 10 11 12 14 14

Nigeria 159 129 159 193 201 209 169 172 219 232 243

Norway 162 97 107 113 116 118 29 41 50 55 63

Occupied Palestinian Territory

299 44 74 69 54 69

Oman 221 4 4 6 6 6

Pakistan 165 320 325 384 512 554

Panama 166 17 20 21 25 27 51 80 95 96 97

Papua New Guinea 168 51 60 68 68 68 5 5 6 6 6

Paraguay 169 166 153 152 152 133 31 36 37 37 37

Peru 170 80 91 103 109 115 353 535 733 710 770

Philippines 171 976 1,217 1,415 1,467 1,617 406 539 650 643 662

Poland 173 1,902 1,938 1,956 2,098 2,151 345 589 796 824 825

Portugal 174 315 331 327 339 364 193 228 198 193 200

Qatar 179 4 4 5 5 5

Romania 183 693 519 436 452 470 280 271 309 273 312

Russian Federation 185 1,891 1,517 1,520 1,641 1,873 872 788 1,346 1,580 1,869

Rwanda 184 3 3 6 5 5 1 2 2 2 2

Saint Kitts and Nevis 188 0 0 0 0 0 0 0 0 0 0

Saint Lucia 189 1 1 1 1 1 1 1 1 1 1

Saint Vincent and the Grenadines

191 1 1 1 1 1 0 0 0 0 0

Samoa 244 3 4 4 4 4 0 0 1 0 0

Sao Tome and Principe 193 0 0 0 0 0 0 1 1 1 1

Saudi Arabia 194 311 469 537 548 559

Senegal 195 4 8 10 10 10 16 23 29 32 37

Serbia 272 255 289 75 70

Serbia and Montenegro 186 630 617 562 83 68 67

Seychelles 196 1 1 1 1 1 1 1 1 1 1

Sierra Leone 197 2 2 2 2 2 9 10 11 11 11

Singapore 200 86 25 20 16 19 79 87 76 76 83

Slovakia 199 246 179 140 122 114 38 59 87 86 83

Slovenia 198 65 66 63 61 57 53 45 46 44 53

Solomon Islands 25 2 2 2 2 2 0 0 0 0 0

Somalia 201 0 0 0 0 0 3 3 4 4 4

South Africa 202 124 113 147 151 150 602 805 949 971 974

Spain 203 2,218 2,929 3,168 3,235 3,544 874 985 1,084 1,065 1,131

Sri Lanka 38 2 2 2 2 2 54 67 97 79 100

Sudan 206 25 26 31 30 25

Suriname 207 1 1 2 1 2 4 4 7 6 6

Swaziland 209 1 1 1 1 1 1 5 7 5 5

Sweden 210 312 293 275 264 265 79 93 96 96 97

Switzerland 211 239 229 236 244 242 36 45 58 48 58

Syrian Arab Republic 212 81 108 163 175 175

Tajikistan 208 0 2 3 1 0 0 1 1

Tanzania, United Republic of

215 10 13 13 13 13 32 42 52 53 46

Thailand 216 497 520 669 865 880 909 1,133 950 962 986

Timor-Leste 176 7 7 10 10 10 1 1 2 2 2

Togo 217 5 6 8 8 9 7 12 18 19 21

Tonga 219 1 1 1 2 2 0 0 0 0 0

Trinidad and Tobago 220 2 2 3 3 3 29 38 58 58 60

Tunisia 222 0 0 0 0 0 54 87 87 66 90

Turkey 223 1 0 0 461 618 937 918 1,068

Turkmenistan 213 3 1 0 0 0 3 6 14 14 13

Uganda 226 67 78 98 60 60 36 43 38 38 38

Ukraine 230 837 641 494 526 635 239 212 497 589 689

United Arab Emirates 225 25 28 34 36 36

United Kingdom 229 1,027 906 706 697 739 1,091 1,230 1,334 1,289 1,270

United States of America

231 7,963 8,682 9,383 9,550 9,953 11,508 13,943 15,869 15,930 16,211

Uruguay 234 22 25 20 19 21 39 57 48 63 45

Uzbekistan 235 15 15 16 18 18 17 16 21 23 22

Vanuatu 155 3 3 3 3 3 0 1 1 1 1

Venezuela 236 134 124 126 137 153 439 735 739 707 777

Viet Nam 237 1,006 1,414 2,288 2,505 2,553 129 289 322 344 359

Yemen 249 53 69 113 118 123

Zambia 251 10 10 11 11 11 26 35 39 37 37

Zimbabwe 181 12 21 30 28 28 19 29 53 40 40

World 5001 79,777 90,025 99,197 100,339 99,212 45,972 58,674 71,412 72,396 75,826

Table I.09. Production of Beef and Sheep, Goat Meat

FAO Statistical YearbookPRODUCTION OF CATTLE MEAT

PRODUCTION OF SHEEP AND GOAT MEAT

2009 (1000 tonnes) (1000 tonnes)

COUNTRIES1994-1996

1999-2001

2005 2006 20071994-1996

1999-2001

2005 2006 2007

Afghanistan 129 128 141 117 137 138 172 134 119 109

Albania 31 35 41 49 50 18 19 20 21 20

Algeria 100 118 120 122 121 182 176 191 199 196

American Samoa 0 0 0 0 0

Angola 67 85 85 85 85 7 11 10 11 11

Antigua and Barbuda 1 0 1 1 1 0 0 0 0 0

Argentina 2,722 2,633 2,980 2,800 2,830 84 57 61 61 62

Armenia 31 31 34 40 43 7 6 8 7 7

Australia 1,791 2,039 2,162 2,077 2,226 624 684 615 643 701

Austria 210 207 204 216 218 7 8 7 8 6

Azerbaijan 43 55 71 73 75 24 35 42 44 45

Bahamas 0 0 0 0 0 0 0 0 0 0

Bahrain 1 1 1 1 1 8 7 7 7 7

Bangladesh 149 172 183 184 186 108 131 172 185 198

Barbados 1 1 0 0 0 0 0 0 0 0

Belarus 325 235 256 272 274 4 3 1 1 1

Belgium 280 267 269 273 5 3 1 1

Belize 1 1 2 2 2 0 0 0 0 0

Benin 16 19 22 23 23 6 6 7 7 7

Bhutan 6 5 5 5 5 0 0 0 0 0

Bolivia 140 159 175 170 170 19 22 24 24 24

Bosnia and Herzegovina 17 15 24 22 24 1 1 2 2 2

Botswana 43 30 35 35 35 8 7 7 7 7

Brazil 5,678 6,605 8,592 6,887 7,049 117 101 105 106 120

Brunei Darussalam 1 4 2 3 2 0 0 0 0 0

Bulgaria 76 63 30 23 22 49 56 24 24 21

Burkina Faso 67 84 106 111 116 33 38 44 45 46

Burundi 10 9 11 8 7 5 4 5 3 2

Cambodia 39 52 57 60 61

Cameroon 74 93 94 94 94 28 31 32 32 32

Canada 948 1,263 1,464 1,327 1,279 10 12 18 17 18

Cape Verde 0 0 1 1 1 0 0 1 1 1

Central African Republic 51 62 75 75 74 8 11 13 13 13

Chad 62 76 82 84 86 23 31 35 36 38

Chile 252 223 216 238 242 15 17 15 17 16

China 3,055 4,745 5,357 5,499 5,849 1,682 2,643 3,504 3,642 3,830

Colombia 693 720 792 790 790 13 13 17 13 14

Comoros 1 1 1 1 1 0 0 0 0 0

Congo 1 2 2 2 2 1 1 1 1 1

Congo, Democratic Republic of the 16 14 12 12 12 23 22 21 20 21

Costa Rica 95 80 81 75 81 0 0 0 0 0

Côte d'Ivoire 35 33 30 31 29 11 11 12 12 9

Croatia 25 27 33 59 55 2 3 3 3 3

Cuba 68 76 60 56 54 4 7 10 9 10

Cyprus 5 4 4 4 4 8 11 7 7 7

Czech Republic 168 113 81 80 79 4 2 1 2 2

Denmark 183 155 136 129 130 2 2 2 2 2

Dominica 0 1 1 1 1 0 0 0 0 0

Dominican Republic 80 68 73 84 101 1 1 2 2 2

Ecuador 143 174 209 211 233 7 12 13 13 13

Egypt 223 245 320 320 320 90 78 61 61 61

El Salvador 28 35 27 31 34 0 0 0 0 0

Equatorial Guinea 0 0 0 0 0 0 0 0 0 0

Eritrea 11 16 17 17 17 10 12 13 11 11

Estonia 26 17 13 15 15 1 0 0 1 1

Ethiopia 244 296 350 374 350 61 64 117 134 124

Fiji 9 9 8 8 8 1 1 1 1 1

Finland 100 91 87 87 89 1 1 1 1 1

France 1,682 1,568 1,517 1,473 1,532 150 140 107 107 102

French Polynesia 0 0 0 0 0 0 0 0 0 0

Gabon 1 1 1 1 1 1 1 1 1 1

Gambia 3 3 3 3 3 1 1 1 1 1

Georgia 50 46 49 33 31 8 8 10 3 4

Germany 1,437 1,346 1,167 1,193 1,186 42 46 50 24 26

Ghana 21 23 25 24 24 12 18 22 22 22

Greece 71 63 72 73 73 143 131 150 152 153

Guatemala 53 62 63 65 65 3 2 2 2 2

Guinea 24 32 41 44 47 5 8 11 12 13

Guinea-Bissau 4 4 5 5 5 1 2 2 2 2

Guyana 4 2 2 2 2 1 1 1 1 1

Haiti 27 37 44 42 42 4 7 7 7 7

Honduras 68 55 73 73 75 0 0 0 0 0

Hungary 60 57 32 34 35 2 4 1 1 1

Iceland 3 4 4 3 4 9 9 9 9 9

India 1,365 1,439 1,334 1,289 1,282 663 620 762 774 777

Indonesia 332 329 359 396 339 98 83 117 140 120

Iran, Islamic Republic of 270 276 344 356 360 376 425 462 495 496

Iraq 41 47 44 54 50 29 28 23 28 28

Ireland 486 600 546 572 581 91 84 73 70 66

Israel 42 58 90 108 105 7 8 9 9 9

Italy 1,177 1,150 1,102 1,109 1,119 78 70 62 61 61

Jamaica 16 14 10 6 6 0 1 1 1 1

Japan 586 510 499 497 504 0 0 0 0 0

Jordan 4 6 4 4 4 12 6 10 7 7

Kazakhstan 551 313 348 367 386 208 97 107 115 124

Kenya 244 273 396 430 445 58 62 79 121 124

Korea, Democratic People's Republic of 28 20 21 22 22 6 11 13 14 14

Korea, Republic of 228 294 195 200 219 3 3 3 3 2

Kuwait 2 2 2 2 2 42 33 35 31 31

Kyrgyzstan 84 99 91 91 89 62 45 46 46 45

Lao People's Democratic Republic 12 17 22 23 23 0 0 1 1 1

Latvia 48 21 20 21 23 1 0 0 0 0

Lebanon 21 51 69 53 53 12 13 11 17 17

Lesotho 11 10 10 3 11 6 6 6 7 6

Liberia 1 1 1 1 1 1 1 1 1 2

Libyan Arab Jamahiriya 19 10 6 6 6 38 34 30 34 34

Lithuania 95 67 62 47 56 2 1 1 1 1

Luxembourg 14 17 16 16 0 0 0 0Macedonia, The Former Yugoslav Republic of 7 7 8 7 7 11 5 7 7 6

Madagascar 146 138 134 147 147 10 8 9 9 9

Malawi 18 17 21 24 27 4 8 11 15 18

Malaysia 16 16 22 22 22 1 1 1 1 1

Mali 56 66 108 106 112 42 51 60 73 78

Malta 2 2 1 1 1 0 0 0 0 0

Mauritania 10 19 26 26 26 23 34 39 39 40

Mauritius 3 3 4 2 2 0 0 0 0 0

Mexico 1,369 1,418 1,558 1,613 1,635 67 72 89 91 91

Moldova, Republic of 49 18 16 15 15 3 3 2 2 2

Mongolia 75 95 47 44 47 115 118 102 88 107

Montenegro 3 3 1 1

Morocco 117 140 157 160 169 123 146 137 143 142

Mozambique 14 12 17 16 29 18 25 26 25 26

Myanmar 95 102 106 120 130 8 11 21 24 27

Namibia 48 55 39 36 42 9 11 12 13 13

Nepal 45 48 49 49 50 34 40 44 46 48

Netherlands 588 450 396 384 386 17 18 14 16 17

New Caledonia 4 4 4 3 3 0 0 0 0 0

New Zealand 598 575 652 643 632 524 539 544 544 575

Nicaragua 50 51 76 85 93 0 0 0 0 0

Niger 77 119 170 177 190 52 63 83 85 88

Nigeria 270 285 261 284 287 222 338 394 406 415

Norway 85 91 87 88 85 27 24 26 25 24

Occupied Palestinian Territory 11 12 5 5 5 15 10 16 18 18

Oman 4 4 4 4 4 17 18 33 35 36

Pakistan 338 420 464 632 656 584 468 532 422 407

Panama 62 69 66 67 67

Papua New Guinea 2 3 3 3 3 0 0 0 0 0

Paraguay 193 226 230 232 234 3 3 4 4 4

Peru 106 129 153 163 163 26 38 40 41 41

Philippines 100 188 173 167 175 30 34 36 45 48

Poland 407 350 310 363 380 6 1 1 1 2

Portugal 99 98 118 105 106 27 25 23 25 24

Qatar 0 0 0 0 0 9 7 5 5 5

Romania 212 153 190 159 165 76 54 52 45 55

Russian Federation 2,868 1,878 1,794 1,705 1,690 269 139 152 153 163

Rwanda 11 18 23 22 22 4 3 6 5 5

Saint Kitts and Nevis 0 0 0 0 0 0 0 0 0 0

Saint Lucia 1 1 1 1 1 0 0 0 0 0

Saint Vincent and the Grenadines 0 0 0 0 0 0 0 0 0 0

Samoa 1 1 1 1 1

Sao Tome and Principe 0 0 0 0 0 0 0 0 0 0

Saudi Arabia 25 22 22 23 24 88 98 104 99 99

Senegal 44 46 47 50 39 23 24 28 30 31

Serbia 83 95 20 20

Serbia and Montenegro 222 181 156 29 23 23

Seychelles 0 0 0 0 0 0 0 0 0 0

Sierra Leone 6 5 6 8 8 1 1 2 2 2

Singapore 0 0 0 0 0 0 0 0 0 0

Slovakia 63 45 26 21 23 2 2 2 1 1

Slovenia 52 47 45 39 38 0 1 2 2 2

Solomon Islands 1 1 1 1 1

Somalia 49 61 68 66 66 57 73 92 90 90

South Africa 542 554 705 804 805 145 147 152 154 155

Spain 519 654 715 670 620 240 246 238 226 214

Sri Lanka 26 27 29 26 24 3 2 2 2 1

Sudan 221 297 350 350 340 228 263 334 334 334

Suriname 2 2 1 2 2 0 0 0 0 0

Swaziland 14 13 14 13 13 3 3 2 2 2

Sweden 141 146 136 137 134 4 4 4 4 5

Switzerland 149 137 132 135 133 6 6 7 6 6

Syrian Arab Republic 35 45 55 60 66 137 181 187 195 213

Tajikistan 31 16 27 25 27 11 13 27 28 29

Tanzania, United Republic of 218 248 270 270 247 36 40 42 42 41

Thailand 251 173 248 184 189 1 1 2 1 1

Timor-Leste 1 1 1 1 1 1 0 0 0 0

Togo 6 7 8 8 9 4 7 8 8 8

Tonga 0 0 0 0 0 0 0 0 0 0

Trinidad and Tobago 1 1 1 1 1 0 0 0 0 0

Tunisia 51 59 53 56 57 54 64 64 67 68

Turkey 304 345 322 341 432 370 364 315 317 317

Turkmenistan 51 72 100 102 102 49 70 97 100 97

Uganda 86 98 106 106 106 26 30 35 35 35

Ukraine 1,220 731 562 568 546 38 17 16 15 15

United Arab Emirates 9 15 10 10 10 45 40 29 30 30

United Kingdom 886 676 762 847 882 387 347 331 330 325

United States of America11,50

912,13

411,24

311,91

012,04

4 130 107 85 105 105

Uruguay 369 409 516 600 560 61 51 33 31 27

Uzbekistan 381 388 518 552 551 77 76 74 84 83

Vanuatu 4 4 3 3 3 0 0 0 0 0

Venezuela 339 413 425 490 494 7 8 8 7 7

Viet Nam 82 93 142 159 206 4 5 9 11 11

Yemen 41 52 73 73 73 38 47 64 58 60

Zambia 45 55 59 58 58 3 5 8 5 5

Zimbabwe 69 99 95 97 97 11 14 14 14 14

World54,06

856,30

459,49

358,75

859,85

210,34

411,24

812,58

412,81

213,13

2

Table I.10. Regional growth estimates of demand for meat over the period 1990-2020.

Region Meat World 60- 93 Developed 17-18 Developing 123-206 68-91Sub-Saharan 141-194 136-161Latin America 76-105 53-77West Asia & North Africa 104-157 74-100Rest of Asia 148-255 64-85Source: IFPRI 1995

Table I.11

Fig 1.12

Fig. 1.13

LIST OF SOME OF THE COMMONLY USED HUMAN PROBIOTICSWHICH ARE CONSIDERED AS GRAS

1. Bacillius mesentericus 2. Bacillus brevis Migula

3. Bacillus circulans Jordon emend Ford.4. Bifidobacterium animalis 5. Bifidobacterium bifidum6. Bifidobacterium breve7. Bifidobacterium infantis8. Bifidobacterium lactis9. Bifidobacterium longum10.Clostridium butyricum11.Faecalibacterium prausnitzii12.Lactic acid Bacillus13.Lactobacillus acidophilus 14.Lactobacillus animalis15.Lactobacillus brevis16.Lactobacillus bulgaricus17.Lactobacillus casei, 18.Lactobacillus delbrueckii subsp. bulgaricus.19.Lactobacillus gasseri20.Lactobacillus johnsonii.21. Lactobacillus paracasei22.Lactobacillus plantarum23.Lactobacillus reutri24.Lactobacillus rhamnosus, 25.Lactobacillus rhamnosus26.Rhodospirillum rubrum27.Saccharomyces boulardii28.Streptococcus faecium29.Streptococcus faecalis.30.Streptococcus lactis31.Streptococcus salivarius32.Streptococcus salivarius subsp. Thermophilus

II. POULTRY

INDIAThe eating-out phenomenon, with more quick service restaurant chains opening up, is changing the consumption profile of Indians. The current chicken consumption is under 3 kg per head a year and the

poultry industry expects the consumption to double in the next five years.

Indian poultry industry has been growing at annual varying rates of 8-15% and this growth in the past few decades made India fifth largest producer of eggs and ninth largest producer of poultry broiler. At present the industry is estimated at over Rs 30,000 crore and is expected to grow over Rs 60,000 crore by 2010. India produces 1,400 million chickens a year, which is close to 27 million a week, of which 95% is traded alive. According to a market report the poultry production and consumption in the domestic markets is slated to grow by 66% to approximately 2.3 million tonnes by 2010.

The Rs 40,000-crore domestic poultry industry produces 240 crore birds commercially every year. To cope with the doubling of demand by 2014-15, the industry will need to expand at a rate of 12-15% annually.“While consumption is expected to double in the next five years, it may not become 6 kg per head in 2014-15. It may increase to 4.5-5 kg per head, factoring in an increase in our population,” Venkateshwara Hatcheries’ deputy general manager Dr Pedgaonkar said. By then, the poultry industry could become a Rs 60,000 crore to Rs 65,000 crore sector.

Godrej Agrovet managing director BS Yadav said, “The consumption of chicken doubles every five-six years, so we expect it to double by 2014-15. Mr Yadav added that the current high prices of chicken are driven by food inflation since pulses have become expensive. “Farmgate chicken prices have nearly doubled this year over prices in 2008. In 2008, the farm gate price was Rs 30-35 per kg, this year it is Rs 60-65 per kg, mainly because the industry shrank last year. Retail prices have reached an all-time high of Rs 100-110 per kg. In 2008, 42-44 million chicks were placed every week. In 2009, the placement fell to 36-37 million per week, leading to the current chicken shortage,” he said. He said that the growth in quick service restaurants has pushed chicken consumption over the past three years to emerge as a significant segment. “Over the past decade, institutional sales, which means these quick service restaurant chains, have emerged as the biggest consumers. Eating out of the home has become a big segment,” Mr Yadav said.

Outlining the issues the poultry industry faces, Suguna Group managing director B Soundararajan said, “In 2007, the per-capita consumption in India was 2 kg. But due to the financial crisis and an increase in commodity prices, there was a drop in consumption. This year, consumption has picked up again.”

EUThe market outlook for poultry meat is seen as favourable given strong consumer preferences for poultry meat and the competitive price of poultry meat vis-à-vis other meats. With the growth in EU poultry-meat production lagging behind the growth in consumption by 2008 the EU has become a net importer of poultry meat. With this trend continuing up to 2014, a growing production deficit will lead to increased EU imports of poultry meat (+8.04% between 2008 and 2014). Exports of poultry meat meanwhile are set to decline by 8.16%, ‘due to strong competition on the world markets by low-cost producers and unfavourable $/€ and Brazilian Real/€ exchange rates’.Despite the growing gap between EU production and consumption EU poultry-meat exports will still amount to 720,000 tonnes in 2014 (down from 881,000 tonnes in 2005), reflecting the EU preference for poultry breast and the need to export poultry parts.

EU_Poultry meat(Tonnes) 2005* 2008 2011 2014 % change 2008-14Usable production 11,564,000 11,435,000 11,776,000 12,047,000 + 5.35%Consumption 11,439,000 11,473,000 11,835,000 12,174,000 + 6.11%Surplus/deficit + 135,000 - 38,000 - 59,000 - 127,000 from + 1.2 % to – 1.0 %

consumption

Exports 881,000 747,000 766,000 720,000 - 8.16%Imports 756,000 784,000 826,000 847,000 + 8.04%*EU25

III. BEEF

EUEU beef production is projected to decline in the medium term to 7.6 million tonnes by 2014 from 7,959,000 tonnes in 2008, a fall of 4.51%. This is linked to the reduction of the dairy herd and the impact of the decoupling of EU aid payments. However, trends in the size of the dairy herd will be critically determined by the rate of milk-quota expansion agreed as part of the transition to the abolition of the quota-management system in 2015. The higher the increase in milk quotas the lower the rate of decline of the dairy herd and consequently the higher the level of domestic EU beef production. EU consumption of beef however is also projected to decline, although at a slower rate of -2.08% between 2008 and 2014. Despite the production deficit in the EU exports will continue to take place, albeit at greatly reduced levels (partly in response to higher domestic demand). Indeed, despite EU enlargement total EU exports by 2014 will be only 21.13% of the 2005 level. EU imports of beef are projected to increase by 25.34% between 2008 and 2014, from 592,000 tonnes to 743,000 tonnes.

EU_Beef(Tonnes) 2005* 2008 2011 2014 % change 2008-14Usable Production 8,044,000 7,959,000 7,740,000 7,600,000 - 4.51%Consumption 8,445,000 8,474,000 8,340,000 8,298,000 - 2.08%Surplus/Deficit - 401,000 - 515,000 - 600,000 - 698,000 Deficit + 74%Exports 213,000 77,000 52,000 45,000 - 41.56%Imports 614,000 592,000 653,000 743,000 + 25.34%*EU25

The rise in EU imports is likely to increase the competition faced by ACP beef suppliers, although the price implications of this will be critically determined by the trade arrangements under which this beef enters the EU market. In anticipation of increased competition on undifferentiated EU beef markets, some ACP beef exporters are improving their marketing efforts to target ‘luxury purchase’ markets in the EU. This is already yielding significant financial benefits. However market diversification beyond the EU remains a critical priority, in preparation for the market consequences of the evolving EU trade regime in the beef sector.

IV. DAIRY

World milk production is projected to increase by just under 2% annually between 2004 and2014, reaching 747 million tonnes in 2014. The European Union, India, United States, Russia, Pakistan, Brazil and China account for over two-thirds of total milk output. The growth is expected to be especially strong in India and China.

EU_Delivery and production of milk (millions of tonnes)

Deliveries EU27 Year EU27 production EU15 production EU10 production EU2 production133.5 2005 148.9 120.7 21.9 6.3132.7 2006 147.5 119.7 21.7 6.0132.9 2007 147.2 119.6 21.7 5.9133.6 2008 147.3 119.8 21.7 5.8134.4 2009 147.5 120.2 21.7 5.7134.7 2010 147.5 120.2 21.6 5.7135.0 2011 147.4 120.2 21.6 5.6135.3 2012 147.4 120.2 21.6 5.6135.5 2013 147.3 120.2 21.6 5.6135.6 2014 147.3 120.2 21.6 5.6

IV. PIG

Pork has achieved steady increases each year in the global markets.

EU_Pig meat(Tonnes) 2005* 2008 2011 2014 % change 2008-

14Usable production 21,572,000 22,081,000 22,464,000 22,677,000 + 2.70%Consumption 20,370,000 20,873,000 21,301,000 21,539,000 + 3.19%Surplus/deficit + 1,202,000 + 1,208,000 + 1,163,000 + 1,138,000 - 579%Exports 1,286,000 1,246,000 1,201,000 1,176,000 - 5.62%Imports 84,000 38,000 38,000 38,000 0%*EU25

Overall meat consumption is projected to increase from the estimated 84 kg/head in 2006 to around 86.7 kg/head by the year 2014. Pig meat would remain the most preferred meat by EU consumers with a share of about 50 %, followed by poultry that would increase its share to 28 % (+1.8 %).

VII 2014 PROJECTIONS OF PROBIOTIC USAGE WORLDWIDE

If global feed production grows at its current annual rate of rate of around 2%, the world will be producing around 750 mmt of industrial feed by 2015. This will require an additional 20% of grain and oilseed meal which translates to a yearly global production of 1168 mmt of coarse grain (additional 195 mmt) and 255 mmt oilseed meal (additional 43 mmt) by 2016.

(Supply and Demand of Raw Materials: Are They in Balance? ; Robert A. Swick, R&D Animal Nutrition Director; Agrenco Group; 50 Armenian Street, #04-02 Wilmer HouseSingapore)

Efforts are made to visualize the production and consumption of Non vegetarian foods by 2014.

REQUIREMENTS BY 2014SPECIES BIOMASS CONCENTRATE

FEED REQUIREMENTIn Kg KgCattle for Beef 66.321x 109 165.80 x 109

PRODUCT TVC and Dose QTY in KgGut Probiotics 4 B CFU/g

28g per adult animal once in a week0.01125447 x 109

of 4 BCFU/gGas Adsorbant Microbes 4 B CFU/g

Once in 15 days @ 100 gms/ ton feed 0.0011053 x 109

of 4 BCFU/g

Wet Litter Managing Microbes over the floor @ 2g/ sq m 0.002389807 x 109

of 4 BCFU/g

Cattle for Milk 89.652x 109 1630.036x 109

PRODUCT TVC and Dose QTY in KgGut Probiotics 4 B CFU/g

28g per adult animal once in a week0.015213 x 109

of 4 BCFU/gGas Adsorbant Microbes 4 B CFU/g

Once in 15 days @ 100 gms/ ton feed 0.010866 x 109

of 4 BCFU/g

Wet Litter Managing Microbes over the litter @ 2g/ sq m 0.00322954 x 109

of 4 BCFU/gMicrobes useful as galactagogues

4 B CFU/g@ 15 g/adult milch animal daily

0.00815018 x 109

of 4 BCFU/gCattle for Agricultural use 22.45x 109 163.885 x 109

PRODUCT TVC and Dose QTY in KgGas Adsorbant Microbes 4 B CFU/g

Once in 15 days @ 100 gms/ ton feed 0.00109256 x 109

of 4 BCFU/g

Wet Litter Managing Microbes over the litter @ 2g/ sq m 0.00080896 x 109

of 4 BCFU/g

Poultry for Table Eggs 129.041x 109 6829.494 x 109

PRODUCT TVC and Dose QTY in KgGut Probiotics 4 B CFU/g

750g / Ton Feed once in a fortnight5.122 x 109

of 4 BCFU/gWet Litter Managing Microbes over the litter @ 2g/ sq m of 20 cm

height heap0.025919 109

of 4 BCFU/gGut acidifying Microbes 2 B CFU/g

1g/L drinking water 13.658988 109

of 4 B CFU/g

Enzyme Secreting DFM 4 B CFU/g75- 150 g to 1M T Feed

0.7853918 x 109

4 B CFU/g

Amino Acid Producing DFM 9 B CFU/g750 g/ MT Feed

5.1221205 x 109

Of 9 B CFU/gToxin degrading DFM 4 B CFU/g

250-500 gms/ Ton Feed2.253733 x 109

Of 4B CFU/g

Poultry for Meat 83.0315 x 109 149.4567 x 109

PRODUCT TVC and Dose QTY in KgGut Probiotics 4 B CFU/g

750g / Ton Feed once in a fortnight0.112 x 109

of 4 BCFU/gWet Litter Managing Microbes over the litter @ 2g/ sq m 0.016606 x 109

of 4 BCFU/gEnzyme Secreting DFM 4 B CFU/g

75- 150 g to 1M T Feed0.50536077 x 109

of 4 B CFU/gAmino Acid Producing DFM 9 B CFU/g

750 g/ MT Feed0.112092525 x 109

Of 9 B CFU/gToxin degrading DFM 4 B CFU/g

250-500 gms/ Ton Feed0.0493207 x 109

Of 4 B CFU/g

Sheep and Goat for Meat 13.4585 x 109 30.28162 x 109

PRODUCT TVC and Dose QTY in KgGas Adsorbant Microbes 4 B CFU/g

Once in 15 days @ 100 gms/ ton feed 0.00020188 x 109

of 4 BCFU/g

Wet Litter Managing Microbes over the litter @ 2g/ sq m 0.0016150 x 109

of 4 BCFU/gEnzyme Secreting DFM 4 B CFU/g

75- 150 g to 1M T Feed0.0034823863 x 109

Of 4 B CFU/gAmino Acid Producing DFM 9 B CFU/g

750 g/ MT Feed0.02272 x 109

Of 9 B CFU/g

Sheep and Goat wool 0.715 x 109 0.01 x 109

PRODUCT TVC and Dose QTY in KgWet Litter Managing Microbes over the litter @ 2g/ sq m 0.0000858 x 109

of 4 BCFU/g

The demands of Duck feed, Quail Feed, Pig Feed, Fish feed and Shrimp feed are not included in all the above calculations.

All the above simple calculations are arrived based on the projections given by veteran agencies like FAO only. (Above Tables may be referred)

VIII. CONCLUSION

1. Total feed requirement can be minimized by improving the absorption techniques like Enzyme secreting Direct Fed Microbes

2. Poultry litter, cow dung etc can be made into fit feeding stuff by processing with microorganisms by eliminating pathogens and increasing the bioavailability of Nutrients in the litter and dung.

3. Employing better Feed technologies like Predigesting the Feeding stuff using microorganisms

4. Pre and post harvest technologies are to be improved and taken up by larger agencies to minimize spoilage and wastage using mcroorganisms

5. Feed Technologies are to be upgraded by employing DFM (Direct Fed Microbes to produce Amino Acids, Organic Acids, Enzymes, Growth promoters, Toxin degraders etc) which are cost effective, target specific and consumer friendly To improve the quality of feed To improve the FCR. To reduce the quantities of inputs by increasing TDN, To reduce the excreta, To improve survival rate To combat the diseases. To reduce the crop cycles To improve the shelf life of the products To produce in an organic way

6. Biodegradation of all the wastes and pollutants of the industry like litter so as to make them more environment friendly.

WEB REFERENCES:http://ec.europa.eu/agriculture/publi/caprep/prospects2007a/summary.pdf

Prospects for EU agricultural markets and income 2007-14, full text (March 2008)http://ec.europa.eu/agriculture/publi/caprep/prospects2007b/fullrep.pdf

Prospects for EU agricultural markets and income 2007-14, executive summary (March 2008)http://ec.europa.eu/agriculture/publi/caprep/prospects2007b/summary.pdf

REFERENCES:Bruinsma, J, H. Haen, N. Alexandratos, J. Schmidhuber, G. Bödeker and M. Grazia Ottaviani. 2002. World

Agriculture towards 2015/2030. Food and Agriculture Organization of the United Nations, Rome, 2002

Gill, C. 2005. World Feed Panorama: China, Brazil and Mexico push global tonnage to new peak. Feed International, January 2005.

Gill, C. 2008. World feed panorama. Feed International, January 2008.

Goll, S. 2008. Agricultural Markets Situation Report, U.S.D.A. WASDE, February 8, 2008.

Grainger, R. 2002. World review of fisheries and aquaculture. Fisheries Resources: Trends in Production, Utilization and Trade. The State of World Fisheries and Aquaculture 2002. FAO. http://www.fao.org/docrep/005/y7300e/y7300e04.htm

Lilley, 2004. Paving the Amazon with soy: World bank bows to audit of Maggi loan. Crop Watch, Dec 16, 2004. http://www.corpwatch.org/article.php?id=11756

Mielke, T. 2007. Oilworld Annual. ISTA Mielke Gmbh. Hamburg. Germany.

Parsons, C. 2005. Is there a future for GE crops beyond 2010? Proceedings of Poultry Beyond 2010 3rd International Broiler Nutritionists Conference, Langham Hotel, Auckland New Zealand, April 2005. Poultry Industry Association of New Zealand.

Sato, M. 2005. Personal Communication. Bunge Inernational Singapore, Ltd.

Seale, A.R and J. Bernstein. 2003. International Evidence on Food Consumption Patterns. TB1904, USDA/ERS, October 2003.

Westcott. P, R. Trostle and C.E. Young. 2007. USDA Agricultural Baseline Projections: Global Agricultural Projections 2006-2015. USDA Office of the Chief Economist, Staff Report, WAOB Feb 2007. http://www.ers.usda.gov/Briefing/Baseline/trade.htm