* Food systems methodology and the

Food systems methodology and the importance of capturing biodiversity in dietary assessments India s experience T. Longvah National Institute of Nutrition Hyderabad 500 007 AP India

Home to 1.2 billion people * *India is one of the 17 megadiverse countries that is hosts to 7.6% of all mammalian, 12.6% of all avian, 6.2% of all reptilian, 4.4% of all amphibian, 11.7% of all piscine, and 6.0% of all flowering plant species. *The Indian economy is the world's eleventh-largest by nominal GDP and third-largest by purchasing power parity (PPP). *Yet India continues to face the challenges of poverty, illiteracy,, malnourishment and inadequate healthcare.

Established in 1972 the bureau is currently in operation in the States of Andhra Pradesh, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Orissa, Tamil Nadu, Uttar Pradesh and West Bengal with the following objectives: 1) To collect, on a continuous basis, data on dietary pattern and nutritional status of the Indian population 2) To periodically evaluate the on-going National Nutrition Programmes to identify their strengths and weaknesses, and to recommend appropriate corrective measures.

*Cross sectional community based survey in 10 states *Selected villages spread over natural geographic regions of the states *120 villages covered in each state of which 90 are from baseline (1975-79), first repeat (1988 90) and second repeat (1996-97) and the remaining 30 are fresh villages *15629 households covered for anthropometry, clinical examination and history of morbidity in 2011 survey *Diet survey carried out in every alternate household covered for nutritional assessment

*Combination of 24 hour recall + weighment method used for diet surveys *Diets Survey carried out in all seasons of the year *Appropriate and useful across a wide range of population therefore suitable for national dietary assessment *NNMB data is the only nationally representative dietary survey available in the country *Captures time trends of food and nutrient intakes as well as changes in food supply

Cereals and grain products: 27 (27) Pulses and legumes: 19 (19) Leafy vegetables: 67 (49) Roots and tubers: 22 (21) Other vegetables: 51 (45) Nuts and oilseed: 24 (16) Condiments and spices: 23 (20) Fruits: 72 (40) Fish and seafoods: 85 (68) Meat and poultry: 20 (18) Milk and milk products: 15 (15) Fats and edible oils: 16 (14) Sugars; 8 (5) Beverages (Alcoholic); 3 Beverages (Non alcoholic): 2 Less familiar foods: 140

CEREALS, CEREAL PRODUCTS AND MILLETS IN THE NNMB DIET SURVEYS 2005-06 No. of Households Mean consumption Range Rice, raw, milled (Oryza sativa L) 3518 247.861 2.3 892.9 Rice, parboiled, milled (Oryza sativa L) 2840 349.284 15.6-1065.1 Wheat, flour(whole) (Triticum aestivum) 1806 168.609 1.0 636.4 Jowar ( Sorghum vulagre) 753 213.189 3.2 880.5 Rice, puffed (Oryza sativa L) 699 68.848 1.9 545.7 Bajra ( Pennisetum typhoideum) 607 250.184 0.1 250.184 Ragi (Eleusince coracana) 459 161.612 0.6 1042.3 Wheat, flour(refined) (Triticum aestivum) 279 307.922 0.3 1052.5 Rice, flakes (Oryza sativa L) 194 63.121 2.4 377.1 Maize, dry (Zea mays) 193 246.204 1.6 551.7 Wheat, semolina (Triticum aestivum) 174 75.770 1.4 282.7 Wheat, bread, (brown) (Triticum aestivum) 144 24.430 1.8 109.4 Wheat, bulgar (parboiled) (Triticum aestivum) 130 54.819 7.7 414.5 Wheat, bread, (white) (Triticum aestivum) 103 25.366 0.2 272.2 Wheat, whole(triticum aestivum) 54 82.306 2.6 294.1 Rice, raw, handpounded (Oryza sativa L) 40 267.863 15.3 506.5 Wheat, vermicelli(triticum aestivum) 20 73.155 16.3 235.3 Varagu (Paspalum scobiculatum) 14 172.279 26.1 500.0 Panivargau (Panicum miliaceum) 5 81.160 25.0 175.0 Samai (Panicum miliare) 5 255.040 51.0 408.2 Maize, tender (Zea mays) 2 53.650 51.7 55.6 Sanwa millet (Echinochloas frumantacea) 2 7.950 5.4 10.5 Barley (Hordeum vulgare) 2 118.350 18.4 28.3

PULSES AND GRAIN LEGUMES IN THE NNMB DIET SURVEYS 2005-06 No. of Households Mean Range Red gram, dhal 2353 31.491 0.3 273.9 Green, gram dhal 1118 31.637 0.7 158.8 Black, gram dhal 880 25.358 0.2 156.6 Bengal gram, dhal 701 21.674 0.2 233.1 Lentil 379 32.093 3.4 110.5 Bengal gram, roasted 216 17.382 0.4 123.7 Green, gram whole 181 29.803 2.3 125.5 Peas, dry 150 31.325 3.0 121.5 Cowpea 129 42.292 7.1 206.6 Horse gram, whole 118 42.486 6.5 132.8 Bengal gram, whole 100 37.674 2.5 230.0 Moth beans 92 27.507 2.6 83.0 Field bean, dry 87 42.652 5.9 131.3 Khesari, dhal 84 41.652 1.6 269.7 Soya bean 79 10.216 0.8 69.3 Peas green 47 34.532 3.8 126.0 Red gram, tender 20 43.975 4.8 93.8 Rajmah 5 64.160 18.8 195.8 Peas, roasted 3 95.133 30.9 178.9

GREEN LEAFY VEGETABLES - INNMB SURVEYS 2005-06 No. of Households No. of Households Curry leaves 1122 Bathua leaves 14 Coriander leaves 888 Amaranth, polygonoides 14 Cabbage 278 Amaranth cautatus 11 Amaranth, tender gangeticus 125 Fetid cassia (dried) 11 Drumstick leaves 102 Ambat chuka 8 Fenugreek leaves 71 Bottle gourd leaves 8 Amaranth, paniculatus 53 Paruppu keerai 7 Gogu 48 Amaranth, viridis 7 Amaranth species 43 Colocasia leaves (green 6 (koyakeera variety ) Amaranth, spinosus 41 Menathakkali leaves 5 Amaranth species 40 Cow pea leaves 5 (Chakravarthikeerai) Cauliflower leaves 36 Betel leaves 4 Bengal gram leaves 34 Agathi 2 Amaranth, stem 27 Beet greens 1 Mint 20 Carrot leaves 1 Ipomoea leaves 19 Colacasia leaves (dried) 1 Mayalu 19 Fetid cassia, fresh 1 Amaranth tristis 16 Modakanthan keerai 1 Colocasia leaves (black 15 Brussels sprouts 1 variety) Mustard leaves 14

Food stuffs 1975-79 1988-90 1996-97 2009-11 RDA Cereals & millets 505 469 450 382 460 Pulses 34 32 27 32 40 Green Leafy Vegetables 8 9 15 17 40 Other vegetable 54 49 47 45 60 Roots & Tubers 56 41 44 58 50 Milk & Milk products 116 92 86 89 150 Fats & Oils 14 13 12 16 20 Sugar & Jaggery 23 29 21 13 30

*Provides detailed information on the food and nutrient intake of the Indian population *Captures the different varieties of commonly consumed foods within food groups *Captures different types of cooking oils *Captures fish varieties *Does not capture the neglected underutilized food species *Fails to capture seasonal changes in food supply *Fails to differentiate varieties within species

*The PDS is the key element in the food security system in India particularly for the poor. *Instrument for ensuring availability of food grains mainly rice, wheat, sugar and kerosene at subsidized rates *Government of India introduced the Targeted PDS in 1997 to provide highly subsidized food grains to those below the poverty line. *Budgetary allocation for food subsidy during the year 2010-11 was US $ 11.1 billion *Major instrument in the government s anti poverty programme the TPDS supports over 400 million Indians below the poverty line *Provides cheap calories to the households

*The green revolution packages during the 1960 s, increased per capita incomes and PDS brought a tremendous change in the people s diet *The low price of subsidized rice and wheat led to a decrease consumer demand of millets *This led to producer shift from traditional crops mostly rain fed dry land crops towards high value water intensive crops. *Shift from locally available, wild, farm, leafy and other seasonal vegetables to some common vegetables *Loss in food biodiversity and important germplasm *Overdependence of population on too few crops

Food item Rural Urban Rice 7.0 (52-24) Wheat 4.4 (32.84) 1993-94 2009-10 % Change 1993-94 2009-10 % change 6.14 (54.10) 4.36 (38.41) -12.86 5.3 (50.00) -0.91 4.7 (44.34) 4.66 (49.73) 4.37 (46.64) -12.08-7.02 Jowar 0.8 0.29-63.75 0.4 0.18-55.00 (5.97) (2.56) (3.77) (1.92) Bajra 0.5 (3.73) Maize 0.4 (2.99) Other cereals & millets 0.3 (2.24) Total cereals 13.4 (100) 0.28 (2.29) 0.20 (1.76) 0.11 (0.97) 11.35 (100) -44.00 0.1 (0.94) -50.00 00 (00) -63.33 0.1 (0.94) -15.30 10.6 (100) 0.09 (0.96) 0.02 (00) 0.08 (0.85) 9.37 (100) Figures in parenthesis indicates percentages Sources: Level and pattern household consumption expenditure in India (various issues) -10.00 00-20.00-11.60

*Food composition data provide detailed information on the nutritional composition of foods *FCT are used in a variety of ways by a spectrum of users *Data on what is actually present in foods are critical for those involved in nutrition research, epidemiological studies and product development as well as for developing government policies regarding health, nutrition and agriculture.

Food stuffs 1975-79 1988-90 1996-97 2009-11 RDA Protein (g) 61.5 58.4 53.7 50.7 60 Energy (Kcal) 2349 2283 2108 1870 2425 Calcium (mg) 606 565 521 425 400 Iron (mg) 30.2 27.2 14.2 14.9 28 Vitamin A (µg) 246 282 300 294 600 Thiamin (mg) 1.46 1.33 1.20 1.3 1.20 Riboflavin (mg) 0.81 0.87 0.9 0.7 1.40 Niacin mg) 14.7 14.2 12.7 14.5 16 Vit. C (mg) 39 37 40 45 40

*A probability-based (PPS)) National sampling plan was developed to sample and analyse foods consumed in the country wherein the country was divided into six regions (North, South, East, West, Central and Northeast) with roughly equal populations *Each region comprises of states and the sample size of each state was based on the number of districts in the particular state. *Population proportionate to size stratified sampling method was applied for the selection of districts within the states based on the number of natural geographical regions (NGR) in each state. *Wherever NGR was not available in the state, administrative regions as followed by the state was taken for stratified sampling. *Sampling units in each district is the biggest town. *Primary sampling units in each town is a retail outlet

Name of the food North North east East West South Central Amarathus 1 4 1 1 3 2 gangeticus Apple 2 2 1 1 1 1 Eggplant 5 14 11 14 11 5 Chilli green 2 9 4 7 5 3 Garlic 3 2 1 1 2 1 Ginger fresh 1 3 1 1 1 1 Potato 1 3 1 1 1 1 Tomato Ripe 2 3 2 2 2 2

EGGPLANT VARIETIES

Eggplant (Solanum melongana) Content/100g Unit Content Variation Water soluble vitamins B1, Thiamine mg 0.06 ± 0.02 0.025 0.10 B2, Riboflavin mg 0.11 ± 0.02 0.050 0.16 B3,Niacin mg 0.53 ± 0.11 0.28 0.79 B5, Panthothenic Acid mg 0.92 ± 0.43 0.18 1.87 B7, Biotin mg B8, Inositol phosphate mg B9, Folic Acid µg B12, Cyanocobalamin mg ND Total Ascorbic acid 1.88 ± 0.99 0.13 4.21 L-Ascorbic Acid mg 0.28 ± 0.24 0.02 0.088 L-dehydroascorbic acid mg 0.83 ± 0.61 0.13 3.29 Glycine betaine mg 72.94 ± 13.76 47.14 98.94 Trigonelline mg 0.06 ± 0.03 0.02 0.16 Butyrobetaine mg ND Choline mg 50.33 ± 7.47 20.44 77.37 CDP-Choline mg 0.06 ± 0.02 0.02 0.13 Total Polyphenols 13.15 ± 5.96 2.66 28.23 Pyridoxamine µg 18.08 ± 13.22 3.59 109.50 Pyridoxal µg 32.13 ± 9.82 17.95 57.84 Pyridoxine µg 51.78 ± 17.19 13.34 103.79 TOTAL µg 98.52 ± 25.95 46.62 186.03 P C L nmol DPPH radical scavenging % 16.98 ± 4.94 9.52 41.69 IC50 26.63 ± 7.44 16.87 53.30 Content/100g Unit Content Variation Fat soluble vitamins Lutein µg 62.84 ± 47.27 13.63 15.55 Zeaxanthin µg ND Lycopene µg ND B-cryptoxanthin µg ND γ- carotene µg ND α-carotene µg ND ß-carotene µg ND α-tocopherol mg 0.09 ± 0.05 0.02 0.22 ß-Tocopherol mg ND ND γ-tocopherol mg 0.04 ± 0.01 0.03 0.05 δ-tocopherol mg ND ND α-tocotrienol mg ND ND ß -Tocotrienol mg ND ND γ-tocotrienol mg ND δ-tocotrienol mg ND D3-Cholecalciferol ND D2-Ergocalciferol 1.28 ± 1.46 0.21 9.20 K1-Phylloquinone µg 16.54 ± 9.70 2.80 35.30 K2-Menaquinone µg ND Campasterol mg 6.19 ± 1.82 3.12 9.89 Stigmasterol mg 16.59 ± 4.08 10.02 26.50 ß -sitosterol mg 69.81 ± 16.46 41.48 98.87

Parameters Hybrid Rice Range Landraces Range (N = 287) (N = 125) Moisture 8.51 1.6 4.0-12.7 12.21 1.34 9.1-15.7 Protein 9.08 1.5 5.6-13.87 7.76 0.92 5.4-10.2 Fat 2.39 ± 0.53 1.8-4.3 2.81±0.40 2.0 3.9 Ash 2.04 ±0.53 1.9-3.5 1.19±0.17 0.6 1.6 IDF 3.62±0.16 3.18-3.9 4.61±0.46 3.4-5.4 SDF 0.79±0.06 0.66-0.92 0.91±0.08 0.7-1.1 TDF 4.41±0.17 3.99-4.71 5.52±0.45 4.4-6.1

Brown rice; 5% Polished; 10% Polished Zn mg g -100 Rice varieties

GLYCEMIC INDEX OF RICE LANDRACES 80 75 70 65 High GI 60 55 50 Low GI 45 40 Machang Nepali Rice Naganad Napdoin Tongnau -Nap Nagduina-Chuilon Nagdai-Chuilon Bungna Taobam Langmai / Daimei Changngat Molphei Durgpat Taobam Chuilon Nandi Maiba Najdainganh-Taobam White glutinous Black glutinous

*Nutrient content can vary widely within species therefore the consumption of different varieties or breeds can have a significant impact on nutritional adequacy. *Differences in the nutrient composition within species can have large influence on data interpretation *Cultivar specific nutrient data can be the key to devise food based nutrition intervention strategies as the key for addressing global hunger, micronutrient malnutrition and chronic degenerative diseases *Capturing biodiversity in diet surveys will also be an important step towards understanding the impact of biodiversity on food and nutrition security *Capturing food cultivar specific data in diet surveys is the need of the day