Isolations of the Compounds and Experimenting on the Toxicity of Extracts from the Asparagus racemosusin,

Managing Potential Feed Resources of Smallholder Dairy Farms under AANZFTA Agreement

Suntorn Wittayakun

Department of Animal Science and Fishery,

Rajamangala University of Technology Lanna, Lampang Campus, Muang, Lampang, 52000 Thailand

Corresponding author: w_suntorn@rmutl.ac.th

Abstract

Free trade agreements have been designed to promote the economic prosperity of participating countries and aimed at creating fair and equal competition across free trade zones. In year 2020, all ASEAN countries are required to completely eliminate tariff rates and non-tariff barriers with Australia and New Zealand, the two major global dairy exporters. In order to gain global competitive potential, smallholder dairy farmers of ASEAN countries may have to pay more attention and intensively manage both quantity and quality of dairy feed supply by: 1) expansion of high yield forage utilization such as Napier grass or whole corn plant, 2) integrated grazing paddock with various legumes or tree legumes in ordinary pasture, 3) utilization of agri- and agro-by products with appropriate treatments and 4) balancing of nutrients in daily feed allowance. Although a number of feeding management strategies are described, these might have potential and further gain competitive potential in global dairy business to sustain and minimize impact of AANZFTA in this region.

Keywords: Asian, Dairy, Feed resource, Free trade agreements

Introduction

Free trade agreements are designed to accelerate the economic prosperity of participating countries and aimed to create fair and equal competition across free trade zones. According to the Agreement Establishing the ASEAN-Australia- New Zealand Free Trade Area (AANZFTA) established on November 30, 2004, Thailand and all ASEAN countries are required to reduce tariff rates, eliminate non-tariff barriers to increase economic cooperation to facilitate trade and economic development which all tariff rates have to completely eliminate in year 2020 [1]. It is well known that Australia and New Zealand are extremely productive countries in milk production more than 10 times the average of ASEAN (Table 1) and account for major global Table 1: World milk production statistic (thousand tons)† and major dairy exporters (million USD)^‡ Milk production ^[2] Year 2013-2015† % Major Exporter ^[3] Year 2016‡ %

World 794,676 100 1. New Zealand 4.4 x 10³ 18.9

Developing countries 411, 533 51.78 2. Germany 2.6 x 10³ 11.0 Developed countries 383,143 48.21 3. Netherlands 1.9 x 10³ 8.1

Asia 316,603 39.84 4. France 1.5 x 10³ 6.5

India 146,501 18.43 5. United States 1.4 x 10³ 6.1

Pakistan 50,233 6.32 6. Belgium 1.2 x 10³ 5.2

China 41,976 5.28 7. Australia 852 3.7

ASEAN 2,440 0.31 8. Belarus 637.6 2.8

Indonesia 1,265 0.16 9. United Kingdom 569.1 2.5

Thailand 1,071 0.13 10. Saudi Arabia 556.3 2.4

Malaysia 84 0.01 11. United Arab Emirates 523 2.3

OCEANIA 30,655 3.85 12. Poland 504.5 2.2

Australia 9,688 1.22 13. Hong Kong 499.1 2.2

New Zealand 20,897 2.63 14. Denmark 451.2 2.0

Source: FAO (2017)[2]; Workman (2018) [3]

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dairy exporters. Their milk production system mostly relies on high quality of pasture and

grazing land with a few of concentrates and extra feeds (Table 2), resulting in significant feed cost reduction and maximizing profit of the dairy farming enterprise [4]. On the other hand, dairy feeding of ASEAN smallholder dairying is generally relying on locally available feed resources, such as natural pastures, tree leaves, shrubs, agri- and agro-industrial by-products [5]. The amount of farm pasture is usually insufficient in year round due to limit of land holding while the pasture nutritive values are wide fluctuation largely due to seasonal change and natural rainfall. Most smallholder dairy farmers have compensated by increasing use of commercial concentrates as a consequence of high feed cost, losing ability of competition in global dairy business and rumen fermentation becomes dysfunctional. To avoid these impacts, smallholder dairy farmers need to take a step back and examine individual feed resources carefully as a whole and intensively managed to ensure a year round feed supply in term of both quantity and quality in order to gain global competitive potential to maximize farm sustainability and minimize impact of AANZFTA in global dairy business.

Table 2: Estimated Feed intake consumed by dairy cow in New Zealand in year 2014-2015

Items ton DM/cow % ton DM/ha %

Total feed intake 4.93 100 14.16 100

Pasture 4.04 81.94 11.61 81.99

Crop 0.18 3.65 0.52 3.67

Harvested supplement 0.26 5.27 0.76 5.36

Imported supplement 0.44 8.92 1.27 8.96

Source: Wales and Kolver (2017) [4]

Expansion of high yield forage utilization Hybrid Napier grass

Napier grass (Pennisetum purpureum) also known as, elephant grass or Uganda grass, is a species of a fast-growing perennial tropical grass of Sub-Saharan African grasslands which is widely grown across the tropical and subtropical regions of the world [6]. Napier grass is tolerance of drought and can be grown in relative poor soil which could produce more dry matter yield per unit area compared to other grasses [7]. Many varieties of hybrid Napier grass have been developed by the hybridization(Table 3) such as Napier grass(Pennisetum purpureum) x Pearl millet (Pennisetum glaucum L.) to increase yield and nutritive values as high quality of green fodder for cut and carry or silage making[8].

Table 3: Yield and nutritive quality of Napier grass varieties over 6 harvests¹

varieties CP NDF ADF IVDMD CumulativeDM

Yield (tons/ha)

Common Napier 9.79 70.90 38.80 - 65.1

Indian Napier 10.64 70.00 38.80 - 56.7

King grass 10.11 70.10 38.10 53.66 61.6

Taiwan Napier 10.09 70.00 39.90 53.02 60.4

Thai Napier (Pakchong1)² 12.45 65.15 38.19 58.60³ 57.47

Source: Halim et al.(2013) ¹[9]; Noola-aong et al.(2016)²[10]; Gunha et al. (2015)³[11];

Napier grass can be harvest as green fodder every 45 to 60 days by cutting at 5 to 15 cm above ground level [12] or 6 to 7 weeks [13]to maximize both yield and nutrient contents. Under well-managed practices, Napier grasses are able to harvest every month in hot and wet

environments, or every 2 months in drier areas [14]. Green Napier grasses are quite high in water soluble carbohydrate during reproductive growth phase (Table 4) as a substrate for lactic acid fermentation [15].

In view of productivity and nutritive values of Napier grass, it is perhaps not surprising that Napier grass would be a potential source of fodder and silage. However, there are evidences that adding molasses at 4 % [16] or 5% of fresh weight [17]could improve the efficiency of ensiling process as well as feed intake and digestibility in dairy cows (Table 5).

Table 4: Average total sugar, starch and total non-structural carbohydrate in hybrid Napier grasses Cultivars Growth phase Total sugar (%) Starch (%) total non-structural CHO (%)

King grass Vegetative 1.72^a 15.89^a 17.61^a

Reproductive 6.34^c 17.34^c 23.68^c

Taiwan Napier Vegetative 2.64^a 14.65^a 17.29^a

Reproductive 7.2^c 15.32^a 23.24^c

Mott Vegetative 1.75^a 14.02^a 15.77^a

Reproductive 3.36^b 16.73^c 20.09^c

Superscript by column cultivars and growth phase significantly different at (P <0.05) Source: Budiman et al.(2011)[15].

Table 5: Effect of additive adding in ensiling process on intake and digestibility of dairy cows.

Items No additive Molasses Cassava FJLB SEM P-value

Total feed intake, %BW 2.14^b 2.41^a 2.12^b 2.19^b 0.02 0.0310

Silage intake, %BW 0.79^b 1.06^a 0.77^b 0.84^b 0.02 0.0269

Digestibility, %

DM 75.64^b 81.54^a 76.18^ab 75.99^ab 1.43 0.0943

OM 77.43^b 83.22^a 78.06^ab 77.82^b 1.36 0.0878

CP 76.95^b 81.09^a 77.5^ab 75.27^b 0.98 0.0454

NDF 66.6^b 76.75^a 68.57^b 67.26^b 1.76 0.0314

Values in the same row followed by different letters are significantly different (P<0.05).

Source: Bureenok et al. (2012) [17].

Whole corn plant as corn silage

Corn (Zea Mays L.) is a major roughage source as silage for dairy cows around the World due to its consistently high yield per planting area and high digestible energy contents. Typical good corn silage, with lot of kernels, is high in energy (68.0% TDN), moderate in crude protein (8.3% CP), low in Calcium (0.31% Ca) and Phosphorus (0.27 % P) on a dry matter basis [18].

The optimal stage of harvesting depends primarily on whole plant dry matter content, yield and nutrient composition (Table 6).

Table 6: Effect of maturity on yield, nutrient content and digestibility of whole plant corn

Maturity stage DM, % Yield, ton/acre CP, % NDF, % ADF, % Digestibility, %

Soft dough 24 5.4 10.3 52.7 27.2 77.1

Early dent 27 5.6 9.9 48.0 24.3 79.0

½ milk line 34 6.3 9.2 45.1 22.8 80.0

¾ milk line 37 6.4 8.9 47.3 23.8 79.6

No milk line 40 6.3 8.4 47.3 24.0 78.6

Source: Wiersma et al.(1993)[19].

To produce good corn silage, very careful preservation is required with additional storage places to store this high quality feed in long period. In addition, adding 4 to 5 % of molasses may benefit to increase the efficiency of ensiling process [16], [17]. The effects of corn silage on performance of milking cows was demonstrated by Cattani et al.(2017)[20], who investigated effects of total replacement of corn silage with sorghum silage on milk yield, composition, and quality of Holstein cows. The result indicated that cows fed corn silage based diet produced more milk yield than those fed sorghum based diet (Table 7).

Table 7: Effects of total replacement of corn silage with sorghum silage in diets of milking cow

Items Corn silage based diet Sorghum silage based diet SEM P-value

DMI, kg/d 24.88 24.52 1.44 0.878

Milk yield, kg/d 31.63 29.79 1.97 0.043

4% FCM, kg/d 31.83 31.54 1.92 0.848

Milk composition, %

Fat 3.98 4.62 0.16 0.024

Protein 3.55 3.66 0.08 0.065

Lactose 4.85 4.84 0.52 0.51

Source: Cattani et al.(2017)[20]

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Integrated grazing paddock with various legumes Legumes mixed in ordinary pasture

Legumes are an excellent source of protein to ruminants due to their symbiotic biological nitrogen fixation by Rhizobium bacteria[21].Integrated suitable legumes to ordinary pasture in grazing or cut and carry paddocks could enhance yield and nutrient output from pasture to increase needed nutrients of dairy cattle. For example, Pholsen et al. (2014) [22] reported yields and nutrient contents of Ruzi (Brachiaria ruziziensis) and Purple guinea (Panicum maximum cv.

TD58) with no fertilizer added in grazing paddock were tended to increase by cultivating with Verano legume (Stylosanthes hamate cv. Verano) and Wynn legume (Chamaechista rotundifolia cv. Wynn) compared with those single grass pasture(Table 8).

Table 8:Effect of mixed legumes on dry matter yield and nutrient output of Ruzi and Purple guinea grasses

Items Ruzi Ruzi+Legumes Sig. Purple guinea Purple

guinea+Legumes Sig.

DM Yield, kg/ha 4601 5573 ** 4082 4989 **

Nutrient output, %

CP 7.20 8.06 ** 7.05 8.86 **

NDF 74.71 73.07 ** 77.08 71.89 **

ADF 35.52 35.76 ** 43.68 42.85 **

Source: Pholsen et al. (2014) [22]

Several of legumes can be potentially planted to improve quality of farm pasture for grazing or cut and carry system in ASEAN countries. List of annual and perennial legumes in Tropics is shown in Table 9.

Table 9: List of annual and perennial legumes in Tropics.

Species/cultivar Common name Type Planting condition

Atylosia scarabaeoides Benth Bankulthi (India) Perennial Arid and semi-arid climates, rainfall: 250-1000 mm, light to heavy even clayey soils with adequate drainage, drought and frost resistant,

Calopogonium mucunoides Desv. Calopo annual Hot and humid tropics, rainfall > 1525 mm, wide range of soils at pH 4.5 to 6.5, moderate drought and shade tolerant Centrosema pubescens Benth Centro Perennial Hot and humid tropics, rainfall > 1525 mm, alluvial to

medium fertile soils, moderately tolerant to poor drainage Clitoria ternatea Linn Butterfly pea, Conch

flower creeper, Mussel-sheel,

Pea blue creeper

Perennial Tropical to warm parts of the world, rainfall: 400-1500 mm or under irrigation, a wide range of soil conditions from sandy to deep alluvial loams and heavy black cracking clays, tolerance to moderately saline soils.

Desmodium intortum (Mill) Fawc &

Rendle

Green leaf desmodium Perennial Tropical and sub-tropical regions, rainfall: 900 to 1275mm, requires a long warm growing season, wide range of soils from light to clay loams with neutral to moderately acidic, well adapted to poorly drained or water logged conditions, no tolerance to salinity.

Lablab purpureus (Linn.) Sweet Dolichos, Lablab bean, Hyacinth or Field bean

Annual Sub-tropical regions, rainfall: 510 to 1500 mm, wide range of soils (deep sands to heavy clays) and pH (5.0 to 7.5).

Lotononis bainesii Baker Lotononis and Miles Lotononis

Perennial Tropical and sub-tropical regions, rainfall:> 900 mm, well drained acid sandy soils, tolerates temporary water logging and flooding, drought tolerant.

Macroptilium atropurpureum (DC.) Urb. Synonym - Phaseoulus atropurpureus DC.

Siratro Perennial Tropical and sub-tropical regions, rainfall: 615 to 1800 mm, wide range of soils from light textured sandy soils to heavy clays with good drainage, soil pH4.5 to 8.0 or moderately saline soils.

Macroptilium lathyroides (Linn.) Urb.

Syn. Phaseolus lathyroides

Phasey bean, Wild pea bean

Annual Tropical and sub-tropical regions, rainfall: 760 to 2030 mm, fertile soils (deep sandy to heavy clays), tolerate to infertile, poor drainage, acid to saline and alkaline soils Macrotyloma axil/ares (E. Mey.)

Verdc.

Syn. Dolichos axillaris

Archer dolichos Perennial Tropical and sub-tropical regions, rainfall 1000 mm, sands to clays with good drainage, require soil pH > 5.5, tolerates salinity.

Neonotonia wightii (Grah. ex Wight

& Arn.) Lackey

Syn. Glycine wightii (Grah. ex Wight

& Arn.) Verde. AndG.javanica L.

Glycine Perennial Tropical, rainfall: 760 to 1525 mm, heavy black soils with good drainage, not tolerate water logging and high acidity conditions, but tolerates soil pH up to 6.5.

Stizolobium deeringianum Bort. Velvet bean Annual Tropical, rainfall: 650 to 2500 mm, all types of soils, prefers sandy to sandy loam or may be in acidic soils.

Stylosanthes guianensis (Aubl.) Sw. Stylo, Schofield or Perennial Sub-tropical, rainfall:> 1525 mm, wide range of soils from

Species/cultivar Common name Type Planting condition Brazilian or tropical

lucerne

It is not tolerant to salinity.

Stylosanthes hamata (L.) Taub. Carribean stylo and Veranostylo

Perennial Sub-tropical, rainfall:> 500 to 1270 mm, wide range of soil types and is drought resistant.

Stylosanthes humilis H.B. & K. Townsville stylo, Townsville or Wild

lucerne

Annual Tropical and sub-tropical regions, rainfall:> 500 to 1270 mm, wide range of soils, but prefers sand and sandy loams, may grow on acidic soils and even on well drained heavier type of soils, fair tolerance to salinity.

Stylosanthes scabra Vag. Shrubby stylo, Scabra stylo

Perennial Tropical and sub-tropical regions, rainfall:> 325 to 1200 mm, all types of soils with good drainage or saline soils.

Vigna luteola (Jacq.) Benth. Dalrymple vigna Perennial Sub-tropical, rainfall:> 500 to 1270 mm, wide range of soils, highly successful on wet and poorly drained soils, also tolerates saline conditions.

Source: Trivedi (2002) [23]

Tree legumes

Tree legumes are an alternative source of protein-rich forage for subsistence of dairy production in the Tropics. Tree legumes could supply foliage during dry periods when other grasses or legumes are not available due to their deep primary root system and symbiotic biological nitrogen fixation. A number of studies have been conducted to determine the influence of feeding tree legumes on feed intake and performance of dairy cattle. For instance, Chanartaeparporn et al. (2010) [24] investigated the different levels of Leucaena forage supplementation for metabolism adaptation in pre and postpartum dairy cows. Crossbred Holstein Friesian dairy cows were fed concentrate and Pangola grass as a control group while other two groups were supplemented more with either 4 or 8 kg of Leucaena forage as fed basis. The result was successfully shown the significant improvement in blood glucose of pre and postpartum dairy cows (Table 10).

Table 10: Effect of Leucaena forage supplementation in pre and postpartum dairy cows

Items Control Plus 4 kg Leucaena Plus 8 kg Leucaena

Total feed intake, kgDM/d 10.54 9.36 8.43

Plasma glucose, mg/dl

- 30 d pre-partum 43.88^a 47.84^a 63.47^b

- 28 d post-partum 42.48^a 51.72^ab 58.47^b

Blood urea nitrogen, mg/dl

- 30 d pre-partum 13.59^a 11.27^b 12.56^a

- 28 d post-partum 15.68^a 13.36^b 14.98^a

Non esterified fatty acid, mg/dl

- 30 d pre-partum 37.32 34.25 41.05

- 28 d post-partum 25.93 23.89 21.48

a,bmeans in the same row with different superscripts are different (P<0.05) Source: Chanartaeparporn et al. (2010) [24]

List of potential tree legumes that recommends to smallholder dairy farms in ASEAN countries is shown in Table 11.

Table 11: List of outstanding tree legumes recommended for smallholder dairy farms in ASEAN

Species/cultivar Common name Region Nutritive value, %

CP NDF ADF Reference Albizia lebbeck Lebbeck, Lebbek tree, Flea

tree, Frywood, Koko

Tropics and sub-tropics

25.04 50.37 35.32 [25]

Cratylia argentea Cratylia. Tropics 17.73 60.03 32.56 [26]

Desmodium rensonii Syn. D. cinerea; D.

cinereum (Kunth) DC.

Rensonii, Alfalfa of the Tropics

Tropics 15.91 42.82 30.21 [27]

Desmodium virgatus Bundle flower Tropics and sub-tropics

22.76 32.53 20.48 [27]

Gliricidia sepium Gliricidia, Quickstick Tropic and sub-tropic

22.09 35.96 34.99 [25]

Leucaena leucocephala White leadtree, Jumbay, Tropics 26.02 31.67 20.30 [27]

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Species/cultivar Common name Region Nutritive value, %

CP NDF ADF Reference White popinac

Leucaena diversifolia Wild tamarind, Red leucaena, Leucaena, Diversifolia

Tropics 22.68 39.80 35.5 [28]

Mimosa pigra Giant sensitive tree Tropics 18.87 50.13 37.06 [29]

Sesbania grandiflora Agati, Hummingbird tree Tropics 26.71 33.43 22.19 [27]

Sesbania sesban Sesban, Egyptian rattle pod, Egyptian river hemp

Tropics 20.07 30.49 21.06 [27]

Utilization of agri-and agro-by products Rice straw

Rice straw is well known as agricultural by product from paddy field. In Asia, the amount of rice straw is produced approximate 61.5 million tons annually (Table 12). Rice straw contains cellulose 32-47%, hemicelluloses 19-27%, lignin 5-24% and ashes 18.8% [30] or glucose 41- 43.4%, xylose 14.8-20.2%, arabinose 2.7-4.5%, mannose 1.8% and galactose 0.4% [31] with low crude protein [5]. Rumen microbes are able to degrade -glycosidic bonds of D-glucose polymers in rice straw [32]to yield volatile fatty acids as energy sources for ruminants [5].High lignification of plant cell wall has a huge impact on plant cell wall digestion by rumen microbe resulting in low digestibility and limit feed intake in cattle fed rice straw [33]. Various methods of treatments to improve the quality of rice straw such as physical treatments (grinding, chopping, etc.), chemical treatments (urea, sodium hydroxide, etc.) and biological treatments (fungi, enzymes, etc.) have been extensively applied [5], [34]. For smallholder dairy farms, urea treatment seems to be the most efficient method with practical, low cost and affordable practice [5].

Table 12: World paddy production and rice straw (million tons)

Paddy production¹ Mean Rice straw²

2015 2016 2017 % Mean

World 740.3 751.9 758.9 750.4 100 510.3

Developing countries 715.2 725.7 733.2 724.7 96.6 65.7

Developed countries 25.1 26.2 25.7 25.7 3.4 2.3

Continents

Asia 669.6 680.1 686.4 678.7 90.4 61.5

Africa 28.8 30.8 30.7 30.1 4.0 2.7

Others 41.9 41.0 41.8 41.6 5.5 3.7

1FAO (2017)[35]; ²Estimated from Singh et al.(1995)[36].

Pineapple peel

Pineapple peel, a cannery by-product of Pineapple (Ananas comosus), is a potential roughage source for ruminants due to the large amount of effective fiber and some sugars [37].

Pineapple peel contains 7.38 % CP, 58.48 % NDF, 27.8 % ADF [38]. Although chemical property of pineapple peel is rather low in pH (3.47-3.84), it can be fed up to 70 % on dry matter basis in mixed diets without any sign of rumen acidosis in Holstein milking cows [38].

Miscellaneous

Many of agri-and agro-by products from field crop residues, plant processing, fruit and vegetable industry, sugar industry, brewing and distilling industry can be used effectively in dairy ration depending on their availability at competitive prices.

Balancing of nutrients in daily feed allowance

Besides high quantity and quality of feed resources, dairy cow diet needs to be balanced in response to daily nutrient requirement in order to achieve productive performance, body condition score and reproductive targets. Rule of thumb for nutrient balancing is shown in Table 13. Diets may distribute to cows in form of total mixed ration to keep the diets consistent, avoid sorting and optimize microbial fermentation in rumen.

Table 13: Rule of thumb for nutrient balancing

Dietary element Intake level

Dry matter intake Minimum daily intake at least 3% of body weight, 4% for higher- producing cows (over 30L/day)

Neutral detergent fiber (NDF) Maximum daily intake to 1.2% (1.3% for high producers) of body weight in total diet. Maximum 1% of body weight from forage NDF content of the total diet 28-32% NDF in diet DM for cows producing over 9,000 L

30-34% NDF for late lactation/medium production

34-40% NDF for cows producing under 6,000 L on tropical pastures Effective NDF (eNDF) Minimum 20% of total NDF as eNDF (forage length 2-5 cm) Non-fibrous carbohydrate (NFC) 35-40% of diet DM at peak/high production

32-37% at late lactation/low production

Starch 22-25% of diet DM

Sugar 3-6% of diet DM (up to 10% on mature tropical grass/molasses diets) Crude protein (CP) Minimum 16% of diet DM at peak/high production

Minimum 13% at late lactation/low production

Rumen-degradable protein (RDP) 66-72% of CP content of the diet at peak lactation/high production 70-76% of the CP content of the diet at late lactation/low production

Fats Maximum 5-6% of diet DM

Source: Anonymous (2013)[39]

Conclusions

Smallholder dairy farmers of ASEAN countries require to intensively manage both quantity and quality of feed supply as following: 1) expansion of high yield forage utilization such as Napier grass or whole corn plant, 2) integrated grazing paddock with various legumes or tree legumes in ordinary pasture, 3) utilization of agri-and agro-by products with appropriate treatments and 4) balancing of nutrients in daily feed allowance. These might have potential to gain competitive potential of smallholder dairy farmers in ASEAN countries among global dairy business with sustainability and able to minimize impact of AANZFTA.

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[19] Wiersma, D.W., Carter, P.R., Albrecht, K.A. and Coors, J.G. (1993). Kernel Milkline Stage and Corn Forage Yield, Quality, and Dry Matter Content. J. Prod. Agric. 6(1): 23-24, 94-99.

[20]Cattani, M.,Guzzo, N., Mantovani, R. and Bailoni, L.(2017). Effects of Total Replacement of Corn Silage with Sorghum Silage on Milk Yield, Composition, and Quality. J. Anim Sci Biotechnol. 8:15.

[21] Maikhuri, R.K., Dangwal, D., Negi, V.S. and Rawat, L.S. (2016). Evaluation of Symbiotic Nitrogen Fixing Ability of Legume Crops in Central Himalaya, India. Rhizosphere. 1:26-28.

[22] Pholsen, S., Rodchum, P. and Higgs, D.E.B. (2014). Dry Matter Yields and Quality of Forages Derived from Grass Species and Organic Production Methods (Year III).

Pak J Biol Sci.17: 898-904.

[23] Trivedi, B. K.(2002). Grasses and Legumes For Tropical Pastures, Indian Grassland and Fodder Research Institute, Jhansi.

[24]Chanartaeparporn, P.,Markvichitr, K., Prasanpanich, S., Koonawootrittriron, S., Choothesa, A.

andRukwamsuk, T. (2010). Leucaena Forage Supplementation for Metabolism Adaptation in Pre and Postpartum Dairy Cows. pp. 93-100. Proceedings of 48^thKasetsart University Annual Conference, Bangkok.

[25] Ndemanisho,E.E., Kimoro, B.N., Mtengeti, E.J. and Muhikambele, V.R.M. (2006). The Potential of Albizia lebbeck as a Supplementary Feed for Goats in Tanzania. Agroforestry Syst. 67:85-91

[26] Anchez,N. R. S. and Ledin, I. (2006). Effect of Feeding Different Levels of Foliage from Cratylia argentea to Creole Dairy Cows on Intake, Digestibility, Milk Production and Milk Composition.

Trop Anim Health Prod. 38:343–351.

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[29] Wittayakun, S., Innaree, W. and Pranamornkith, P. (2017). Yield, Nutrient Content and Rumen in vitro Digestibility of Giant Sensitive Tree (Mimosa pigra) as Dairy Feed. Asian J Agri &

Biol.5(4):355-360.

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225-234.

[31] Roberto, I.C., Mussatto, S.I. and Rodrigues R.C.L.B. (2003). Dilute-Acid Hydrolysis for Optimization of Xylose Recovery from Rice Straw in a Semi-Pilot Reactor. Ind. Crops Prod. 7:171-176.

[32] Van Soest, P.J. (1994). Nutritional Ecology of the Ruminant. 2^nd Cornell University Press, Ithaca, New York.

[33] Van Soest, P. J. (2006). Review: Rice Straw, the Role of Silica and Treatments to Improve Quality. Anim. Feed Sci. Technol. 130:137-171.

[34] Sarnklong, C., Cone, J. W., Pellikaan, W and Hendriks, W. H. (2010). Utilization of Rice Straw and Different Treatments to Improve Its Feed Value for Ruminants: A Review. Asian-Aust. J. Anim.

Sci. 23(5) : 680 - 692.

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[36] Singh, R.B. Sana R.C., Singh, M., Chandra, D., Shukla S.G.,Walli T.K., Pradhan P.K. and Kessels H.P.P.(1995). Rice Straw-Its Production and Utilization in India. Handbook for Straw Feeding Systems. ICAR, New Delhi.

[37] Datt, C.,Chhabra, A., Singh, N. P. and Bujarbaruah, K. M. (2008). Nutritional Characteristics of Horticulture Crop Residues as Ruminant Feed. Indian J Anim Sci. 78 (3): 312-316.

[38] Wittayakun, S.,Innaree, S., W. Innaree, W. and Chainetr, W. (2015). Supplement of Sodium Bicarbonate, Calcium Cabonate and Rice Straw in Lactating Dairy Cows Fed Pineapple Peel as Main Roughage. Slovak J Anim Sci.48 (2): 71-78.

[39] Anonymous. (2013). Balancing the Diet. Department of Agriculture and Fisheries, The State of Queensland. Access (18 May 2018). Available (www.daf.qld.gov.au/business-priorities/animal- industries/dairy/feed-and-nutrition/nutrition-for-lactating-dairy-cows/balancing-the-diet)

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Development and Performance Evaluation of a Cassava Digger Namely Curve Shear Blade Type

Sahapat Chalachai^1* Kritsana Naoprakhon¹ Rangsan Koodsamrong¹ Peeyush Soni² and Anuchit Chamsing³

1Agricultural Engineering and Technology,

Rajamangala University of Technology Tawan-ok, Bang Phra, Sriracha, Chonburi, Thailand

2 Agricultural Systems and Engineering, Asian Institute of Technology

3 Department of Agriculture, Agricultural Engineering Research Institute

*Corresponding author: sahapat@hotmail.com

Abstract

In this research were designed and tested a digging unit for its integration with a cassava harvester, suitable for Thai farms. The developed cassava digger was suitable for a medium size (36 horse powers) tractor for continuous working. This cassava digger was tested for its function of the blade types (curve shear blade type) at three different digging angles (20, 25 and 30degrees) and at three different forward speeds (1.3, 1.9 and 2.6 km/h). After modifying the cassava digger based on results of the initial functional test, its performance was evaluated in field. The scope of testing was field performance improvement, mainly to reduce draft force, fuel consumption, and harvesting loss to increase harvesting capacity and field efficiency. The results indicated that the best digging efficiency was obtained when testing with the curve shear type blade at low gears (L3). The results showed that the field capacity was 0.20 ha/h, fuel consumption per hectare was 27.08 l/ha, cassava loss in soil was around 6.74% and field efficiency was 95.40%.

Keywords: Digger, Harvesting, Curve shear blade type and Angle of blade

Introduction

Cassava was originated in the tropical areas of America, particularly in South America.

Mexico, Peru, Guatemala and Honduras are regions where cassava was found before three to five thousand years back, and then the plant was circulated across America and elsewhere. The transport of cassava to the African continent was accomplished by the slave brokers and Portuguese in the 15^th century [1]. Between 2006 and 2010, the world's cassava output grew at 1.93 % per year rate because producing countries of Congo, Mozambique, Ghana, Vietnam and Indonesia increased their productions to meet consumer demand and the increasing demand for renewable energy production. Cassava is considered as a highly economic crop for a country like Thailand. It is used basically as raw material for several industries. It is also used for two key purposes, firstly as energy crop for ethanol production that is needed for producing gasohol, and secondly as substitute for Methyl Tertiary Butyl Ether (MTBE) in bio-diesel production. Thailand is a major world exporter of cassava worth 2 billion USD (6 5 billion THB) per year. It is the fourth largest cassava producer after Nigeria, Brazil and Indonesia. In Thailand, the planted area for cassava is 1.2 million ha (7.91 million rai) which is the fourth largest area after rice, maize and rubber with a total production of 30 million tons[2].

In Thailand, there are two common harvesting practice patterns: a) mostly using human labor with simple indigenous tools; and b) using cassava digger attached to a tractor and then hand-picked by human labor [3]. However, analyses show that about 3 7 % of the labor cost and 10% of the harvesting cost could be saved by using the second (mechanized) pattern. Currently, labor shortage is a major constraint for cassava production in Thailand, especially for harvesting.

Because of the growing economy, and in particular industrial growth, there has been a shift of labor from the agricultural sector to the industrial sector, influenced by more comfortable working

BO1013

conditions, as well as higher wages. Hence, this study focuses on design, development and field evaluation of a digger which could contribute to overcoming the current labor shortage problem, provide improved performance, mainly to reduce draft, fuel consumption, and harvesting loss to increase harvesting capacity and field efficiency.

Now a day, many reported constraint of cassava harvesting by using a cassava digger attached to a 50 hp tractor of larger is its limitation in continuous operation and the tractor is too large. The main reason for this limitation is because the cassava roots that were dug in previous pass are pressed by tractor wheel in the following pass – causing to increase damage and yield losses. As a current practice, a number of laborers are required to wait along the digging rows to collect the dug root out immediately after digging before continue with the next row. Retain link operation; harvesting loss and high fuel consumption are thus very commonly reported problems in the current situation.

To develop and evaluate a cassava digger attached to 36 hp tractors a testing unit was developed for examining related components including Curve shear blade (size and blade angle).

Harvesting loss, produce damage, fuel consumption and field capacity were among the major assessment indicators.

Materials and Methods

1. Current harvesting methods and physical properties of cassava

The most difficult process in cassava production is harvesting [4], which occurs from six to seven months after planting (MAP) for most of the varieties [5]. After harvesting, cassava starts to deteriorate as early as within one to three days; therefore, harvesting of cassava should be finished on time [6]. In Thailand, cassava is ready for harvest starting from 8 to 12 MAP. The method of harvesting, by small scale farmers in Thailand, is by using specific hand tools [7]. There are four steps in harvesting. The first step is to cut stems before harvesting roots; cassava stems are both cut and collected for using as stock for the next crop planting or some farmers just remove it from the field [8]. The second step is to dig or pull cassava roots from the soil using a cassava lifter indigenously developed by Thai farmers that is locally known as “Mac hoe” [9]. The third step is to collect and cut cassava roots from the stem, and eventually carry it to the truck for transportation and sale [10].

Mechanical harvesting of cassava involves the use of a harvesting implement integrally hitched to a prime mover, usually tractor, to uproot the cassava roots. However, manual effort is still required after the uprooting has been completed to collect and separate the cassava roots from stem. The field is also required to be in good condition for an optimum mechanical cassava harvesting operation such as: a) the field should be free from hidden obstructions (rocks, roots, stumps etc. up to 40 cm deep) of sizes that can interfere with lifting the root, b) having good weed control as they block the lifters, and c) cutting down (coppicing) the cassava plant to a stalk height of about 30cm prior to harvesting [11].

Presently, the majority of large-scale cassava farmers in Thailand employ tractor-mounted cassava digger. Ironically, harvesting cost constitutes the largest share in cassava production due to the high labor requirement and high labor wages, especially during months of labor shortage [12]. Given the importance of mechanization in cassava production, cassava diggers have been developed since over rest 30 years. Figure 1 shows the cassava diggers that are currently available in Thailand. Based on the shear blade used, the existing cassava diggers can be broadly grouped as fork shear blade type and curve shear blade type [3].

Information on the traditional harvesting method and performance was collected from the Office of Agricultural Economics, Thai Ministry of Agriculture and Cooperative, previous research form Field Crops Research Institute, and/or directly measured on cassava farms. It is shown that the average capacity of manual harvesting was 0.066 ha/man-day, or the man-hour requirement was 121.83 man-h/ha. It is clear that cassava products from Thailand can remain competitive only if farmers increase their yields through the use of improved varieties and better

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production practices. Presently, the main operating costs are pertaining to harvesting, weeding, planting and fertilizer application, which are approximately 37%, 27%, 18% and 12% of the total operating cost respectively [13].

The physical characteristics of cassava stem of popularly grown Rayong-81 and Huay Bong varieties compared statistically. The comparison of the key characteristics (dimensions, moisture content and distance of cassava plant and dimensions of cassava roots) of cassava showed that the maximum diameter and bend of the stem of Huay Bong is bigger than Rayong-81 variety. The mean height, weight of stems, and width of canopy at the top and the bottom are higher for Rayong-81. The mean values of distance between raws of Huay Bong is larger than Rayong-81 variety. The mean values of diameter and weight of rhizome are more for Huay Bong. The mean weight of root, number of roots, and root depth are higher for Huay Bong variety. The mean values of distance between rows are used to select the size of tractor. The maximum length across the rows of root is used to design the size of digger. The maximum root depth is used for the design of the height of digger.

a) Fork shear blade

b) Curve shear blade Figure1:Types of cassava excavation blades available in Thailand 2. Soil properties of the field

While designing the digger for cassava, it is important to characterize the soil in the experimental field. The resistance of soil affects lifting force for cassava root, so measurement of soil properties around the root was performed. Some of the soil properties were measured in laboratory prior to the field experiments, while other soil properties were measured in the field.

The experiments were conducted in the field at Buriram province, Thailand. Table 1 summarizes soil properties measured for the test site.

Table 1: Soil properties of the test field at Buriram province of Thailand

Item Detail

1) Type of soil Sandy loam red color, and having some gravel

2) Mean soil clod diameter (mm) 1.35

3) Soilmoisture content (%w.b.) 16.16

Item Detail

4) Bulk density of soil (g/cm³) 1.22

5) Consistency limits Plastic limit (%w.b.) Liquid limit (%w.b.) Plasticity Index (Ip)

42.20 86.2 44.06 6) Penetrometer profile and cone index, MPa (15

places) at 50 mm at 100 mm at 150 mm at 200 mm at 250 mm at 300 mm

0.53 0.90 1.09 2.24 2.58 3.70 3. Design and Fabrication of the Prototype

The digger was designed to meet the current cassava root harvesting practices. Before designing the digger, the types and problems of cassava excavation blades available in the market were studied. In this study curve shear blade type (Fig. 2a) were used. This information was used for analysis of the problem and to guide the design and development of the prototype of cassava root digger. The knowledge and technology used for fabrication of digger was kept simple, so that the local workshops can manufacture it without difficulty. The prototype of the digger is shown in Figure 2b.

4. Experimental setup

The cassava digger was tested at Buriram province, Thailand. The type of soil, moisture content and soil cone index were determined for the site. The test beds were selected at cassava planting field at Buriram province and prepared by using the method of agriculturalist. ‘Rayong 81’ variety was planted in a bed prepared with the average distance between the rows being 0.77 m and the distance between the plants being 0.85 m. A field of 12 such plots, each with a size of 350 m2 was used.

A dynamometer was used to determine draught force for each mechanical cassava harvester (Fig. 3a). The instrument recorded the force required to pull the implement. The instrumented tractor had the implement hitched to it and was set to a neutral gear and pulled by another tractor (Fig. 3b). Load and no-load draught forces were obtained for each implement in working and transport positions, respectively.

a) Curve shear blade type b) Prototype of curve shear blade type digger Figure 2: Type of cassava shear blades in Thailand and prototype (All dimensions are in mm.)

510

340

280 0

925

900

560

780

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a) Dynamometer b) The draught measurement procedure Figure 3: Draught force determination

5. Performance Evaluation

After designing the prototype of cassava digger, the performance indicators used to evaluate its performance included: a) digging capacity, b) digging efficiency, c) power requirement, d) cassava root loss in the soil, e) specific energy consumption, and f) fuel consumption.

a) Digging capacity (unit/h)

Dc=𝑁𝑢𝑚𝑏𝑒𝑟𝑜𝑓𝑐𝑎𝑠𝑠𝑎𝑣𝑎𝑝𝑙𝑎𝑛𝑡𝑠𝑑𝑖𝑔𝑔𝑒𝑑 (𝑢𝑛𝑖𝑡)

Time (h) (1)

b) Digging efficiency (%)

Ed = Dc

Theoretical digging capacityx 100 (2) The theoretical digging capacity is estimated by the speed of tractor.

c) Power requirement

Power requirement = Determined from the net power (3)

d) Cassava root loss in the soil (%)

CL =𝑁𝑢𝑚𝑏𝑒𝑟𝑜𝑓𝑐𝑎𝑠𝑠𝑎𝑣𝑎𝑏𝑟𝑜𝑘𝑒 (𝑑𝑎𝑚𝑎𝑔𝑒𝑑) 𝑖𝑛𝑠𝑜𝑖𝑙 (𝑟𝑜𝑜𝑡)

Total number of cassava roots digged (root) x 100 (4) e) Specific energy consumption (kW-h/unit)

Specific energy consumption = Power requirement (kW)

Digging capacity (unit/h) (5)

6) Fuel consumption (l/ha)

Fc =Fuel consumed (l)

Area covered (ha) (6)

Three different blade angles (20, 25 and 30 degree) were used at three different tractor speeds (low-2, low-3, and high-1) (Fig. 4). The dynamometer was used to measure the draft force requirement. A comparison between treatment means was done by least significant difference (LSD) at P<0.05. All observations were replicated five times.

Figure 4: Experimental design for digger

Results

The preliminary testing of the digger aimed to determine the necessary working conditions and to break open the hard soil that covers cassava root and lift it up on the ground to enable harvesting. The test consisted of five trials aimed at understanding the effects of the type of blade, angle of blade, and traveling speed of tractor on draft force requirement.

Effect of angle of the blade on draught force

The draft requirement of the cassava digger at different blade types and angles was determined in the field. The draft of digger with curve shear blade types and different angles at the same traveling speeds of 1 .3 km/h are presented in Table 2 . The average draft of the digger with curve shear blade type and blade angle range of 2 0 to 3 0 deg was between 3 . 4 2 to 8.36kN/row, and the wheel slip range of 20 to 30deg was increase from 8.26 to 10.70kN/row.

Effect of traveling speeds on draught force and power requirement

The draft requirement of the cassava digger at different traveling speeds was determined in the field. From the results, a 20 degree blade angle was selected for this test because of its lower draft requirement. The draft of digger with different traveling speeds of 1.3, 1.9, and 2.6 km/h are presented in Table 3. The average drafts of the was between 3.42 to 7.4 kN/row, and the wheel slip with different traveling speeds was reduce start from 8.26 to 5.7 km/h

Table 2:Average draft requirement and wheel slip of digger at different blade types and blade angles at the same traveling speeds of 1.3 km/h

Type of blade

Draft per unit width, kN/row Wheel slip, %

Angle of blade Angle of blade

20 25 30 20 25 30

Curve shear 3.42±0.44 5.58±0.52 8.36±0.48 8.26±0.40 9.14±0.57 10.70±0.57 (Mean± standard deviation, n=5)

Table 3:Average draft requirement and wheel slip of digger at different blade types and operation speeds (20 degree blade angle)

Type of blade

Draft per unit width, kN/row Wheel slip, % Operating speed, km/h Operating speed, km/h

1.3 1.9 2.6 1.3 1.9 2.6

Curve shear 3.42±0.44 5.16±0.48 7.4±0.62 8.26±0.40 7.28±0.41 5.7±0.62 (Mean± standard deviation, n=5 row)

Digging speeds Low 2

Low 3

High 1

The same as b1 The same asb1

20 degree b1

25 degree 30 degree Angle of the digging blade

Curve shear

Prototype digger with a1

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After obtaining the results of draft requirement of cassava digger, the Equations 7 and 8 were used to calculate tractor power requirement.

𝐷𝑟𝑎𝑤𝑏𝑎𝑟𝑃𝑜𝑤𝑒𝑟(𝑘𝑊) = 𝐷𝑟𝑎𝑢𝑔ℎ𝑡𝐹𝑜𝑟𝑐𝑒(𝑘𝑁)𝑥𝐴𝑣𝑒𝑟𝑎𝑔𝑒𝑆𝑝𝑒𝑒𝑑 (𝑚/𝑠) (7) 𝐵𝑟𝑎𝑘𝑒 𝑝𝑜𝑤𝑒𝑟 (𝑘𝑊

𝑚²) =𝐷𝑟𝑎𝑤𝑏𝑎𝑟𝑃𝑜𝑤𝑒𝑟

0.19 (8)

Table 4 shows the drawbar power, and brake horsepower at different traveling speeds (1.3, 1.9 and 2.6 km/h) observed for cassava digger. The average drawbar power ranges from 1.23 to 5.33 kW.

Table 4: Average power requirement in digging at Buriram province

Type Speed (km/h) Drawbar Power (kW) Brake Hp (kW) Hp

Curve shear 1.3 1.23±0.16 6.50±0.83 4.85±0.74

1.9 2.73±0.25 14.39±1.33 10.73±1.88

2.6 5.33±0.44 28.04±2.34 20.92±2.07

(Mean± standard deviation, n=5)

Field performance evaluation of digger

The designed cassava digger was evaluated for its performance on indicators, such as:

working width, depth of digging, actual travelling speed, fuel consumption per hectare, field capacity, field efficiency and cassava losses in the soil. The three different gears of tractor Low-2 (1.3 km/h), Low-3 (1.9 km/h) and High-1 (2.6 km/h) were used in this study. The blade angle was selected at 20 deg and the engine speed was 1200 rpm.

The results in Table 5 showed that the curve shear type blade with gear L3 had the highest field efficiency and the least cassava losses in the soiland fuel consumption per hectare.

Therefore, the curve shear type with gear L3 is deemed suitable for this area. Figure 5 shows the cassava digger testing in the field. The operating depth was about 30 cm.

Table 5: Field performance of cassava digger

Item Digger type

CL2 CL3 CH1

a) Working width, (m) 0.80 0.80 0.80

b) Depth of digger, (m) 0.29 0.30 0.28

c) Actual travelling speed, (km/h) 1.30 1.90 2.60

d) Digging capacity, (ton/h) 9.87 11.50 12.99

e) Digging efficiency, (%) 92.11 95.94 96.96

f) Power requirement, (kW) 6.50 14.39 28.04

g) Specific energy consumption, (kW-h/ton) 0.66 1.25 2.15

h) Fuel consumption per hectare, (L/ha) 27.82 27.08 25.32

i) Cassava losses in soil, (%) 6.35 6.74 6.95

j) Field capacity, (ha/h) 0.19 0.20 0.21

k) Field efficiency, (%) 94.12 95.40 93.21

(CL2 = Curve shear blade type with gear Low – 2, CL3 = Curve shear blade type with gear Low – 3, and CH1 = Curve shear blade type with gear High – 1, n = 3)

a) Operating of digger b) The cassava root after digging Figure 5: Field testing of cassava digger

Discussion

The draft of digger increased rapidly with increasing blade angle at a given speed. The analysis of variance (ANOVA) showed that the type of blade and angle of blade had a significant effect on draft requirement but the angle of the blade was non-significant effect on type of the blade (P0.05) (Table 6).

Table 6: ANOVA result on draft requirement with different blade angles (traveling speeds of 1.3 km/h)

Source of variable df SS MS F P - value

Type of blade (A) 1 73.320 73.320 224.792 0.000

Angle of blade (B) 2 142.706 71.353 218.762 0.000

Interaction (A*B) 2 0.761 0.380 1.166 0.329

Error 24 7.828 0.326

(Significant at 5% level)

The draft of the digger increased rapidly with increasing traveling speed. The analysis of variance (ANOVA) showed that the type of blade and operation speed had a significant effect on the draft requirement and operating speed was less significant effect on type of the blade (P0.05) (Table 7)

Table 7: ANOVA result on draft requirement at different operation speeds (20 degree blade angle)

Source of variable df SS MS F P - value

Type of blade (A) 1 36.520 36.520 81.277 0.000

Operating speed (B) 2 78.731 39.365 87.608 0.000

Interaction (A*B) 2 4.595 2.297 5.113 0.014

Error 24 10.78