A Study on Sustainability of Small Holder Dairy Farming on Agroforestry System: Case Study in Lembang West Java Province, Indonesia.

A STUDY ON SUSTAINABILITY OF SMALL HOLDER

DAIRY FARMING ON AGROFORESTRY SYSTEM: CASE

STUDY IN LEMBANG WEST JAVA PROVINCE, INDONESIA

WINDI AL ZAHRA

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2013

STATEMENT

I, Windi Al Zahra, herby stated that this thesis entitled:

A Study on Sustainability of Small Holder Dairy Farming on Agroforestry System: Case Study in Lembang West Java Province, Indonesia

Is a result on my own work under the supervisor advisory board during the period February 2012- April 2013 and that it has not been published before. The content of the thesis has been examined by the advising advisory board and external examiner.

Bogor, April 2013

Windi Al Zahra

iv

RINGKASAN

WINDI AL ZAHRA. KAJIAN KEBERLANJUTAN USAHA

PETERNAKAN RAKYAT SAPI PERAH PADA SISTEM AGROFORESTRY: STUDI KASUS LEMBANG, JAWA BARAT. Di bimbing oleh BAGUS P. PURWANTO, M. FAIZ SYUAIB, and MASAKAZU KOMATSUZAKI

Usaha peternakan sapi perah mempunyai peranan penting dalam memenuhi kebutuhan gizi manusia, karena susu yang di hasilkan merupakan pangan lengkap yang sempurna. Perkembangan usaha peternakan sapi perah di Pulau Jawa akan menghadapi permasalahan serius, terkait dengan kelangkaan pakan. Sistem agroforestry dapat menjadi salah satu jalan dalam memenuhi kebutuhan hijauan untuk keberlanjutan usaha peternakan sapi perah. Lebih jauh, informasi mengenai potensi sistem agroforestry perlu diketahui lebih jauh, oleh karena itu penelitian ini dilakukan. Penelitian ini dilakukan di Agroforestry area, Lembang, Jawa Barat dan laboratorium lapang di Insitut Pertanian Bogor, Indonesia. Hasil penelitian menunjukkan adanya penurunan produktivitas secara signifikan dengan meningkatnya kerapatan pohon dan tinggi nya intensitas naungan (p<0.05). Hasil penelitian di laboratorium lapang juga menunjukkan adanya pengaruh naungan, pemberian pupuk organik dan pengaturan waktu panen terhadap kuantitas dan kualitas hijauan. Sebesar 31.1% produksi hijauan pada P. purpureum menurun dengan bertambahnya intensitas naungan. Kualitas hijauan seperti produksi bahan kering, abu, lemak dan protein secara dramatis dipengaruhi intensitas naungan (p<0.05). Berdasarkan hasil penelitan ini, dilakukan simulasi dengan beberapa skenario. Hasil simulasi menunjukkan adanya kemungkinan peningkatan TDNA (Ketersediaan TDN sebesar 34.09% dibandingkan dengan kondisi tanpa adanya management (penambahan pupuk organik dan pengaturan waktu panen). Nilai ini akan mampu memberikan tambahan pakan untuk 2311 (Unit standar) sapi perah di Lembang. Penilaian ekonomi juga di lakukan, dan menunjukkan tenaga kerja meliputi 15.12% dari total produksi, dan 17.63% sebagai gross margin. Sistem Agroforestry juga layak secara ekonomi. Sebesar keuntungan peternak per unit dan harga meningkat sebesar 18.38% dengan adanya perbaikan management. Kata Kunci: Usaha peternakan sapi perah, Agroforestry, Keberlanjutan.

SUMMARY

WINDI AL ZAHRA. A Study on Sustainability of Small Holder Dairy Farming on Agroforestry System: Case Study in Lembang West Java Province, Indonesia. Under the supervision of BAGUS P. PURWANTO,M. FAIZ SYUAIB, and MASAKAZU KOMATSUZAKI

Dairy farming practices is one of the empowerment agriculture sectors in Asia, due to Labor and nutrition fact on milk. The fastest dairy farming development found in Java island, noted as the most populated island in Indonesia. Todays, farmers conduct endeavor varied ways in filling forage demand for the dairy cattle, one of them by Agroforestry system. An appropriate management on Agroforestry system is highly required in enhancing forage production. However, the information of potency that might be occuring not clearly understood, therefore the broad objection of this research is to explore the potency of Agroforestry system due to sustainability of small scale dairy farming.

The observation of Agroforestry system was conducted in Lembang (West Java). Several plots have been designed West Java and As 78 of farmers have been involved. We observed, more than 36% of dairy farmers attempted the forage by utilizing forest area. We calculate the highest forage yield was gained in low-density forage (21.01 Mg/ha, 12% shading level). The lower forage yield (7.09 Mg/ha) was found in middle density plot, since it higher levels of shade (78%). In general discussion, it could be seen that in higher density plot showed higher nutrients compound specially in DM, fiber, protein and fat.

Experimental field has been design to understand the effect of shading treatment to the forage. In field experiment research there were two kinds of variety forage used; P. purpureum (King Grass) and S. Splendida. Pointed on the influence of shading levels, we were stressing on several treatments; un-shaded (0%) and shade treatments. The artificial shading treatment (60% and 80%) was applied for this research. Organic fertilizer was used as the secondary factor. As 30 Mg/ha, 20 Mg/ha and 10 Mg/ha of organic fertilizer were conducted. We were simulating for 40d, 50d and 60d of the harvest time. Therefore, totally 81 plots have been designed for this research. As 31.1% of forage yield was slowly decreasing as increasing shading intensities.Underneath shading condition such as 60% and 80%, the forage yield required higher organic fertilizer. In 40 and 50 days of plantation, the additional 30 Mg/ha organic fertilizer presences the highest forage yield underneath limitation of sun availability. The plant height was gradually increasing with the higher number of levels of shade. Chlorophylls content were the other respond showed by plant as the effect of shading treatment. It could be obtained that as 29.03% and 23.41% of chlorophyll content was increasing rapidly on P. purpureum, and S. splendida respectively.

The average of DM production was depleting as 28.69% for S. splendida, this amount was lower compared with P. purpureum (36.50%). Ash compound was significantly influenced ash content (p<0.05). We also observed that levels of shade has a significantly effect due to fat content on P. purpureum (P<0.05). The average of data gained showed that fat content was increase for 16.35% as the raising of levels of shade in S. splendida. The less number of irradiance accepted by plants, showed the increment of protein content (%) (p<0.05). The average of crude protein content was increasing for 26.95% in P. purpureum and 23.41% in

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S. splendida. There was a trend on the increment of crude fiber content influenced by Levels of shade and Defoliation management.

We calculated TDNA (Total Digestible Nutrient Available), that provided in forest in supplying TDN amount for the feed of dairy cattle in Lembang. The calculation of TDNA (Mg/yr) was carrying in two varied ways. The first was the actual TDNA in agroforestry system (TDNA without management improvement). In addition we also acquired the information regarding TDND (Total Digestible Nutrient Demand). We gained that as totally 15782 LSU was requiring approximately 35.895,15 TDN Mg/yr. It was gained that as 7.012,04 Mg/yr of TDN in the Agroforestry system in Lembang. In another hand, it affirmed that TDNA without management improvement supported 19.53% of totally TDND of the dairy cattle. Moreover, we also verified the amount of TDNA with management improvement. Likewise, the additional organic fertilizer and defoliation management has been conducted in order to improve forage production and its quality. We also obtained the number of carrying capacity (C) for 3100 LSU amounts of dairy cattle. This number increases with management improvement for 5411 LSU. We calculate that as 19.760,74 IDR/ days did dairy farmers issue the daily feed cost. The daily feed cost will be lower for 15.16% or as 21.561 IDR/days since farmers do some management improvement. Highlighted on the farmers income, we also obtained that profit was higher for 17.63%.. It was gained, as 18.38% of cost per unit and its price were getting higher with better improvement management.

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A STUDY ON SUSTAINABILITY OF SMALL HOLDER DAIRY FARMING ON AGROFORESTRY SYSTEM: CASE STUDY IN LEMBANG WEST JAVA

PROVINCE, INDONESIA.

WINDI AL ZAHRA D151110091

A thesis submitted for the Degree Programs of Master of Science in Animal Production and Technology

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY 2013

x

A thesis submitted for the Degree Programs of Master of Science in Animal Production and Technology

Dr. Ir. Bagus P. Purwanto, M.Sc. Agr Supervisor

uaib M.Sc. A r Dr. Masakazu Komatsuzaki

Co Supervisor

Program Coordinator

Prof. Dr. Ir. Muladno, M.SA

o

9 SEP

2013

Research Title

Name Student ID Study Program

: A Study on Sustainability of Small Holder Dairy Farming on Agroforestry System: Case Study in Lembang West Java Province, Indonesia

: Windi Al Zahra : D 15111 0091

: Animal Production and Technology

Sign

A thesis submitted for the Degree Programs of Master of Science in Animal Production and Technology

Research Title : A Study on Sustainability of Small Holder Dairy Farming on Agroforestry System: Case Study in Lembang West Java Province, Indonesia

Name : Windi Al Zahra Student ID : D151110091

Study Program : Animal Production and Technology

Sign

Supervisor Comitee

Dr. Ir. Bagus P. Purwanto, M.Sc. Agr Supervisor

Dr. Ir. M. Faiz Syuaib, M.Sc. Agr Co Supervisor

Dr. Masakazu Komatsuzaki Co Supervisor

Program Coordinator

Prof. Dr. Ir. Muladno, M.SA

Dean of Graduate School

ACKNOWLEDGEMENT

In the name of Allah, the Most Gracious and the Most Merciful Alhamdulillah, all praises to Allah for the strengths and His blessing in completing this thesis entitled a study on sustainability of small holder dairy farming on agroforestry system: case study in Lembang west java province, Indonesia. This thesis submitted for the Degree Programs of Master of Science in Master of Science in Animal Production and Technology.

I would like to express my gratitude to Dr. Ir. Bagus P. Purwanto, M.Sc. Agr who served as my major advisor for the useful comments, remarks and engagement through the learning process of this master thesis. I am also grateful to my other committee members, Dr. Ir. M. Faiz Syuaib. M.Sc. Agr and Dr. Masakazu Komatsuzaki from Ibaraki University Japan, as for their constructive guidance, valuable advice and cooperation. This research is conducted as the part of Double Degree Program both Bogor Agriculture University and Ibaraki University, Japan.

I also addressed my gratitude to all staff and class mates in Animal Production and Technology program, Graduate school Bogor Agriculture University. Finally, I would like to thank my family,

Mustahgfirin for making all of this possible through their continued support, pray. I will be grateful forever for your love. They are the reason that I have been able to succeed. Finally, I hope this research will be useful to solve forage scarcity problems, in enhancing dairy farming sustainability in Indonesia.

TABLE OF CONTENTS

Page

Table of Contents ... xi

List of Table ... xiii

List of Figure ... xv

List of Appendices ... xvii

CHAPTER I ... 1

General Introduction ... 1

CHAPTER II. Agroforestry system supported Sustainability of Dairy Farming; Case study, Agroforestry system in Lembang district Area, West Java, Indonesia ... 4

2.1 Introduction ... 4

2.2 Method ... 5

2.3 Data Collection and Procedur ... 5

2.3.1 The calculation of carrying capacity on Agroforestry system .... 6

2.3.2 The analytical framework on economic calculation ... 7

2.4 Results and Discussion ... 8

CHAPTER III. An Experimental Treatment, A learnt from Actual Condition; The effect of shading and organic fertilizer on forage production ... 12

3.1 Introduction ... 12

3.2 Method ... 13

3.3 Soil and Fertilizer Analysis Measurement ... 15

3.4 Sampling Procedur and Data Collection ... 16

3.4.1 Plant Production ... 16

3.4.2 Forage layer height and leaf area ... 17

3.4.3 The measurement of Chlorophylls Content. ... 17

3.4.4 The analyses of forage quality. ... 18

3.3.4.1 Dry Matter Analysis ... 18

3.3.4.2 Ash Analysis ... 19

3.3.4.3 Fat Analysis ... 19

4 3.4.4.5 Fiber Analysis ... 22 3.4.5 Statistical Analysis. ... 22 3.4 Result and Discussion ... 24

3.4.1 Plant Responses due to the level of irradiance, organic fertilizer and Defoliation Management ... 24 3.4.2 The Nutrient Analysis of P. Purpureum and S. Splendida ... 44 CHAPTER IV

General Discussion ... 62 CHAPTER V

Conclusion and Recommendation ... 73 CHAPTER V

LIST OF TABLES

Number Page

1. Measurement of forage yield on varied plot designed (low, middle and

high density) ... 10 2. Biomass Production (kg/m2) obtained with the different distance (1 m to

5 meter) from the tree ... 10 3. The measurement of forage quality in Agroforestry System, in three

different plots (low, middle and high density plot) ... 11 4. The analyses of Fertilizer and Soil Sample ... 16 5. The Information of Component of Organic Fertilizer Analysis measured

in Field Center Experimental Research Faculty of Animal Science,

Bogor Agriculture University. ... 16 6. The Information of Soil Quality measured in Field Center Experimental

Research Faculty of Animal Science, Bogor Agriculture University ... 16 7. The Measurement forage yield (Mg/ha) P. Purpurem on different levels

of shade, organic fertilizer and defoliation management treatments. ... 25 8. The Measurement fresh weight production (Mg/ha) of S. Splendida on

levels of shade, organic fertilizer and defoliation management

treatments ... 27 9. The Measurement plant layer height (cm) P. Purpureum on Levels of

Shade, organic fertilizer and defoliation management treatments ... 30 10.The Measurement plant height (cm) on S. Splendida on Levels of Shade,

organic fertilizer and defoliation management treatments ... 32 11.The Measurement of leaf size (mm2) on P. Purpureum on Levels of

Shade, organic fertilizer and defoliation management treatments ... 34 12.The Measurement of leaf size (mm2) on S.Splendida on Levels of Shade,

organic fertilizer and defoliation management treatments ... 36 13.The Measurement Chlorophyll content (mg/gram) of P. Purpureum on

Levels of Shade, organic fertilizer and defoliation management

treatments ... 38 14.The Measurement Chlorophyll content (mg/gram) of S.Splendida on

Levels of Shade, organic fertilizer and defoliation management

6 15.The Measurement Chlorophyll-a and chlorophyll-b (mg/gram) of P.

Purpureum on Levels of Shade, organic fertilizer and defoliation

management treatments ... 41 16.The Measurement Chlorophyll-a and Chlorophyll-b (mg/gram) of S.

Splendida on Levels of Shade, organic fertilizer and defoliation

management treatments ... 43 17.The Measurement dry matter (DM) production (Mg/ha) of P.

Purpureum on Levels of Shade, organic fertilizer and defoliation

management treatments ... 45 18.The Measurement dry matter (DM) production (Mg/ha) of S. Splendida

on Levels of Shade, organic fertilizer and defoliation management

treatments ... 47 19.The Measurement ash content (%) of P. Purpureum on Levels of Shade,

organic fertilizer and defoliation management treatments ... 49 20.The Measurement ash content (%) of S. Splendida on Levels of Shade,

organic fertilizer and defoliation management treatments ... 50 21.The Measurement fat content (%) of P. Purpureum on Levels of Shade,

organic fertilizer and defoliation management treatments ... 52 22.The Measurement fat content (%) of S.Splendida on Levels of Shade,

organic fertilizer and defoliation management treatments ... 53 23.The Measurement protein content (%) of P. Purpureum on Levels of

Shade, organic fertilizer and defoliation management treatments ... 55 24.The Measurement protein content (%) of S.Splendida on Levels of

Shade, organic fertilizer and defoliation management treatments ... 56 25.The Measurement fiber content (%) of P. purpureum on Levels of

Shade, organic fertilizer and defoliation management treatments ... 58 26.The Measurement fiber content (%) of S.Splendida on Levels of Shade,

organic fertilizer and defoliation management treatments ... 60 27.Distribution of Dairy cattle in Indonesia (Java, Sumatra and others

island during 2007-2011 ... 63 28.The information of dairy cattle population and TDND based on its

growing stage ... 65 29.The nutritional requirement of the dairy cow with the weight 450 Kg ... 67

30.Nutrient content from feeding composition of the dairy cow ... 68 31.The economic calculation of dairy farming enterprises in Lembang,

8 LIST OF FIGURES

Number Page

1. Site of Agroforestry research, Lembang West Java. ... 5 2. Sampling plot on agroforestry system in Lembang, West Java ... 6 3. The outspreading of household condition due to forage provision in

Lembang, West Java ... 8 4. Two kinds variety were used in the research (1) P. Purpureum, (2)

S.Splendida ... 13 5. The trend of solar irradiance on different of the level of shades ... 14 6. Defoliation management introduced in this research ... 14 7. Showed the microclimate condition among the research field at Field

Work Center, Faculty of Animal Science, Bogor Agriculture University,

(a) Temperature, (b) humidity, (c) rainfall, (d) solar irradiance. ... 15 8. Plot Design ... 23 9. The main effect levels of shade on forage yield P. Purpureum.

Subscripts with the same letter showed the significant different test by

Least Square Determination (LSD) in P<0.05... 26 10.The interaction both fertilization and defoliation management on forage

yield P. purpureum ... 27 11.The main effect defoliation management on forage yield (Mg/ha)

S.Splendida. Subscripts with the same letter showed the significant

different test by Least Square Determination (LSD) in P<0.05 ... 28 12.The interaction both fertilization and levels of shade measurement on

fresh weight production of S.Splendida ... 29 13.The main effect levels of shade measurement on plant height (cm) of P.

Purpureum. Subscripts with the same letter in the same column showed the significant different test by Least Square Determination (LSD) in

P<0.05 ... 31 14.The interaction both defoliation and fertilization treatment measured on

plant height of P. Purpureum ... 32 15.The main effect levels of shade measurement on plant height (cm) of S

Splendida. Subscripts with the same letter showed the significant

16.The main effect (1) levels of shade on leaf size (mm2) of P. Purpureum.

Subscripts with the same letter in the same column showed the significant different test by Least Square Determination (LSD) in

P<0.05. ... 34 17.The interaction both defoliation and fertilization treatment measured on

leaf size of P. Purpureum ... 35 18.The main effect (1) levels of shade and (2) defoliation management on

leaf size (mm2) of S.Splendida. Subscripts with the same letter in the same column showed the significant different test by Least Square

Determination (LSD) in P<0.05 ... 36 19.The interaction both defoliation management and levels of shade

measurement on leaf size of S.Splendid ... 37 20.The main effect levels of shade on Chlorophyll content (mg/gram) of P.

Purpureum. Subscripts with the same letter in the same column showed the significant different test by Least Square Determination (LSD) in

P<0.05 ... 39 21.The main effect levels of shade on Chlorophyll content (mg/gram) of

S.Splendida. Subscripts with the same letter in the same column showed the significant different test by Least Square Determination (LSD) in

P<0.05 ... 40 22.The mean effect levels of shade and measurement on (1) Chlorophyll-a

(mg/gram) and (2) Chlorophyll-b (mg/gram) of P. Purpureum.

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 42 23.The mean effect levels of shade and measurement on (1) Chlorophyll-a

(mg/gram) and (2) Chlorophyll-b (mg/gram) of S. Splendida. Subscripts with the same letter in the same column showed the significant different

test by Least Square Determination (LSD) in p<0.05 ... 43 24.The main effect (1) levels of shade and (2) defoliation management of

P. Purpureum on DM production. Subscripts with the same letter in the same column showed the significant different test by Least Square

Determination (LSD) in p<0.05 ... 45 25.The interaction both defoliation management and the additional organic

fertilizer on leaf size of P. Purpureum ... 46 26.The main effect levels of shade of S.Splendida on DM production.

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 47 27.The interaction both levels of shade and the additional organic fertilizer

10 28.The main effect levels of shade of P. Purpureum on ash content (%).

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 50 29.The mean effect levels of shade of S.Splendida on ash content (%).

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 51 30.The mean effect levels of shade of P. Purpureum on fat content

(%).Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 53 31.The main effect levels of shade of S.Splendida on fat content (%).

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 54 32.The main effect levels of shade of P. Purpureum on protein content (%).

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 56 33.The mean effect levels of shade of S.Splendida on protein content (%).

Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 57 34.The main effect (1) levels of shade and (2) defoliation management of

P. Purpureum on fiber content (%). Subscripts with the same letter in the same column showed the significant different test by Least Square

Determination (LSD) in p<0.05... 59 35.The main effect defoliation management of S.Splendia on fiber content

(%). Subscripts with the same letter in the same column showed the

significant different test by Least Square Determination (LSD) in p<0.05 60 36.Overview the dairy cattle population and milk production in Indonesia. .. 62 37.The comparisons both TDND and TDNA without and with management

improvement in Agroforestry system in Lemban ... 66 38.The comparisons of daily feed cost paid by farmers in low, middle and

high density respectively. ... 68 39.The comparisons of additional cost for renting land paid by farmers in

low, middle and high density respectively ... 69 40.The comparisons of daily feed cost issued by farmers without and with

1

CHAPTER I.

1. 1. General Introduction

The elevated of Indonesian‘s civilization-more than 237 million people with the growing rate for 1.49% (National Statistic 2011), less number of agriculture area, and the high number of food imports are major problems occuring now a days. Food staple- rice is no doubt required for human, wherase it does not support at all. However, the human trend consumption is change. People realize, milk contains important nutrients such kinds of vitamin, protein and mineral that could not be found in others food, therefore the awarness of people for consuming milk is rising.

Dairy products contribute 15–20% of human intake of total fat, 25–33% of saturated fat and about 15% of dietary cholesterol in the USA (Havel, 1997). In moderate economic growth, per capita consumption of temperate fruit, poultry, beef, other meat, baked products and dairy goods will grow most rapidly. In general, awarness of importance of milk consuming is enlarging with the escalation of household income. Despite the majority of people still regareded milk as luxurious beverage, but it recorded that the share of milk in monthly per capita food expenditure was 16.3% and 14.8% in urband and sub urban areas respectively (Sulastri 2005).

It is assessed that the amount of dairy cattle reachs 597.000 heads, that producing 925.775 tonnes of milk. It covers 30% of national milk production. Regrettably, this amount is insufficient in filling milk demand, consequently Indonesia goverment supposed to do import. Now a days, as 70% of milk production supplies from others country such as Australia, New Zealand Ect. Government is trying to improve National milk production, considering 90% of dairy farming is running by small scale enterprises, only 10% is proceeding by industrial scale. They are trying to improve milk production by varied ways, for example fixing dairy cattle performace, reproduction, Ect. Unfrotunatley, feeding problem unsolved quitely.

However, the development of dairy cattle also be confined by its microclimate condition. Recently, the growing of dairy farming rapidly occurs in Java Island. It was counted that 90% of the dairy farming was located in Java

2 Island, where the microclimate condition was the best situated for dairy cattle; temperature 27-28 0C and RH 70-80%. East Java, Central Java and West Java were the location for the development of the dairy cattle (Director General Of Livestock And Animal Health 2011). Unfortunately, those areas were the most populated province in Indonesia, where also the fastest growing economic, industrial, and business.

In the future, the development of dairy farming will force serious problem. Limitation of farming area, and forage scarcity are the major problems in Java Island. Forage scarcity highly related with the land availability. Therefore, sustainability of dairy farming is needed to be considering. Forage is the main feed for the dairy cattle. Access to fresh, high quality pasture seems to be the most significant variable in the nutrition equation, regardless of organic or conventional production systems. It requires for maintenancing and growing for the dairy cattle. Forages are unique compared with other dietary ingredients. In fact, it provide long fibrous particles that are retained in the rumen longer and tend to ferment more slowly than smaller feed particles. It provides a consistent source of fuels to microbes in the rumen as well as a basal supply of fuels to the liver and mammary gland over time, allowing greater milk yield.

Now days, forage is limit, because of poor growing conditions and insufficient land base on individual farms that effected on milk production. Zemmling (2002) stated that whilst demand for livestock products is expanding, the total area of naturally occurring forages is declining as the more favorable areas are converted into arable land, leaving only the poorest land for grazing or gathering of feed for animals.

Todays, farmers conduct endeavor varied ways in filling forage demand for the dairy cattle. They are attempting for meeting its requirement by planting forage, purchasing forage or finding in the open area, Ect. Moreover, now a days the government and the farmers are collaborating to solve this problems. Planting forage is the most movement suggested for filling forage demand. Forage cultivation is conducting in any area that could be used for planting forage.

In some province, such as West Java, dairy farming found close to the forest area. Therefore, farmers are using the area as the effort for filling forage

3

demand. Moreover, this system is well known as the Agroforestry system. Agroforestry system has a huge potency in supporting forage demand in West Java. Agroforestry defined as a farming system that integrates crops or livestock with trees and shrubs. This system is an effort as sustainability forage production for small scale dairy farming.

Susitainability of small scale dairy farming needs to be concerned, since it is the backbone of National milk production. It could be assessed into theree principal aspects; ecology, economy and social aspect. Agroforstry system may become the way in sustaining small scale dairy farming. Attemped on ecologycal aspect, it is very important for maintaning the soil organic matter to increase soil resistance to prevent erosion risk (Young 1989). However, the utilization of Agroforestry system is facing some problems, regarding the ecological interaction both the forest and forage that may occuring and influence forage production. It might be the most resticted factors due to the forage productivity. Many dairy farming opperessed with this situaion. An appropriate management on Agroforestry system is highly required in enhancing forage production. Also, the limitation information of economic and sosial aspect due to the utilization of this system. Pointed on economic aspect, forage production might support househould profit inderictly, but this information is also bounding. The social aspect, regarding the beneficial relationship that might rising both the farmers and goverenment still not well definied. Based on the description of those problems, this research is conducted. However, the information of potency that might be occuring was not clearly understood, therefore the broad objection of this researchis to explore the potency of Agroforestry system due to sustainability of small scale dairy farming.

4 CHAPTER II.

Agroforestry system supported Sustainability of Dairy Farming; Case study, Agroforestry system in Lembang district Area, West Java, Indonesia

2.1 Introduction

Agroforestry is very important in particularly dairy farming practices. It roles in providing forage, which collaborated with forest plantation. In many parts of the world, this system has been recommended as a technique to ensure sustainability in animal production systems (Paciullo et al.2010). In dairy farming practices, Agroforestry viewed on ecological aspect, carried some benefits including to its environment and livestock sectors. Furthermore, others values together with biodiversity conservation (Pagiola et al. 2004), atmospheric carbon sequestration (Andrade et al., 2008; Soto-Pinto et al. 2010) and the mitigation of greenhouse effect gases (Kaur et al. 2002; Schoeneberger 2009), increased soil fertility and conservation (Power et al. 2003).

Agroforestry technologies enhance ultimate the quality of life for people (Young 1989). Highlighted among the benefits of the utilization of such system depends on the balance among pasture, trees and animal, as competition for growth and production resources, such as radiation, water and nutrients can render the system's sustainability unfeasible (Pacuillo et al. 2011). Smallholder farmers have traditionally used naturally occurring grasses, legumes, herbs, shrubs and tree foliage as the primary feeds for ruminants. Apart from some labor inputs, these feed resources were available at no cost and had little or no commercial value.

Additionally, the majority of dairy farming system was smallholder, where located mainly in Java Island, on the highland area, more than 700 meters above sea level, which the environment was better suited for dairy farming development.

Recently, dairy farmers were planting forage in the forest as their effort to fill their forage. This method was known briefly as Agroforestry system. The objection of this research is to explore the potency of Agroforestry system, with the study case in Lembang West Java. Therefore we also gain the fresh yield and nutrients quality in Agroforestry system.

6

1x1

Sampling Plot

1 2 3 4 5

by using lux meter and fresh weight production was measured by using electrical balance. The data beneath the tree directly also obtained. The sample quadrats used of 1 x 1 m2 on each site with the distance 1m, 2m, 3m, 4m, 4m, and 5m respectively. Also, the measurement of lux intensity and fresh weight production were conducted (Figure 2).

Figure 2. Sampling plot on agroforestry system in Lembang, West Java

2.3.1 The calculation of carrying capacity on Agroforestry system

Carrying capacity was defined as the capacity of an ecosystem, which could maintain its productivity, adaptability, and capability of renewal (IUCN/UNEP/WWF 1991). In this study, the number of livestock that land resources in the study area could support has been considered as the carrying capacity, which was determined using following equation.

∑

where C was the livestock carrying capacity of land resources; TDNA was Total digestive nutrient (TDN) available; TDND, the TDN demand per livestock standard unit (LSU). TDN was a standard indicator of crude protein, crude fiber, nitrogen-free extract, calcium and phosphorous content in forage, fodder and concentrate (Banerjee 1988). Since livestock were fed with grass, fodder, crop residue and grain, with varying nutrient contents, conversion of all these materials into TDN was essential to determine the carrying capacity (Tahpa 1999).

7

2.3.2 The analytical framework on economic calculation

The analytical framework on economic calculation was designed to obtain the data regarding economic aspect of dairy farming system in Lembang. The interview method was conducted in order to get any further information with the respondent (dairy farmers). The determination of respondents were counted by the proportion estimation by using this equation (Rae 1994) :

n=

̂ ̂ n = sample

̂ = estimated value for p ̂ = (1- estimated value for p)

e = error

= normal distribution

The calculation of economic aspect on small-scale dairy farming was conducted. It was given the variable farm inputs as Xi and fixed farm input K are

used in agroforestry farm to produce output Yj. The relationship both he quantities

of input employed and quantities of output produced could be expressed as :

Y

j

= f (Xi, K)

or explicity as :

Y

j

= f (X

i

, X

2

, ….X

n

, K) ………(X)

∑

∑

………..

(X)

8

Dairy farmers without land for

forage 22%

Dairy farmers rent the land for

forage 18% Dairy farmers

planting forage in forest

36%

Dairy farmers has their own land for

forage 24%

2.4 Results and Discussion

The benefit of using Agroforestry also, could be seen in the economical aspect. We obtained some data in small-scale dairy farming in Gunung Putri Villages, Lembang area, West Java. A deeply interview and discussion obtained regarding the benefit aspect on Agroforestry system. As 78 of farmers have been involved in turn to obtain further information of Agroforestry system. We observed, that more than 36% of dairy farmers attempted the forage by utilizing forest area.

The dairy farmers, under any condition who were utilizing forest area for foraging might acquired with many benefits, either ecological or economic. It could explain easily; they were using the land that available for planting forage, further it supported for forage production for the dairy cattle. The land that available in forest was providing by renting to household. However, we also gained that the price for renting was inexpensive. Farmers issued approximately 245.000 IDR per Ha per yr. This amount was lower compared than they have to purchase forage. We averaged that household were belonging the land for 5.513,15 m2 in the forest. In figure 3 described clearly the spreading information regarding farmers condition due to filling forage demand.

Figure 3. The outspreading of household condition due to forage provision in Lembang, West Java

The social aspect was highly significance to be assessed, since the Agroforestry system was well known in the community. However, the system

9

guided to the good impact on sustainability of dairy farming. We observed that there was a cooperative relationship both the farmers and the government. However, since the government officially regulated the household for planting forage in 2005, harmonized relation occurred on both side. Household had their awareness for keeping the forest, as the area for planting forage and for the natural conservation. Since the regulation was issued, some hazards were decreasing dramatically. For example, the fire accident was lower, the wood criminal harassment also depleted. However, co-management, activity that involving community has been proved successfully in maintaining the forest.

In Indonesia forest management is recognized by State Owned Forestry Enterprise (Perum Perhutani). Perum Perhutani has been established since 1961. The primary job is managing forest resources in Java and Madura Island. Their strategic programs are supporting balancing economic, Forest Eco-community system that had collaboration either Perhutani and Forest community or others

stakeholder. Forest area in Lembang is managed by ―Badan Kesatuan Pemangkuan Hutan Lembang‖ (BKPH). Forest has potency as the income‘s

source of community; planting forage, water resources, etc.

Furthermore, some problems facing by the household due to in utilizing forest area for foraging were also gained. The information were collected from deeply discussion, with the dairy farmers in Lembang. The farmers were facing low productivity of forage that planted beneath the tree.

The information completed by obtaining some data in Agroforestry system. It assumed that forage yield affected by the low levels of irradiance that accepted understorey. Further its quality (nutrients content) also needed to be concerned. Further, we designed several plots that showed significance forage production in each plot respectively. Table 1 described the measurement of forage yield beneath the tree (Table 1).

10 Table 1. Measurement of forage yield on varied plot designed (low, middle and

high density).

No Plot designed in Agroforestry system

Forage Yield (Mg/ha)

Levels of shade (%)

1 Low density plot 21.017.07 12

2 Middle density plot 15.382.21 57

3 High density plot 7.091.71 78

Table 1 described the variety of forage yield in different plot design in Agroforestry system. The highest forage yield was gained in low-density forage (21.01 Mg/ha), since it has the lowest levels of shade (12%). Middle density (57%) showed forage yield for 15.38 Mg/ha. Further, high density showed the lowest forage yield (7.09 Mg/ha) with the levels of shade for 78%. Further, in this plot farmers do some forest management, where they were doing some thinning tree. This reason also connected with the higher yield of forage produced.

Furthermore, we were trying to gain more deeply information regarding forage production that effected by the distance from tree. As we also know, that the different distance from tree might influence yield production. It assumed, that as the longer distance from tree, some significance different of forage production might occurs. The information of forage production beneath the tree was provided in Table 2.

Table 2. Biomass Production (kg/m2) obtained with the different distance (1 m to 5 meter) from the tree

No Distance (m) Forage Yield (kg/m2) Levels of Shade (%)

1 1 0.6 31.29

2 2 0.6 28.62

3 3 0.8 26.90

4 4 1.2 10.05

5 5 1.5 0

Table 2 showed the different result on forage yield underneath tree with the different distance. Based on table above it could be seen that as the longer distance from the tree, the more forage was resulted. The data described that underneath the tree (1-2 meter), showed the least forage yield (0.6 kg/m2), whereas in 5 meters showed 1.5 kg/m2. The data described that as the decreasing of levels of shade, forage yield dramatically increased. Based on this information, it proofed that the irradiance level accepted by plants was connected highly with forage yield. This information might be useful in understanding how shading

11

affected forage yield. The relationship was also occurring on forage yield, levels of shade and the distance, in Agroforestry system. In general speaking, it could be inferred that as the higher number of shading ratio, it showed the less number of production. Figure 4 also described the correlation both forage yield and the distance measured (R2). It could be inferred that R2 number was 0.91. On the other hand, it could be stated that as 91% of forage yield measured was affected by distance, and the rest influenced by others factors.

However, it also observed the quality of forage yield in Agroforestry system. We intended deeply information about the quality of forage yield in different density type. The information regarding the quality of forage could be seen in Table 3.

Table 3. The measurement of forage quality in Agroforestry System, in three different plots (low, middle and high density plot).

Table 3 described the measurement on forage quality in different type plot observation. The higher density plot showed higher nutrients compound specially in DM, fiber, protein and fat. It described that underneath canopy, the quality of forage was increasing. In middle density (78%) of levels of shade, showed the higher nutrient compound compared with low (12%) and high-density plots (54%). Moreover, the quality on grass also explained by Ludwig et al. (2004), who stated that in older trees tend to be more widely spaced than the smaller ones. These trees in medium density show an optimal effect on herbaceous layer productivity compared to more densely, where grasses have been inferior competitors for resources as a light, water and nutrients. Anna et al. (2007) more over also explained that in sub canopy of tree reflect a high Nitrogen and Phosphor value, as the facilitative effect of trees prevails.

CHAPTER III. No Plot designed in

Agroforestry system

Moisture content (%)

Ash content (%)

Protein content (%)

Fat content (%)

Fiber content (%) 1. Low density plot 8.36 14.02 10.01 1.32 27.8 2. Middle density

plot

9.55 12.51 11.88 1.62 28.08

12 An Experimental Treatment, A learnt from Actual Condition; The effect of

shading and organic fertilizer on forage production 3.1 Introduction

Agroforestry system was known briefly as an effort for providing forage, elaborated with forest plantation. However, agroforestry system was complicated because it involved many factors, such as solar radiation, tree growth, density, sloping, rainfall etc. Those factors were quite hard to understand in estimating forage production. Simplification of those factors was required in estimating forage availability in forest. In order we could understand the potency of agroforestry as the source of forage plantation. Therefore, the research was conducted, several factors were involved to understanding the Agroforestry system related to the small-scale dairy farming in Indonesia. A learn from actual condition was introduced in field experiment research. The using of P. purpureum

as the most used forage variety used by farmers, whereas discover the potency of

S. splendida as the other variety for animal feed also conducted. S. splendida has been known as the one of forage that used as a feed for animal. Wilson and Minson (1980) also proofed that the leaf of plant has a more the organic matter digestible than the steam. S. splendida, consist more leaves than the steam. Further, we would like also gained about the endurance of S. splendida

underneath the levels of shade.

Level of irradiance (shading) was used as the first factor assumed might affect forage production. It became the primary limiting factor because levels of shade would curb growth in biomass accumulation. Organic fertilizer was used as the secondary factor. Using organic fertilizer was very important for sustainability dairy farming. Since the organic fertilizer has been known widely as the factor that might increase SOM (Soil Organic Matter). SOM was also known as the indicator for soil health. Defoliation management also affected forage production substantially. Defoliation, whether by hand or by animals reduced leaf area and induced a carbon shortage in plants through reduction in light interception. The objection of this research is to gain the information about the forage yield due to shading affect and its quality.

14

0 100 200 300 400 500 600 700 800 900

40d

Initial harvest time (adding organic fertilizer)

Therefore, we measured the solar intensity intended for determining levels of shade. The data was acquired for 8 hours (9 AM- 4.00 PM) by using solar meter. Figure 5 described clearly the measurement of solar radiation in Field Experiment Research.

Figure 5. The trend of solar irradiance on different of the level of shades. 0% levels of shade, 60% levels of shade, 80%

level of shades.

It could be seen from figure above that the different on levels of shade affected the solar radiance acceptation by plant. It indicated that the highest number of solar radiance was 780 w/m2, 298 w/m2, 110 w/m2 for each shading level; 0%, 60%, 80%. The lowest number of solar radiance was 443 w/m2, 108 298 w/m2 and 42 w/m2 with the average was 572.80 w/m2, 218.9 w/m2 and 57.64 w/m2 for each shading level. Since defoliation management had been influenced forage production, hence it was emphasized on this research. Defoliation management was implied in this research, including 40, 50, 60 days after plantation (Figure 6).

Figure 6. Defoliation management introduced in this research.

40 50 60

First harvest time

Secondary harvest time

Third harvest time

15 0 10 20 30 40 50

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61

R a in fa ll ( m m )

61 Days observation (May-June 2012) 22 23 24 25 26 27 28

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61

T e m p e r a tu r e ( 0C)

61 Days observation (May-June 2012) 70 75 80 85 90 95 100

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61

Hu m id it y ( % )

61 Days observation (May-June 2012)

0 100 200 300 400

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61

S o la r R a d ia n c e ( c a l/ m 2)

61 Days observation (May-June 2012)

An experimental field treatment showed three different levels of irradiance (shading) for forage crop. At the beginning information several data was obtained related to microclimate condition among the research field. 61 days data observation was gained. The data showed the highest temperature was 27.1 oC, and the lowest was 23.4 oC, with the average was 26.18 oC. The highest humidity was 95% and the lowest was 73% with the average of humidity was 83.06%. The measurement of rainfall showed, the highest rainfall was 44.1 mm and the lowest was 0.5 mm with the average was 11.89 mm. The solar irradiance measurement showed the highest number was 378 cal/m2 and the lowest number was 296.68 cal/m2. Figure 7 described clearly the information of microclimate condition, data source from Indonesia Meteorology and Geophysics Agency.

Figure 7. Showed the microclimate condition among the research field at Field Work Center, Faculty of Animal Science, Bogor Agriculture University, (a) Temperature, (b) humidity, (c) rainfall, (d) solar irradiance.

3.3. Soil and Fertilizer Analysis Measurement

Soil and fertilizer analysis was measured in BALITRO, Bogor. The following method of measurement could be seen on Table 4.

16 Table 4. The analyses of Fertilizer and Soil Sample

No Parameter Method

Fertilizer

1 pH pH meter

2 N (%) Kjeldahl

3 P (%) Spectrophotometer

4 K (%) AAS

5 C-Organic (%) Spectrophotometer Soil

1 pH pH-metri

2 C-Organic (%) Walkey & Black

3 N-Total (%) Kjeldahl

4 P (ppm) Bray l

5 K Percolation with NH4C2H3O2 1M

In this research the utilization of organic fertilizer (manure from cattle) was used. The information regarding component of organic fertilizer used soil quality analysis provided in Table 5 and 6.

Table 5. The Information of Component of Organic Fertilizer Analysis measured in Field Center Experimental Research Faculty of Animal Science, Bogor Agriculture University.

Compound Amount

N (%) 2.17

P (%) 0.36

K (%) 0.28

Organic Carbon (%) 31.88

pH 6.5

Table 6. The Information of Soil Quality measured in Field Center Experimental Research Faculty of Animal Science, Bogor Agriculture University Levels of

shades pH

Organic carbon

N-Total

(%) C/N Ratio P K

60% 5.14 2.06 0.22 9.36 6.88 0.11

80% 4.74 2.5 0.28 8.93 8.28 0.15

3.4 Sampling Procedure and Data Collection 3.4.1 Plant Production

On the day after plantation determined, the plant harvested and weight by using electrical balance. P. purpureum was chopped and reminded 10 cm from

17

ground whereas S. Splendida was cutting and reminding 5 cm from ground. Remove sample from any roots from plants and brush off dirt particles. Fresh weight was measured and dried in 65 OC for 48 hours and weighted again. Plant biomass was converted into Mg/ha in dry weight basis. Leaves were grinded partially dried sample into fitness desired for analyses.

3.4.2 Forage layer height and leaf area

The measurement of forage layer height (cm) was done by measuring from the soil surface to the highest point of the arch of the uppermost leaf. We were using stick ruler with the maximum length was 3m. We also focused on measurement on leaf area (mm2). It measured by using leaf area meter. Both forage layer height and leaf area were completed in 60 days after plantation.

3.4.3 The measurement of Chlorophylls Content.

The following analysis was performed on chlorophylls content, including chlorophyll a and chlorophyll b. Small sward was cut and used as a sample; the third and forth leaves from the bottom of the ground. Fresh leaf was breaking into simpler form and measured for 1 gram. It was destructed and dissolved by using 80% acetone for 2 ml. Sample was centrifuged and diluted for 5 ml. Sample of chlorophyll were observed by using spectrophotometer (UV-Vis) on the wave length 663 and 645 nm. The calculation of total chlorophyll (the a and b chlorophyll) was counted by using equation (Yoshida 1981):

a chlorophyll = (0,0127 x D663–0,00269 x D645) fp

b chlorophyll = (20,2 x D645 + 8,02 x D663) fp

fp = dilatation factor = d/e x b/c x 1/a x 1.000 Information

A = weight of sample B = initial extract volume

C = the extract volume obtained from the initial extraction D = extract volume after destructed

E = conversion from litter to millimeter 1.000 = conversion from gram to milligram

18 D663 = spectrophotometer on 633 nm wave length

D645 = spectrophotometer on 645 nm wave length

3.4.4 The analyses of forage quality

Since the feed was not only focused on the quantities rather its quality. Moreover the main process of growth from forage was obtained form photosynthesis process. However, the product of photosynthesis would be transferred into the organ for the growth and maintenance. The product of photosynthesis was the dry matter production and others nutrients compound. Hence, the nutrients content analyses were measured on moisture analysis, dry matter production, ash analysis, fat content fiber content and protein content respectively.

3.4.4.1 Dry Matter Analysis

Dry matter analysis was measured based on AOAC method (Association of Official Analytic Chemist). The Total Dry Matter by Oven Drying at 105oC for 16 hr. The principle mechanism was emphasized on the heat treatment (1050 C). Water would evaporated by heat treatment, remaining the rest material (dry matter) that would be weighted formerly. Total dry matter is determined

gravimetrically as residue remaining after drying. Weighing made on hot sample or after cooling in desiccator. The calculation of moisture content (%) could be seen on equation:

Where

W1 = dry weight of sample and container (with cover) in grams

W2 = tare weight of container (with cover) in grams

W3= dry weight of sample in grams

Percent Total Moisture was calculated as:

19

3.4.4.2 Ash Analysis

Ash of Animal Feed. (942.05) Official methods of Analysis. 1990. Association of Official Analytical Chemists, 15th Edition. Ashing is the process of mineralization for preconcentration of trace substances prior to chemical analysis. The ash content is an approximate measure of the mineral content and other inorganic. Remove crucibles with cover which have been dried for at least 2 hr at 100 0C from oven, to 
desiccator. Cool, and record weight of crucibles with cover to the nearest 0.1 mg (W1). Weigh 1.5 to 2.0 g of sample into the crucible, recording weight of crucible with cover and 
_{sample to the nearest 0.1 mg (W2).} Ash in furnace at 600 oC for 2 hr after the furnace reaches temperature. Allow crucibles to cool in furnace to less than 200 oC and place crucibles with cover in 
desiccator with vented top. Cool and weigh crucible with cover and ash to the nearest 0.1 mg (W3).

3.4.4.3 Fat Analysis

Fat analysis was conducted based on AOAC method. It emphasized on the fat extraction measurement. Sample was weight the ground dry sample into the extraction thimble. The extraction thimble was closed with fat free cotton wad, and inserted into the Soxhlet extractor. Fill the solvent into the solvent vessel, and extracted at a temperature of 50 OC for 16 hours. The solvent drained into a suitable container by opening the spigot on the Soxhlet extractor. The solvent vessel was continued for heating until all the solvent has been evaporated and condensed in the Soxhlet extractor. Vessel contained fat residue was placed in a drying oven (105 OC) and heat to constant weight (indicating evaporation of all solvent). The vessel containing the fat was allowed to cool to room temperature (about 30 minutes).

Compute the fat content according to the following formula

20 Where

m1 = weight the dry empty vessel (gram)

m2 = weight of the vessel containing fat residue after evaporation of the solvent

(gram)

E = the sample weight (gram)

3.4.4.4 Protein Analysis

Protein (Crude) Determination in Animal Feed: Copper Catalyst Kjeldahl Method. (984.13). Official Methods of Analysis. 1990. Association of Official Analytical Chemists. The Kjeldahl method is the standard method of nitrogen determination dating back to its development in the late 1800's. The method consists of three basic steps: 1) digestion of the sample in sulfuric acid with a catalyst, which results in conversion of nitrogen to ammonia; 2) distillation of the ammonia into a trapping solution; and 3) quantification of the ammonia by titration with a standard solution.

Digestion

Weigh approximately 1g ground sample into digestion flask, recording weight (W)to nearest 0.1 mg. Include reagent blank and high purity lysine HCl as check of correctness of digestion parameters. Weigh a second subsample for laboratory dry matter determination. Add 15 g potassium sulfate, 0.04 g anhydrous copper sulfate, 0.5 to1.0 galundum granules. Place flask on pre heated burner (adjusted to bring 250mL water at25oC to rolling boilin 5 min). Heat until white fumes clear bulb of flask, swirl gently, and continue heating for 90 minfor copper catalyst or 40 min for CuSO4/TiO2 mixed catalyst. Cool, cautiously add 250 mL distilled water and cool to room temperature (<25oC). Note: If bumping occurs during distillation, volume of water may be increased to ca. 275 mL.

Distillation:

Prepare titration flask by adding appropriate volume (VHCl) accurately measured acid standard solution to amount of water so that condenser tip is immersed (try 15 mL acid and 70 mL water if undecided). For reagent blank, pipet 1 mL of acid and add approximately 85 mL water. Add 3 to 4 drops methyl red indicator

21 solution. Add 2 to 3 drops of tributyl citrate or other anti foam agent to digestion flask to reduce foaming. Add another 0.5 to1.0 galundum granules. Slowly down side of flask, add sufficient 45% sodium hydroxide solution (approximately80 
mL) to make mixture strongly alkali. (Do not mix until after flask is connected to distillation 
apparatus or ammonia will be lost.) Immediately connect flask to distillation apparatus and distill at about 7.5 boil rate 
(temperature set to bring 250 ml at 25 oC to boil in 7.5 min), until at least 150 ml, distillate was collected in titrating flask. Remove digestion flask and titrating flask from unit, rinsing the condenser tube with distilled 
water as the flask is being removed.

Titration

Titrate excess acid with standard sodium hydroxide solution to orange endpoint (color change from red to orange to yellow) and record volume to nearest 0.01 mL (VNaOH). Titrate the reagent blank (B) similarly.

The calculation of N (%) :

[ ]

VNaOH = mL standard NaOH needed to titrate sample

VHCl = mL standard HCl pipetted into titrating flask for sample

VNaOH = Normality of NaOH


VHCl = Normality of HCl

VBK = mL standard NaOH needed to titrate 1 mL standard HCl minus B

B = mL standard NaOH needed to titrate reagent blank carried through method and distilled into 1 mL standard HCl 1.4007 = milliequivalent weight of nitrogen x 100

W = sample weight in grams

Percent Crude Protein (CP)

CP (DM basis)= % N (DM basis) X F Where F = 6.25 for all forages and feeds except wheat grains

22 3.4.4.5 Fiber Analysis

Fiber analysis was conducted based on AOAC method. The understanding principle of this calculation was the organic material that not soluble in liquid concentrated acid and concentrated base heating for 30 minutes. The rest material remaining was fiber. It would be burn into 600 OC, and stated as the fiber content (%).

% Fiber

Where :

x = sample weighed

a = the weight of paper filter

y = sample weight of the cup after heated on liquid concentrated acid and Concentrated base.

Z = sample after heated on 600 OC

3.4.5 Statistical Analysis

Plant production and nutrient analyses data were tested for significant differences using randomize block complete ANOVA. Least significance difference (LSD) post hoc tests were conducted to compare means between treatments. Data were analyzed by using StatView, SAS Institute Inc.

Hypothesis

1. The Hypothesis of treatment factors due to levels of shade H0 = ̅̅̅̅= ̅̅̅̅= ̅̅̅̅

H1 = At least there was a level shade treatment resulting in the effect 2. The Hypothesis of treatment factors due to organic fertilizers

H0 = ̅̅̅̅= ̅̅̅̅= ̅̅̅̅

H1 = At least there was an organic fertilizers treatment has an effect 3. The Hypothesis of treatment factors due to Blocking‘s components

(defoliation management) H0 = ̅̅̅̅= ̅̅̅̅̅̅̅ ̅̅̅̅ H1 = ̅̅̅̅≠ ̅̅̅̅≠ ̅̅̅̅

23 121 10 122 11 123 12

111 1 112 2 113 3

131 19 132 20 133 21

311 28 312 29 313 30 321 37 322 38 323 39 331 46 332 47 333 48

221 64 222 65 223 66 211 55 212 56 213 57

231 73 232 74 233 75

121 13 122 14 123 15 111 4 112 5 113 6

131 22 132 23 133 24

121 16 122 17 123 18 111 7 112 8 113 9

131 25 132 26 133 27

311 31 312 32 313 33 321 40 322 41 323 42 331 49 332 50 333 51

311 34 312 35 313 36 321 37 322 41 323 42 331 52 332 53 333 54

221 67 222 68 223 69 211 58 212 59 213 60

231 76 232 77 233 78

221 70 222 71 223 72 211 61 212 62 213 63

231 79 232 80 233 81

H0 = ABijl = 0

H1 = ABijk 0

Yijk = µ + KK + Ai + Bj + ABij+εij

Yijk = Forage production (Pennisetum purpureum and Setaria Splendida )

Influenced by shading level (i) and organic fertilizer (j) µ = Mean Square

KK = Influence of blocking, ie: -k

Ai = Influence of solar radiation ie: -i

Bl = Influence of fertilization ie-l

ABil = Interaction of solar radiation and fertilization

Design : Randomize block complete plot with there replications, Unit plot 3m (Totally 27 plots).

Shading Level. 1) 0%, 2) 60%, 3) 80%, Fertilizer. 1) 30 Mg ha-1, 2) 20 Mg ha-1, 3) 10 Mg ha-1, Defoliation: 40d , 50d , 60d Replication : 1,2,3

24 3.4 Result And Discussion

3.4.1 Plant Responses due to the level of irradiance, organic fertilizer and Defoliation Management

Several treatments on Field Experimental research were design and the data regarding forage production was gained. Moreover, the levels of shade were assumed might influence strongly on forage yield. Levels of shade were connected directly with light availability. Light is electromagnetic radiation of

wavelengths to which the human eye is sensitive(λ ≈ 400 to 700 nm). However, sometimes the word light is also used to refer to other nearby regions of thespectrum: ultraviolet (shorter wavelengths than visible light) and infra-red (longer wavelengths). Light is both a source of energy and a source of information for green plants. It is a sourceof energy for photosynthesis, and a source of information for photoperiodism (night/day length), phototropism (light direction), and photomorphogenesis (light quantity and quality) (Aphlaho 2006). Trees in some ecosystems, for example in forest, savanna, ect have been referred to as

‗islands of fertility‘ (Belsky et al. 1989), because elevated soil nutrients are found beneath their crowns, together with decreased solar radiation, reduced evapotranspiration and reduced soil temperatures (Ludwig et al. 2004).

The use of organic fertilizer such as manure might be useful to increase SOM. Thelen et al. (2010) observed the manure effected to soil organic matter by using corn Stover. Based on the research, they were obtained that adding manure or compost were effective ways to build SOM even with complete removal of corn Stover. Therefore manure (the organic fertilizer) was used on this research.

The availability of light might influence nutrient intake by plant. Light quality (and irradiance) incident on shoots could affect the growth of roots by indirectly affecting the photosynthetic availability in roots, either because of changes in allocation or changes in assimilation. In turn changes in the root growth, morphology and symbioses could affect the ability of plants to take up nutrients form the soil. Moreover, light quality can affect the enzymes involved in nitrogen metabolism. At the biochemical level light dependent light induction and modulation of enzyme activity has been studied in some detail. On the other hand,

25

effects of light quality on whole plant mineral nutrient uptake and status have been little studied (Aphlaho 2006).

In actual condition forage plantation was forced by the limitation of sun availability that could be influence forage production. This condition occurred as the impact of competition both the trees and its plant. In general, plants have two main strategies in response to light competition: overgrow and shade the competitors and/or tolerate shade by maximizing growth under reduced light (Humphreys 1981). The former was obviously not a viable strategy for pasture plants growing in association with trees. However, tropical grasses were differing in their tolerance of shade. Several data were gained as its responses regarding to different levels of solar radiance, the utilization of organic fertilizer and defoliation management. The information consists of variations including forage yield, plant architecture (plant layer height), and leaf area also chlorophyll concentration. In the early respond was provided the measurement on forage yield production on P. purpureum.

Table 7. The Measurement forage yield (Mg/ha) P. Purpurem on different levels of shade, organic fertilizer and defoliation management treatments. Levels

of shade

Organic Fertilizer (Mg/ha)

Defoliation management

40d 50d 60d

0% 30 47.8±4.9 35.6±18.5 28.7±4.4

20 26.8±5.9 29.0±10.0 19.2±3.2

10 25.0±7.3 27.9±3.8 29.5±11.1

60% 30 35.7±5.6 35.4±0.8 23.1±5.7

20 21.7±2.0 26.4±5.9 25.9±4.2

10 21.4±1.4 22.9±1.8 15.1±4.8

80% 30 18.9±6.3 23.9±4.1 14.3±2.8

20 13.5±2.8 14.6±5.5 16.8±5.1

10 8.1±2.8 14.3±2.7 11.8±7.4

Table 7 showed the measurement on forage yield P. purpureum on different treatments. The data illustrated that levels of shade, organic fertilizer and defoliation management were persuaded on forage yield on P. purpureum. The study showed that yield production depressed as the less number of irradiance accepted by plants. At the same time, the utilization of higher amount of organic fertilizer enlarged yield production compared with less organic fertilizer. It was observed underneath shading condition, the forage yield was reducing, but it could be enhance by adding the organic fertilizer. Underneath shading condition

26

0 5 10 15 20 25 30 35

0 60 80

M

g

/ha

(%)

a

a

b

such as 60% and 80%, the forage yield required higher organic fertilizer. In 40 and 50 days of plantation, the additional 30 Mg/ha organic fertilizer presences the highest forage yield underneath limitation of sun availability. While, in the longer time or harvest time, it required less organic fertilizer to obtain maximum yield. In 60 days after plantation, the organic fertilizer was required for 20 Mg/ha. We calculated that as 31.1 % of forage production was depleting, since it planted on 80% Levels of shade (Figure 9).

Figure 9. The main effect levels of shade on forage yield P. purpureum.

Subscripts with the same letter showed the significant different test by Least Square Determination (LSD) in P<0.05.

Moreover, the Analysis of Variance (ANOVA) result showed there was significance different on the Levels of shade (P<0.05). From figure 9, it could be seen that forage yield showed significant differences on levels of shade. The result indicated that the less number of forage yield was produced in higher levels of shade. It gained that the highest amount was obtained on 0% levels of shade as 30.50 Mg/ha. Furthermore, we also obtained the interaction both the organic fertilizer and defoliation management due to forage yield (Figure 10).

27 0

5 10 15 20 25 30 35 40

40d 50d 60d 40d 50d 60d 40d 50d 60d

10 Mg/ha 20 Mg/ha 30 Mg/ha

M

g

/ha

Figure 10. The interaction both fertilization and defoliation management on forage yield P.purpureum.

In figure 10, the interaction occurred as the impact of additional organic fertilization and defoliation management on forage yield. Furthermore, it could be understood that the additional fertilizer, compacted with defoliation management. As in the early growing stage on the plant that required additional fertilizer to support plant growth. In the longer time of defoliation management, the amount of fertilizer needed slowly decreasing. We also observed the influenced of treatments on S. splendida. In table 8 was showing the forage yield S. splendida

influenced by levels of shade, organic fertilizer and defoliation management. Table 8. The Measurement fresh weight production (Mg/ha) of S. splendida on

levels of shade, organic fertilizer and defoliation management treatments Levels

of shade

Organic Fertilizer (Mg/ha)

Defoliation management

40d 50d 60d

0% 30 27.2±0.7 26.1±1.7 18.8±3.4

20 20.3±0.8 31.3±0.7 23.5±5.3

10 21.2±2.5 15.2±0.7 17.5±1.9

60% 30 20.5±5.6 27.5±1.1 20.2±0.8

20 23.3±5.8 28.7±5.0 15.5±6.0

10 21.3±5.3 28.7±2.7 13.7±4.0

80% 30 18.6±2.9 22.2±1.0 12.5±2.6

20 18.1±2.1 11.5±4.4 18.3±3.2

10 16.6±1.9 25.2±4.0 14.4±2.2

Table 8 described the forage yield measurement of S. splendida. It could be seen from table 8 that the average of highest forage yield production was 24.73 Mg/ha. It was found in 50 days after plantation. Unlike P. purpureum where

28

0 5 10 15 20 25 30

40 50 60

M

g

/ha

days

5 10 15 20 25 30 35

M

g

/ha

shading highly influenced to forage yield. In S. splendida, within the longer time of defoliation management, it required less organic fertilizer. It could be seen in Table 8 that the optimum forage yield for 0% levels of shade in 40 days after plantation for 30 Mg/ha, and with the longer time of defoliation management (50 and 60 days after plantation), the requirement of organic fertilizer was reducing for 20 Mg/ha. The result quite different with the influence of the limitation of sun availability, whereas in 60% levels of shade showed the higher organic fertilizer requirement for 20 Mg/ha for 40 and 50 days after plantation. The organic fertilizer was required higher for 30 Mg/ha for the longer time defoliation management (60 days after plantation). In this study, defoliation management has a significance effect due to forage yield (Figure 11).

Figure 11. The main effect defoliation management on forage yield (Mg/ha) S. splendida. Subscripts with the same letter showed the significant different test by Least Square Determination (LSD) in P<0.05.

Figure 11 described the influence of defoliation management due to fresh weight of S. splendida. It could be seen that the different time of days after plantation has lead the different amount of fresh weight production. In this study, there was significance different on 60 days defoliation management (p<0.05). It also found that S. splendida did not show the direct effect regarding to shading effect. However, the influenced of levels of shade has seen as the interaction with the additional organic fertilizer (Figure 12).

a a

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CURRICULUM VITAE

Windi Al Zahra was born in Bogor, West Java on 14th February 1989. She is the first daughter of Mr. Nana Mahdi and Mrs. Wiwi Mulyawati. She finished her elementary school in SD Al-Ghazali Bogor, the Junior high school finished in SMP 9 Bogor, and finished her Senior high school in SMU 9 Bogor. She accepted in Bogor Agricultural University in Faculty of Animal Science, Department of Animal Science and Technology Production in 2006 and officially she received her bachelor degree in 2010. In 2010 she pursued her master degree at Natural Resources and Environmental Management Program and finished in 2012. In 2011, she obtained scholarship from General Higher Education, Ministry of Education, Indonesia and continue master degree program in Animal Science and Technology program, Bogor Agriculture University (IPB). In 2012 she accepted in Double Degree Program both IPB and IU (Ibaraki University). She spent 1 year in Japan for doing research, regarding sustainability dairy farming practices.