UNIVERSITI PUTRA MALAYSIA

SPATIAL VARIABILITY OF SOIL FACTORS AFFECTING IRRIGATED LOWLAND RICE YIELD

MOHD NASIR WARRIS

FP 2002 38

SPATIAL VARIABILITY OF SOIL FACTORS AFFECTING IRRIGATED LOWLAND RICE YIELD

By

MOHD NASIR W ARRIS

Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulrillment of the Requirement for the Degree of Master of Agricultural Science

December 2002

ii

Dedicated to

My beloved mother, wife and children

1ll

Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirements for the degree of Master of Agricultural Science

SPATIAL VARIABILITY OF SOIL FACfORS AFFECTING IRRIGATED LOWLAND RICE YIELD

By

MOHD NASIR W ARRIS December 2002

Chairman: Anuar Abdul Rahim, Ph.D. Agriculture Faculty:

Spatial variability of soil chemical and physical properties, and its influence on leaf

nutrient content, and yield components were studied in a 0.95 ha rice field in Kuala

Selangor. A total of 120 soil samples at 1 5 cm depth and 120 samples of rice plant

were taken at harvesting stage based on grid point sampling of 10m x 10m.

The studies revealed that coefficients of variation for soil physical properties were in

the order of bulk density > soil moisture > clay content. Soil chemical properties

showed coefficients of variation in the order ofK > Mg >total-N > CN ratio> P> Ca

> total-S > total-C and Cu > Zn > Na > Mn > pH. The coefficients of variation for

leaf nutrient content were found to be in the sequence of Cu > Zn> P > K> Mg > N >

Na > Mn > Ca. The range for soil physical properties was found to be in the order of

bulk density (134 m) > soil moisture (100 m) > clay content (17 m), while the range

for soil chemical properties was in the sequence of Mg (21 8 m) > total-C (161m) >

pH (134 m) 2: total-S (134 m) 2: P (134 m) > Ca (120 m) > total-N (54 m) > CN ratio

(46 m) > Na (41 m) > Mn (35 m) > Cu (20 m) > Zn (15 m).

IV

Correlation analysis for soil physical properties with yield showed only soil moisture

had positive association with yield, while soil chemical properties with yield showed

soil total-N, total-C, CN ratio, K, Mn, and Na were significantly associated with yield.

There were negative associations between soil total-N with leaf N, soil Ca with leaf

Ca, and soil Mn with leaf Mn. Positive associations existed between yield with

nwnber of tillers m"2, nwnber of panicles m"2, nwnber of spikelets panicle"I, and yield

with percentage of filled spikelets. Soil total-N showed positive association with

nwnber of panicles m-2, nwnber of spikelets panicle"l and percentage of filled

spikelets. Principal component analysis showed the first three principal components

accounted for 59% of the total variance and were represented as the fertility status of

the soil, substitution cation between Na and K, and bulk density with clay content

relationship, respectively. Multiple linear regression analysis for soil properties

revealed the equation Yield = 517.78 + 69.13 soil total-No The equation for leaf

nutrient content at rice crop maturity stage was Yield = 524.17 - 256.64 leaf N +

102085.391eafCu + 2663.92IeafMn, and equation for yield components was Yield =

1.55 (nwnber of panicles m-2) + 10.20 (number of spikelets panicle-I) + 8.05

(percentage of filled spikelets) - 47.61 (seed weight).

Semivariograms and kriging were able to explain the soil and crop attributes

variability of the rice field. Kriged map of soil total-nitrogen had the same pattern as

kriged map of nwnber of panicles m-2. Geographic information system was able to

spatially locate, and calculate the area of a given variable range of values to help in

managing the rice field efficiently.

�'AI\AAN 8UlTAN Afl')VL SAMAD UNlYfftilTI NT¥ MALA YSlA

Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master Sains Pertanian

V ARIASI RUANG CIRI-CIRI T ANAH YANG MEMPENGARUm BASIL SAW AH P ADI BERPENGAIRAN

Oleh

MOHD NASIR W ARRIS Disember 2002

Pengerusi: Anuar Abdul Rahim, Ph.D. Fakulti: Pertanian

Variasi roang eiri-eiri kimia dan fizik tanah, dan kesannya ke atas kandungan nutrien

daun, dan komponen basil telah dikaji di sawah padi berkeluasan 0.95 ha yang

terletak: di Kuala Selangor. Sebanyak 120 sampel tanah pada kedalaman 15 em dan

sebanyak 120 sampel bahagian pokok padi telah diambil pada peringkat tuian padi

secara penyampelan grid pada jarak 10m x 10m.

Kajian ini menukilkan bahawa pekali variasi ciri fizik tanah mengikut turutan

ketumpatan pukal tanah > kelembapan tanah > kandungan lempung. Pekali variasi eiri

kimia tanah mengikut turutan K > Mg >jumlah-N > nisbah CN > P > Ca > jumlah-S

> jumlah-C dan Cu > Zn > Na > Mn > pH. Pekali variasi untuk kandungan nutrien

daun pula mengikut turutan eu > Zn > P > K > Mg > N > Na > Mn > Ca. Jarak

pergantungan ruang sampel untuk eiri fizik tanah didapati mengikut turutan

ketumpatan pukal tanah (134 m) > kelembapan tanah (l00 m) > kandungan lempung

(17 m). Jarak pergantungan ruang sampel untuk. eiri kimia tanah pula mengikut

turutan Mg (218 m) > jumlah-C (161m) > pH (134 m) � jumlah-S (134 m) � P (134

m) > Ca (120 m) > jumlah-N (54 m) > nisbah CN (46 m) > Na (41 m) > Mn (35 m) >

Cu (20 m) > Zn (15 m).

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Analisis korelasi eiri fizik tanah menunjukkan perkaitan terus di antara basil dengan

kelembapan tanah. Ciri kimia tanah menunjukkan perkaitan terus di antara hasil

dengan jumlah-N dan jumlah-C. Terdapat perkaitan songsang di antara hasil dengan

nisbah CN, K, Mn dan Na. Wujud perkaitan songsang di antara jumlah-N tanah

dengan N daun, Ca tanah dengan Ca daun, dan Mn tanah dengan Mn daun. Terdapat

perkaitan terus di antara hasil dengan bUangan bilah padi m-2, bilangan tangkai m-2,

bilangan spikelet tangkai-l, dan peratusan spikelet berisi. Wujud perkaitan terus di

antara jumlah-N tanah dengan bilangan tangkai m-2, bilangan spikelet tangkai-l, dan

peratusan spikelet berisi. Analisis komponen prinsipal menunjukkan tiga komponen

prinsipal pertama membentuk 59% daripada jumlah variasi dan ianya diwakili oleh

status kesuburan tanah, kation gantian di antara Na dan K, dan hubungkait

ketumpatan pukal tanah dengan kandungan lempung. Analisis regrasi tinar berganda

bagi eiri-eiri tanah, kandungan nutrien daun pada peringkat kematangan pokok padi,

dan komponen hasil telah memberikan persamaan-persamaan HasH == 517.78 + 69.13

jumlah N tanah, Hasil = 524.17 - 256.64 N daun + 102085.39 Cu daun + 2663.92 Mn

daun, dan HasH == 1 .55 (bilangan tangkai m-2) + 10.20 (bilangan spikelet tangkai-l) +

8.05 (peratusan spikelet berisi) - 47.61 (berat biji).

Semivariogram dan kriging berupaya menjelaskan variasi em-eiri tanah dan tanaman

di sawah padi. Peta variasi bilangan tangkai m-2 yang dihasilkan melalui interpolasi

kriging didapati mempunyai eorak yang menyerupai peta variasi jumlah-N tanah.

Sistem maklumat geografi dapat menentukan kedudukkan roang, dan menghitung

keluasan sesuatu julat nilai-nilai angkubah yang ditentukan untuk membantu

mengurus sawah padi dengan lebih cekap.

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ACKNOWLEDGEMENTS

The author acknowledges with profound appreciation particularly to the Chairman of

the Supervisory Committee Dr. Anuar Abdul Rahim for his continuous guidance,

encouragement and financial support till the completion of this thesis. To the

Supervisory Committee Members Associate Professor Dr. Mohd. Fauzi Ramlan,

Associate Professor Dr. Jamal Talib, and Mr. Ismail Adnan Abd. Malek for their

valuable guidance and suggestions in the preparation and improvement of this thesis

is highly appreciated.

Fullest appreciation is extended to the Land Management Department Laboratory

staffmembers: Mr. Fuzi, Mr. Mokhtar, Mr. Ariffm, Mr. Abdul Aziz, and Mr. Abdul

Rahim for assisting him in the soil physical and chemical analyses, Mr. Junaidi Jaafar

and Mr. Ghazali, assisted him in taking the study site GPS readings, and Mr. Asri for

his willingness in teaching him to use the various useful computer application

software programs.

He is grateful to his former staffs of Sungai Burong Rice Seed Production Centre for

helping him in collecting the soil and rice plant samples. He is also grateful to

Baratlaut Selangor Integrated Agriculture Development Project staff members for

their understanding in allowing him to use their office facilities for printing the draft

thesis. To his colleague Mr. Syed Fadzil Syed Shahabuddin, Agriculture Officer of

the Soil Division, Department of Agriculture who helped in identifying the soil

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properties to be studied� he extends his thanks. Special gratitude is given to Mr. Bazle

Jafti the energetic and dynamic farmer for allowing him to use the rice field as the

research site.

Sincere appreciation is extended to the Director General of Department of Agriculture

for granting him the study leave and scholarship to pursue his studies. Likewise� the

author wishes to express his love and appreciation to his wife and children who

provided moral and spiritual support, cooperation and inspiration that led to the

completion of this thesis.

Last but by no means least� he expresses his sincere thanks to friends and

acquaintances that in one way or another have contributed to the completion of the

study.

IX

I certify that an Examination Committee met on 19th December, 2002 to conduct the final examination of Mohd Nasir Warris on his Master of Agricultural Science thesis entitled "Spatial Variability of Soil Factors Affecting Irrigated Lowland Rice Yield" in accordance with Universiti Pertanian Malaysia (Higher Degree) Act 1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1981. The Committee recommends that the candidate be awarded the relevant degree. Members of the Examination Committee are as follows:

Syed Omar Syed Rastan, Ph.D. Faculty of Agriculture, Universiti Putra Malaysia (Chairman)

Anuar Abdul Rahim, Ph.D. Faculty of Agriculture, Universiti Putra Malaysia (Member)

Mohd Fauzi Ramlan, Ph.D. Associate Professor, Faculty of Agriculture, Universiti Putra Malaysia (Member)

Jamal Talib, Ph.D.

Associate Professor, Faculty of Agriculture, Universiti Putra Malaysia (Member)

Ismail Adnan Abd. Malek, Faculty of Forestry, Universiti Putra Malaysia (Member)

MSHER MOHAMAD RAMADILI, Ph.D. ProfessorlDeputy Dean School of Graduate Studies, Universiti Putra Malaysia

Date: .2 5 JAN 2003

x

This thesis submitted to the Senate of Universiti Putra Malaysia has been accepted as fulfilment of the requirement for the degree of Master of Agricultural Science. The members of the Supervisory Committee are as follows:

Anuar Abdul Rahim, Ph.D. Faculty of Agriculture, Universiti Putra Malaysia (Chainnan)

Mohd Fauzi Ramian, Ph.D. Associate Professor, Faculty of Agriculture, Universiti Putra Malaysia (Member)

Jamal Talib, Ph.D. Associate Professor, Faculty of Agriculture, Universiti Putra Malaysia (Member)

Ismail Adnan Abd. Malek, Faculty of Forestry, Universiti Putra Malaysia (Member)

AINI IDERIS, Ph.D. ProfessorlDean School of Graduate Studies, Universiti Putra Malaysia

Date:

Xl

DECLARATION

I hereby declare that the thesis is based on my original work except for quotations and citations which have been duly acknowledged. I also declare that it has not been previously or concurrently submitted for any other degree at UPM or other institutions.

I (Mohd Nasir Warris)

DEDICATION ABSTRACT ABSTRAK ACKNOWLEDGEMENTS APPROVAL SHEETS DECLARATION FORM LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS

CHAPTER

1 INTRODUCTION 1. 1 BackgroWld

TABLE OF CONTENTS

1.2 Objective of the Study

2 LITERATURE REVIEW

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Page

11 iii v vii ix Xl XIV xvi XIX

1 3

2. 1 Rice Industry 4 2.2 Botany of Rice 6 2.3 Field Water Depth 8 2.4 Leaf Area Index and Tiller Density 9 2.5 Nutrients Uptake by Rice Plant 10 2.6 Soil Physical and Chemical Properties 13 2.7 Yield Components 16 2.8 Climatic Environment 17 2.9 Variography 19 2.10 Kriging 21 2. 11 Spatial Variation of Soil Nutrients 23 2.12 Summary of Literature Review 25

3 MATERIALS AND METHODS 3.1 Study Area 26 3.2 Sampling Design 26 3.3 Data Collection 28

3.3.1 Analyses of Soil Physical and Chemical Properties 28 3.3.2 Field Water Depth, Leaf Area Index, and Tiller Density 30 3.3.3 Leaf Nutrient Content 30 3.3.4 Yield Components 31 3.3.5 Meteorological Data 32

3.4 Analyses of Data 34

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4 RESULTS AND DISCUSSION 4.1 Soil Physical Properties 38 4.2 Soil Chemical Properties 42

4.2.1 Soil pH 44

4.2.2 Soil Total-Carbon, Soil Total-Nitrogen, and CN Ratio 46 4.2.3 Soil Total-Sulphur and Available Phosphate 49 4.2.4 Exchangeable Potassium, Calcium, and Magnesium 51 4.2.5 Exchangeable Sodium, Manganese, Zinc, and Copper 55

4.3 Leaf Nutrient Content 59 4.3.1 Leaf Nitrogen, Phosphorus, Potassium,

Calcium, and Magnesium 61 4.3.2 Leaf Sodium, Manganese, Copper, and Zinc 66

4.4 Field Water Depth, Leaf Area Index, and Tiller Density 67 4.5 Yield Components and Yield 71 4.6 Correlation Analysis 77

4.6. 1 Correlations between Yield, Bulk Density, Clay Content, and Soil Moisture 77

4.6.2 Correlations between Yield Components, Bulk Density, Clay Content, and Soil Moisture 78

4.6.3 Correlations between Yield and Soil Chemical Properties 79 4.6.4 Correlations between Yield Components

and Soil Chemical Properties 8 1 4.6.5 Correlations between Yield and Leaf Nutrient Content 83 4.6.6 Correlations between Yield Components

and Leaf Nutrient Content 85 4.6.7 Correlations between Soil Nutrient

with Leaf Nutrient Content 86 4.6.8 Correlations between Field Water Depth,

Tiller Density, and Leaf Area Index 89 4.6.9 Correlations between Yield Components,

Field Water Depth, and Leaf Area Index 89 4.6.10 Correlations between Yield and Yield Components 90

4.7 Principal Component Analysis 91 4.8 Multiple Linear Regression Analysis 95

5 SUMMARY AND CONCLUSION 97

REFERENCES 102

VITA 111

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LIST OF TABLES

Table Page

1 Characteristics of MR 185 8

2 Geostatistical parameters and coefficient of variation of soil chemical properties of rice field 24

3 Methods of analysing bulk density, clay content and soil moisture 29

4 Methods and determinations of analysing soil chemical properties 29

5 Methods and determinations of analysing leaf nutrient content 31

6 Rating values of the soil chemical variables 36

7 Descriptive statistics of bulk density, clay content, and soil moisture 38

8 Geostatistical parameters of bulk density, clay content, and soil moisture 39

9 Descriptive statistics of soil chemical properties 43

10 Geostatistical parameters of soil chemical properties 44

11 Descriptive statistics of leaf nutrient content 60

12 Geostatistical parameters of leaf nutrient content 61

13 Descriptive statistics of leaf area index, tiller density, and field water depth 68

14 Geostatistica1 parameters leaf area index, tiller density, and field water depth 68

15 Descriptive statistics of yield components and yield 72

16 Geostatistical parameters of yield components and yield 73

17 Correlations between yield and bulk density, clay content, and soil moisture 77

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18 Correlations between yield components and bulk density, clay content and soil moisture 78

19 Correlations between yield and soil chemical properties 80

20 Correlations between yield components and soil chemical properties 82

21 Correlations between yield and leaf nutrient content 84

22 Correlations between yield components and leaf nutrient content 86

23 Correlations between soil nutrient and leaf nutrient content 88

24 Correlations between yield, field water depth, and leaf area index 89

25 Correlations between yield components, field water depth and leaf area index 90

26 Correlations between yield and yield components 91

27 Principal component analysis, eigenvalues, and proportions of variance to the total variance 92

28 Factor pattern for first three principal components 94

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LIST OF FIGURES

Figure Page

1 Location of the study area 27

2 Sampling pattern 28

3 Daily air temperature of MARDI Tanjong Karang weather station (1 st August - 30th November, 2000) 32

4 Daily relative humidity of MARDI Tanjong Karang weather station (1 st August - 30th November, 2000) 33

5 Daily rainfall of MARDI Tanjong Karang weather station (1 st August - 30th November, 2000) 33

6 Daily sunshine of MARDI Tanjong Karang weather station (1 st August - 30th November, 2000) 34

7 Isotropic linear variogram and kriged map of bulk density 40

8 Isotropic spherical variogram and kriged map of clay content 41

9 Isotropic exponential variogram and kriged map of soil moisture content 41

10 Isotropic linear variogram and kriged map of soil pH 45

11 Isotropic spherical variogram and kriged map of soil total-carbon 47

12 Isotropic spherical variogram and kriged map of soil total-nitrogen 48

13 Isotropic spherical variogram and kriged map of eN ratio 48

14 Isotropic linear variogram and kriged map of total-sulphur 50

15 Isotropic linear variogram and kriged map of available phosphorus 51

XVll

16 Isotropic exponential variogram and kriged map of exchangeable potassium 53

17 Isotropic exponential variogram and kriged map of exchangeable calcium 54

18 Isotropic exponential variogram and kriged map of exchangeable magnesium 55

19 Isotropic spherical variogram and kriged map of exchangeable sodium 56

20 Isotropic exponential variogram and kriged map of exchangeable manganese 58

21 Isotropic spherical variogram and kriged map of exchangeable zinc 58

22 Isotropic exponential variogram and kriged map of exchangeable copper 59

23 Isotropic spherical variogram and kriged map of leaf nitrogen 62

24 Isotropic linear variogram and kriged map of leaf phosphorus 63

25 Isotropic exponential variogram and kriged map of leaf potassium 64

26 Isotropic spherical variogram and kriged map of leaf calcium 65

27 Isotropic spherical variogram and kriged map of leaf magnesium 66

28 Isotropic exponential variogram and kriged map of leaf manganese 67

29 Isotropic spherical variogram and kriged map of leaf area index 69

30 Isotropic exponential variogram and kriged map of tiller density 70

31 Isotropic linear variogram and kriged map of field water depth 70

xviii

32 Isotropic spherical variogram and kriged map of number of panicles m-2 74

33 Isotropic exponential variogram and kriged map of number of spike lets panicle-l 75

34 Isotropic exponential variogram and kriged map of percentage of filled spikelets 75

35 Isotropic exponential variogram and kriged map of weight of 1000 grains 76

36 Isotropic exponential variogram and kriged map of yield 76

CN ratio

DOA

GIS

GPS

MADA

LAI

EC

t ha-l

RSS

CV

PC

PCA

MARDI

LIST OF ABBREVATIONS

Soil Total-carbon to Soil Total-nitrogen Ratio

Department of Agriculture Peninsular Malaysia

Geographic Information System

Global Positioning System

Muda Irrigation Development Authority

Leaf Area Index

Electrical Conductivity

tonnes per hectare

Residual Sum of Squares

Coefficient of Variation

Principal Component

Principal Component Analysis

Malaysian Agricultural Research and Development Institute

xix

1.1 Background

CHAPTERl

INTRODUCTION

1

Soil spatial variability occurs on a variety of scales, between regions, between fields or

within fields (Bouma and Finke, 1993). As soil serves as a growth medium for crops,

its physical and chemical conditions affect potential and actual crop yield. Field

variability of soil physical and chemical properties revealed spatial crop yield

(McBratney and Whelan. 1995).

Physical properties of soil that can vary spatially are structure and texture (McBratney

and Whelan, 1995). These two physical properties are important as they influence

directly or indirectly on other soil physical properties such as bulk density, water

holding capacity and soil strengths. Soil structure affects physical properties such as gas

diffusion, water movement and root anchorage. Soil texture influences crop growth and

yield by affecting nutrient availability, and water and gas movement (McBratney and

Whelan, 1995). Pedogenic processes mainly contribute to the spatial variation of soil

texture. Anthropogenic actions such as tillage can lead to changes in soil structure

variability (Cattle et ai., 1994).

Soil chemical properties that vary spatially include nutrients, pH, salinity and organic

matter. Spatial variation in nutrients occurred as a results of variation in nutrients

uptake by plants, level of leaching or a change to the system such as liming operation

altering the chemical balance of the soil (McBratney and Pringle, 1997). Bouma and

2

Finke (1993) mentioned that fertilizer applica�ions could increase the spatial variability

of soil nutrients due to uneven spreading patterns. Soil pH and salinity vary spatially

depending on factors that affect its accumulation and decay such as temperature, pH,

moisture content, oxygen availability, soil texture and management practices

(Jenkinson, 1988).

Current standard methods of soil sampling are designed to obtain a representative

composite sample from an area that is considered to be uniform with respect to soil

types, previous cropping, and fertilizer and lime use. In practice, a single field is

normally considered the sample area, although some large fields may be divided into

more than one sample (Dampney, 1997). Recommendations such as a uniform fertilizer

rate and seeding rate are made for the entire field without considering short ranged field

variation.

Precision agriculture is an approach for sub-dividing the fields into small, relatively

homogeneous management zone where agronomic practices such as tillage, liming,

seeding, fertilizing, herbicide spraying and infield water management are custom

managed according to the unique mean characteristics of the management zone (Mulla,

1997). Precision agriculture is a site specific management which will only be relevant if

agronomists have precise information on spatial soil conditions to enable delivering of

accurate specific advise (Voltz, 1997).

In Malaysia, there is a need for adoption of precision agriculture in the research and

extension of rice crop. New available technologies such as geostatistics, Geographic

Information System (GIS), Global Positioning System (GPS) and remote sensing can be

3

utilized to assist in the implementations of precision agriculture in rice farming (Laili,

2000). At present, it is necessary to gather data to characterize the small-scale soil

variability factors that may be expected over space and time in a rice field. Research is

required to ensure the data collected is representative of the true variation at this small

scale, to provide insights into its implications and use, and to maximize the benefits

obtained for agricultural farm management.

A field experiment was undertaken to test the hypothesis that spatial variability of soil

factors exist in a rice farm. In testing this hypothesis, the following aspects were

investigated:

1. The spatial variability of soil factors, rice leaf nutrient content,

yield, and yield components.

2. Correlations between soil factors with leaf nutrient content,

soil factors with yield and yield components, and leaf nutrient

content with yield and yield components .

3. Soil factors affecting yield and yield components of rice.

1.2 Objective of the Study

The objectives of this study are

1. To determine the spatial variability of soil factors of a rice farm.

2. To correlate soil nutrient with rice leaf nutrient content.

3. To determine the soil factors affecting yield and yield components.

2.1 Rice Industry

CHAPTER 2

LITERATURE REVIEW

4

Although rice is cultivated as far as 49 � in Czechoslovakia (Kratochvil, 1956) and as

far south as 35° in Australia but more than 90% of the world's rice growing-area is in

Asia. These include cOWltries in the South Asia region like India, Pakistan, Bangladesh,

Nepal and Sri Lanka and cOWltries in the Southeast Asia region like Myanmar,

Cambodia, Laos, Vietnam, Thailand, Malaysia, Indonesia and Philippines. COWltries in

the East Asia region like China, Japan, Taiwan and Korea is another important rice­

growing region of the world. World acreage of cultivated rice in 1998 was about 150.30

million hectare and rice crop ranks second to wheat in terms of harvested area. The

world rice production in the year 1998 was aroWld 563.20 million tonnes with average

yield of 3.75 t ha-1 (Anon, 2000).

Rice is an important food crop in Malaysia and forms the staple diet of the Malaysians.

Having average annual cropped area of about 660,000 ha in terms of total harvested area

of main season and off season planting in 1998, rice is the third most important crop in

Malaysia in terms of land-use after oil palm and rubber with 2.89 and 1.57 million ha

respectively (Anon, 1999). The COWltry average farm size estimated at 1.50 ha with

only two percent of farms exceeding 3.00 ha. The number of households engaged in

rice farming as a major income were 116,000 and higher number of households

involved in rice farming as a minor income of 200,000 households (Jegathesan, 1996).

In 1998, Malaysia produced 2.13 million tonnes of rice and met 73% of the country self­

sufficiency level (Anon, 1999). The national average for rough rice yield in the main

planting season 1999/2000 was 3.57 t ha-1 with Peninsular Malaysia achieving yield of

3.56 t ha-1 compared to 3.78 t ha-1 for Sabah and 1.63 t ha-1 for Sarawak. The national

rough rice yield average can be considered low when compared to rough rice yield

obtained from the well irrigated and better managed rice granary areas such as the Barat

Laut Selangor Integrated Agricultural Development Project with average yield of 4.57 t

ha-1 and MADA with average yield of 3.92 t ha-1 during the main planting season

1999/2000. In Barat Laut Selangor Integrated Agricultural Development Project more

than 12.50 % of the rice area had achieved greater than 6.00 t ha-1 of rough rice yield

(Anon, 2001).

The rice-growing areas of Peninsular Malaysia can be divided into three main types of

physiographic regions. Firstly, the marine coastal plain commonly found on the west

coast has a fertile rice field such as the Muda Irrigation Scheme and the Barat Laut

Selangor Integrated Agricultural Development Project but there are also swampy parts

of the coastal plain facing problems of excessive saturation, salinity and organic matter

accumulation encountered as in the Krian Laut Irrigation Scheme. Secondly, the

riverine flood plain found mainly on the east coast such as Kemubu and Besut Irrigation

Schemes may have colluvial, deposits from nearby hills and most of the soils in this

region are stratified. Thirdly, the inland valleys found mainly in the middle and upper

reaches of major and minor rivers such as in Negeri Sembilan, Melaka, Johor and

Pahang (Samy et al., 1980). The soils on the marine sediments have a higher pH, higher

organic matter content, higher cation exchange capacity and better plow sole

development than those soils developed on riverine alluvia. The mineralogy of the soils