UNIVERSITI PUTRA MALAYSIA

EVALUATION OF THE MACROS-SAHEL MODEL FOR

THE RAINFED PRODUCTION OF CORN (ZEA MAYS L. CV SUWAN I)

RUSHIDAH BT WAN ZAIN

FH 1993 5

EVALUATION OF THE MACROS-SAHEL MODEL FOR THE RAIN FED PRODUCTION OF CORN

(ZEA MAYS L. CV SUWAN I)

By

RUSHIDAH BT WAN ZAIN

Thesis Submitted in Fulfi lment of the Requirements for the Degree of Master of Agricultural Science

in the Facu lty of Agricu lture, U niversiti Pertan ian Malaysia

April 1 993

ACKNOWLEDGEMENTS

The author wishes to convey her sincere g ratitude and than ks to Dr.

Wan S ulaiman bin Wan Harun , Chairman of the Supervisory

Committee, for his guidance and encouragement throughout the course

of the programme and h is valuable assistance in the preparation and

completion of this manuscript. Appreciation is a lso expressed to Dr. S .

Singh and Encik Zakaria bin Wahab for serving this committee.

Thanks are also due to the staff of the Department of Soil Science

and the Universiti's Farm Office for their cooperation and approval in

using the facilities.

Finally, the author expresses her utmost g ratitude to MARDI for

awarding the scholarship to pursue this course and to all her friends

and colleagues who had contributed to this study while not forgetting

her devoted family (Gie, Ee, E ri and Icam) for all the encouragement

and sacrifices.

i i

TABLE OF CONTENTS

ACKNO�EDGEMENTS

LIST OF TABLES

LIST OF FIGURES

ABSTRACT

ABSTRAK

CHAPTER

INTRODUCTION

Objectives of Study

II REVIEW OF LITERATURE

General

Climatic and Soil Requirements Corn Yield in Southeast Asia Corn Production in Malaysia

Water Stress and Corn Growth

Page

ii

v i

vi i i

ix

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1

3

4

4

6 7 8

1 0

Water Stress and Photosynthesis .... ........... 1 1 Water Stress and Crop Development 1 2 Water Stress and Corn Yield ......... ... . . . . . . . . . . . 1 3

Meteorological Factors Affecting Corn Production ...................................................... 1 5

Rainfall ................. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5 Temperature and Light ..... .... ............ ........... 1 6

Modelling Crop Growth 1 8

Com Models 19

iii

"' THE MODEL MACROS . . .......................... . ...... . .. . .... 22

Introduction ............... ...... ........ . ......... .. ............... 22

Production Level 1 .......... .................... ........ ....... 24

Carbon Dioxide Assimilation .......... . ............ . .. 26 Respiration and Growth ............... . ........ ....... .. 27 Partition ing of Dry Matter . . ....... . . . . . . . . . . . . . . . . . . . . . . 28 Leaf Area Growth and Senescence ......... ..... 29 Crop Development .......... .... . . . .. . . ..... .. . . .. ... . ..... 30

Production Level 2 . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

IV MATERIALS AND METHODS ................................. 35

Field Experiment 35

Data Collection 40

Weather Data ................. .... . .......... .... ......... ....... 42

Simulation at Production Level 1 .... .................. 42

Crop Data .... . ............................. ......... . . . . . . . . . . 43 Model Evaluation ............................... . ........... 45

S imulation at Production Level 2 ..... ............ ...... 45

Crop and Soi l Data ........................................ 46 Model Cal ibration and Evaluation ...... . ..... ....... 47

V RESULTS AND DISCUSSIO NS ..... ....... .......... .... . . . . 49

Soi l Physical and Chemical Properties 49

Weather ............................................................. 52

Field Experiment .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Y ield Components ........................................ .. 54 Growth Duration . ................... . . . . . . . . . . . . . . . . . . .. . . . . . 56

iv

Total Above-grou nd D ry Matter and Grain Y ie ld . ....... . . . . .. . .. .... ...... .. . ... . ... . . . . . . . . . 58

Plant He ight,Cob He ight, Cob Length and Numbe r of Rows per Cob ............... 60

M odel for Pote ntial Production ............. ............. . . .... 60

Developme nt Rates ............... .......... ....... . . . . . . . 60 Carbohydrate Partitioning ..... .... . .. .. . . .. . . . . . . . . . . . . 62 Specific Leaf Weight Constant .................. . .... 64 Model Calib ration ................ ............. . . ... . . .. . . . . . 64 Model Evaluation .................... ....... .... .. . ....... . . 70

Production Leve l 2 7 1

Mode l Calib ration and Adaptation .................. . 7 1 Model Evaluation ....... ..................... ................ 79

VI GENERAL DISCUSSION AND CONCLUSIONS 88

B IBLIOGRAPHY

APPENDICES

A Anova Tab les for Cob He ight, Plant He ight, Cob Length and N u mber of Kerne l Rows

92

per Cob ................................... ...................... 99

Functions CALVT, CASTT and CASST used in the S imulation . . . . . . . . . . ... . . . . .. . . . . . . . . . . . .. . . . .. ..... 1 01

Functions D RWT used in the Simulation . . .... 1 01

B L isting of Modu les for S imulation Program 1 02

C Abbrev iations in the M odu les of L istings for for an Explanation of CSM P Functions and Labels ... ...... ....... ........................ . . . . ....... ......... 1 09

VITA ....................................... ................................ . 1 1 8

v

Table

1

2

3

4

5

6

LIST OF TABLES

Corn Production in Major Producing Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . ... .

Total Area Grown to Corn in Malaysia

Import of Corn (unmilled) into Peninsular Malaysia . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .

Soi l Characteristics of Experimental S ite

Total Amount of Water Received During the Growing Per iod from Emergence to Maturity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . .. .

Treatment Effect on the C rop Components (Hundred Seed Weight, N um ber of Kernel Rows per Cob and Number of Kernels per Row) . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7 Growth Duration (from Emergence to Physiological Maturity) of S uwan I and the Relation of Water Stress Level for the Different

8

9

Treatments

Treatment Effect on the Above-ground Dry Matter and Grain Y ield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Comparison of Development Rates of Vegetative (DRCV) and Reproductive (DRCR) Phases for Temperate and Tropical Corn Varieties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .

1 0 Observed and S imulated Crop Components with Various FSTR Fractions for Potential

1 1

1 2

Production of corn cultivar S uwan I

Observed and S imulated Crop Duration and Y ie ld of Suwan I for Potential Conditions at Kubang Kranj i . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . . . . . . . ..

Root Length with Respect to Days after Emergence (DAE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

v i

Page

5

9

1 0

50

54

55

57

59

61

67

70

72

1 3 S im ulation Resu lts with Function DRWT I and Various Maximum Rooting Depth of Crop (ZRTMS) .......................................................... 75

1 4 S im ulation Resu lts with Functions DRWT I I and Various Maxim um Rooting Depth of Crop (ZRTMS) ..................... .......... ................ ....... . . . . 76

1 5 Observed and S im ulated Values for Suwan I u nder Partial ly I rrigated Conditions ......... . . . . ....... 80

vii

Figure

1

2

3

4

5

6

7

8

9

LISTS OF FIGURES

Relational Diagram of a System at Production Level 1 ...... .. ............... ....... ... ....... .

Relational Diagram of a System at Production Level 2 . ... . .... . .. ............ ..... .......... ..

Schematic Diagram of the Experimenta l Layout .. ........................................................... .

Schematic Diagram of Arrangement of Dr ip Irrigation in a Plot .. .... ... ......... .................. ... ... . .

Schematic D iagram of Ind ividual Plots Showing Sampling Rows and Harvested Area . . . .. . .. .... .

Soil Water Characteristic of D ifferent Soi l Layers in the Exper imental Plot ............ .................. .. .

Rainfal l Distr ibution During the Growing Period of the Corn Crop (November 1 989 -March 1 990) ... ........ . ..... ..... ... . .. .. . .... ............ .

S pecific Leaf Weight for Corn cv Suwan I as a Function of Development Stage .......... .... ..... .

Observed and S imulated B iomass of Above-ground Plant Parts of Corn cv Suwan I ... .. ...... .... . ... ... ............ .... . ... . . ..... ... .

1 0 Observed and S imulated Soi l Moisture Content

1 1

1 2

1 3

1 4

for Rainfed p lot

Observed Soi l Moisture Content in Treatments 1 , 2 and 3 in 0-1 5 cm Soi l Layer . ... .. ... ........ . ..

Observed Soil Moisture Content in Treatments 1 , 2 and 3 in 1 5-30 cm S oi l Layer ... . .. ..... . . . . . .

Observed Soil Moisture Content in Treatments 1 , 2 and 3 in >30 cm Soi l Layer . ...... .... .... .. ... .

The Relation between the Soi l - water Content and the Stress Multiplication Factor on the Rate of Water Uptake . ... . .... . .. ... .. . .... ...... .. ..... .

vi ii

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Abstract of thesis submitted to the Senate of Universiti Pertanian Malaysia in fulfilment of the requirements for the degree of Master of Agricultural Science.

EVALUATION OF THE MACROS-5AHEL MODEL FOR THE RAIN FED PRODUCTION OF CORN (ZEA MAYS L CV SUWAN I )

By

RUSHIDAH BT WAN ZAIN

April 1 993

Chairman: Assoc. Prof. Wan Sulaiman bin Wan Harun . Ph. D .

Faculty : Agriculture.

There is an urgent need to cultivate g rain corn on a large scale in

Malaysia to meet the g rowing demand. Before attempting to do this a

thorough evaluation of environmental effects on the growth and yield

of the crop has to be u ndertaken. One way of doing this is by using

simulation models. Therefore the main objective of this thesis is to

adapt the MACROS (crop growth) model for the simulation of potential

and rainfed production of corn cultivar Suwan I.

A field experiment was set up at Serdang for the establishment of

the crop data for corn cultivar Suwan I . The crop data were partitioning

of assimilates to the different organs, specific leaf weight constant and

crop development rates. They were then used to adapt the MACROS

ix

model for simulating potential yie ld of corn with the L 1 D modu le and

subsequently the rainfed yie ld of the crop, the latter using the SAHEL

modu le for the water balance.

Evaluation with data obtained from Kubang Kra nji in Kelantan gave

a sim ulated potential yield of between 8 ,31 3 kg ha-1 and 9,685 kg ha-1

compared to the observed yield of between 7,066 kg ha-1 and 8 ,833 kg

ha-1• The sim ulated growth duration was within -2 to +3 days of the

observed . Evaluation for SAHEL was carr ied o ut using the data

obtained from Serdang. There was no apparent d ifference i n the

simu lated yield and crop d uration when the crops were not irr igated

for 7 to 2 1 days at 42 days after emergence . The observed and

simulated rainfed yield s were between 5 ,964 kg ha-1 and 6,636 kg ha-1

and between 7,657 kg ha-1 and 7 ,659 kg ha-1 respectively, while their

respective crop growth d urations were between 98 days and 1 00 days,

and 1 01 days. Overal l , the MACROS model was able to simulate

yield and crop d uration accurately for potential production but to a

lesser extent the rainfed production.

The MACROS model is very well adapted to the study of

behavioural patterns or response to environment changes and crop

manipulations. More precise data on other crop data such as the rate

of loss of leaf area and basic physiological data pertaining to

photosynthesis have to be established in order to improve the model

for predicting or simu lating absolute yields of specific varieties or

x

cultivar . The model is also potential ly capable of predicting yields for

any planting dates within a year. Therefore, MACROS can be used by

growers to schedule their time of planting and estimate the yield.

x i

Abstrak tesis yang d ikemukakan kepada Senat Un iversiti Pertanian Malaysia bagi memenuh i syarat keperluan untuk mendapatkan ijazah Masters Sains Pertan ian .

PENILAIAN MODEL MACROS-5AHEL U NTUK PENGELUARA N JAGUNG BIJIRIN (ZEA MAYS L CV SUWAN I ) 01 KEADAAN

TADAHAN HUJAN

Oleh

RUSHIDAH BT WAN ZAIN

April 1 993

Pengerusi: Prof. Madya Wan Sulaiman bin Wan Harun, Ph.D

Fakulti : Pertan ian

Bagi memenuh i keper luan jagung bijirin semasa d i Malaysia ,

penanaman jagung secara besar-besaran perlulah d ijalankan .

Sebelum meneruskan perusahaan in i kajian pertalian d i antara

persekitaran dan pengeluaran hendaklah terlebih dahulu d ijalankan.

Salah satu cara ialah penggunaan model simulasi. Dari itu objektif utama

tesis i n i ialah untuk menguji kesesuaian model (tumbesaran

tanaman) MACROS bagi mensimulat hasil potensi dan

keadaan tanpa pengairan bagi jagung bijirin, jenis Suwan I .

dalam

Satu percubaan di ladang telah d ijalankan di Serdang bagi

mendapatkan data-data tanaman jagung. Data- data tersebut ialah

pengagihan asimilat ke atas bahagian-bahagian tanaman, angkali berat

daun yang k husus dan kadar tumbesaran tanaman . Data-data

xi i

tersebut kemudiannya dipadankan kepada model MACROS bagi

mensimulat hasil potensi jagung menggunakan modul L 1 0 dan SAHEL

bagi hasil d i keadaan tadahan hujan.

Penilaian model dengan data-data yang d iperolehi daripada Kubang

Kranji d i Kelantan menunjukkan hasil potensi dari simulasi ialah d i

antara 8,31 3 kg sehektar dan 9 ,685 kg sehektar berbanding dengan

hasil sebenar, d i antara 7 ,066 kg sehektar dan 8,833 kg sehektar.

Tempoh tumbesaran tanaman yang d isimulat pula berbeza di antara -2

h ingga +3 hari dari tempoh sebenar. Penilaian ke atas SAHEL pula

menggunakan data-data yang d iperolehi daripada Serdang. Tiada

perbezaan yang nyata pad a hasil simulasi bi la tanaman tidak menerima

air selama 7 hingga 2 1 hari mulai dari 42 hari selepas d isemai . Hasil d i

keadaan tadahan hujan, sebenar d a n simulasi ialah masing-masing di

antara 5.964 kg sehektar dan 6 ,636 kg sehektar. Manakala tempoh

tumbesaran sebenar ialah di antara 98 dan 1 00 hari dan simulasi 1 01

hari. Pada amnya, model MACROS berupaya untuk mensimulat

dengan tepat hasil dan tempoh tumbesaran tanaman untuk pengeluaran

jagung berpotensi tetapi kurang berkesan di dalam keadaan tanpa

pengairan .

MACROS sangat sesuai bagi mengkaji poria tindakbalas tumbesaran

terhadap perubahan persekitaran dan manipulasi tanaman. Data-data

yang lebih tepat seperti pertalian d i antara kadar kehilangan luas

permukaan daun serta data fisiologi seperti fotosintesis hendaklah

xi i i

ditentukan supaya penggunaan model dapat diperbaiki dan dapat pula

mensimulat atau meramal hasil mutlak jagung dari jenis atau kaltivar

yang khusus. Model in i juga berpotensi untuk meramal hasil jagung

bagi mana-mana tarikh tanaman d isepanjang setahun . Oleh itu model

MACROS boleh d ijadikan sebagai panduan untuk menjaduaJ serta

mengira hasil yang akan d iperolehi oleh pengusaha tanaman jagung .

xiv

CHAPTER I

INTRODUCTION

Large scale corn production in Malaysia have to be expanded in

order to meet the growing demand parallel to the expansion of the

swine a nd pou ltry industry. The annua l import of corn worth 400 m il l ion

r inggit (Malaysia , 1 988) is expected to increase to one bil l ion r ingg it by

the year 2000 (MARDI , 1 990) .

Before venturing into large scale production , the crop performance in

d ifferent locations in relation to the interactive effects between the

environment and the crop needs to be evaluated. The most important

environmenta l factor for corn production in Malaysia is rainfal l. I nspite

of the h igh average a nn ua l rainfa l l (in excess of 2400 mm), rainfed

production of annual crops have not been very successful because of

the uneven and unpredictable rainfal l d istr ibution . The inconsistent

weather conditions pose a great problem to the farmers in estimating

the best time to plant the ir crop a nd the expected yield . To reduce their

r isk , farmers plant their crop immediately after the monsoon when

moisture is considered to be adequate for seed germination and the

subsequent crop growth. The low yield for commercia l production of

grain corn, reported to be within the range of 0 .9 to 3.9 mt ha-1

(MARD I , 1 98Gb), was main ly due to moisture deficits.

1

2

The complex interactive effect of the external factors on crop growth

can be investigated and best be handled by a systems approach or

crop g rowth simulation models. Crop growth models can be used for

quantifying the environmental l imits to crop production apart from a

broad spectrum of other purposes including an understanding of the

plant and its processes (Jones and Kiniry, 1 986). Their application not

only minimize the costly and lengthy experimentation but also resu lts

can be obta ined within a short period throug h computer simulations.

Modelling and simUlation studies require read ily available weather

records. Static models based on soi l water budgets from rainfall and

evaporation have been used by researchers as a first step in calculating

the expected productivity of the agricuHurai systems under a wide range

of climatic conditions. They have been used to develop aHemative

choices and decision strategies for use under l imited available water.

Amnuay (1 980), Steward and Hash (1 982) and Reddy (1 983) studied

com y ie ld prediction in rainfed conditions using rainfal l and evaporative

records for agricultural planning . Recently, dynamic phYSiologically based

models such as MACROS (Penning de Vries at al., 1 989) developed

after BACROS (Wrt, 1 978) and SUCROS (Kuelan at al., 1 982) have

been shown to be effective as growth simulators. The model MACROS

was developed for annual crops and is widely used in crop g rowth

simulations for rice, soyabean and wheat.

3

Objectives of Study

The general objective of the study is to adapt and evaluate the

model MACROS for potential and rainfed production of com cultivar

Suwan I. There is insufficient crop data to enable the modelling of the

crop in Malaysia. The basic crop data can be grouped, firstly, into

physiologically based crop data which are fairly universal and applicable

to a wide range of environment. Most of these are available from the

literature. The second group are cultivar specific and for Suwan I , are

still lacking. Thus the specific objectives of the study are:

1 . To establish crop data for cultivar Suwan I for use in the MACROS model (Pen ning de Vries at al., 1 989). namely:

i. Carbohydrate partitioning for growth of leaves (CAL VT), stem (CASTT) and storage organs (CASST)

i i . Crop development rates during vegetative (ORCV) and reproductive (ORCR) phases

i i i . Specific leaf weight constant (SLC)

2. To adapt and evaluate the MACROS model for potential and rainfed yield of corn cultivar Suwan I in Malaysia.

CHAPTER I I

REVIEW OF UTERA TURE

General

Corn or maize (Zea mays L.) has been cultivated for thousands of

years. Com parts first spotted in New Mexico were believed to be

about 4500 years old (Berger, 1 962). At the time of discovery of the

New Wand , corn was already cultivated in many parts of the American

continents, mainly in Mexico, Central America and parts of South

America . During the voyages of Columbus, corn was brought to Spain

and later spread to other parts of E urope and northern Africa. At the

beg inn ing of the sixteenth century com was brought to India and

China . Until today the most important cultivated areas are sti l l in

America, in the states of Ohio, Indiana, I l l inois and Iowa. The production

according to the major regions of the wond is shown in Table 1 .

The g rain is heavi ly consumed in countries like Portugal, Republic

of South Africa , Brazil , Guatamela, Venezuela, I ndia and Mexico where

it is served as a special food in the native d iets. I n the Philippines,

corn is a substitute cereal crop for rice for 20 percent of its population .

4

Table 1

Corn Production in Major Producing Countries

Corn production (million metric ton) Countries

1 979-81 1 987 ·1 988 1 989

U .S.A 1 92.1 1 8 1 .2 125.2 1 9 1 .2 (29.7) (24 .0) (23.6) (27.2)

China 60.7 79.5 77.7 75.8 (20.0) (20.3) ( 19 .6) (20.4)

Brazif 1 9.3 26.8 24.8 26.5 (1 1 .4) (13 .5) (13.2) (1 2 .9)

Mexico 1 1 .9 1 1 .6 1 0.6 9.9 ( 6.8) ( 6 .8) ( 6.5) ( 5.9)

S. Africa 1 1 .2 7 .3 7.1 1 1 .7 ( 4 .9) ( 4 .0) ( 3.7) ( 3.8)

India 6.5 5.7 8.3 7.8 ( 5.9) ( 5.6) ( 5.9) ( 5.8)

Philippines 3.2 4 .3 4.2 4.5 ( 3.3) ( 3.1) ( 3.7) ( 3.5)

Figures in parentheses represent total cultivated area for the specified years, in million hectares (Source: FAO Production Year Book, 1 989).

Com is used as raw material for industrial products in dry mining. wet

milling. mixed feed manufacturing and distillation and fermentation.

Outlets for dry milling are corn -meal. com flour. grits and breakfast

cereal. For wet milling, products are in the form of starch, feed. sugar,

oil and dextrines. The distillation and fermentation industries

manufacture alcohol. acids. glycerol and whisky.

5

6

CHmatic and Soil Requirements

Com is planted over a much wider range of climatic conditions than

either wheat or rice due to its adaptability. It is an important crop in

both the warm temperate and the humid sub-tropical regions of the

world. The climatic and soil requirements for the crop are well

described by Aldrich et al. (1976). It requires a growing season of 100

to 140 days depending on the climate. It is a neutral to short day

length crop requiring an average temperature of 18°C to 30°C. The

relative humidity during Us growth stages should be 40 to 80 percent

and at maturation stage, 30 to 40 percent. The crop requires between

500 mm and 800 mm rainfall during its entire growing season (MARDI,

1986a).

The soil requirements for com in Malaysia are summarized by

MARDI, (1986a). It can be grown on a wide variety of soils but performs

best on well-drained, deep loam and stH roam containing abundant

organic matter and nutrients such as the riverine and marine terraces

and flood plains. Developed peat is also fairly suitable for corn

cuHivation. The crop performance is very poor on IT1UCk or peat soils.

Com may be grown on moderately acid soils, but the optimum pH

range is from 5.3 to 6.0 with an exchange capacity of 18 to 30 cmoJ(+)

kg-1 and 75 % base saturation. The Bray No.2 extractable P for maize

should ideally range from 16.4 ,..g g-l to 20.5"'9 g-l. Soil bulk density

of 1.3 Mg m-3 or less is desirable for com growth.

7

Com Yield in Southeast Asia

Corn y ield was reported to vary between locations due to climatic,

soil and genetic factors (varieties and hybrids). However, the i r

variations can be minimized by exerting maximum inputs and efficient

management practices. In the Ph il ippines, maximum yields of between

8 and 1 0 mt ha-1 have been achieved (Lantin . 1 987) . In Thai land ,

Pakistan and Indonesia yields were reported to be 5.8 - 9.0 mt ha-1

(Kunta , 1 987) , 7.1 - 1 0 mt ha-1 (Bahadur, 1 987) and 5.4 - 6 .2 mt h a-1

(Subandi , 1 987) respectively. In Malaysia , the reported maximum yield

so far was only between 6 .0 and 7 . 1 mt ha-1 (Leong ,1 988). The low

yield recorded in Malaysia cou ld partly be due to the composite cultivar

used (Suwan I). The reported yields in other countries were from hybrid

cultivars.

The major factors that l imit corn y ield in the tropics are drought and

water logging (Mercado, 1 987). Rainfed yields are expected to vary in

time and place depending on the amount and d istribution of rainfal l .

Zakaria and Razak (1 990) reported that the d rought affected yield was

between 2 .5 and 3.0 mt ha-1 whilst for crops affected by both drought

and waterlogging the y ield was between 0.6 and 1 .4 mt ha-1• Drought

and waterlogg ing can cause poor crop establishment and thus reduce

the crop population. I n Indonesia , farmers make use of early maturing

cuHivars of 75 to 80 days (Subandi , 1 987) to minimize the risk of

drought and waterlogging . The yield obtained in this case was less

than 3 mt ha-1• I n the Philippines, Serran no and Aller (1 987) reported

8

yields of 3.5 to 5.7 mt ha-1 for partially stressed crop (irrigation witheld

for 35 days after planting) and 2 .3 - 2 .6 mt ha-1 for the rainfed crop.

Besides exerting maximum inputs and efficient management

practices corn yield in Southeast Asia could also be improved by using

h igh yielding cultivars.

Com Production in Malaysia

The potential areas for corn cu ltivation in Peninsular Malaysia can

be d ivided into two categories. The fist category includes al/ areas

under perennial crops and double-cropped rice areas. Cultivation on

such land is l imited due to the existing crops. The second category is

the rainfed rice areas, forest areas, peat swamp forest and idle farm

land. The areas are fairly small indiv idually and scattered while

planting during the drier periods normally requires irrigation, especially

in Perlis, Kedah, Kelantan and Terengganu. Past records and

experiences have indicated that d rought is a major problem in corn

cultivation and plays a major role in grain yield reduction in Malaysia

(Lee, 1 986).

AHhough production areas of corn increased annually (Table 2). the

supply of grain corn for animal feed is far from sufficient. Imports amount

to thousands of tonnes per year worth more than 200 million ringgit

(Table 3) , mainly from China, Australia, Burma, Thailand and Argentina

(Malaysia. 1 988) . By the year 2000 import is expected to increase to

9

almost a b illion ringgit (MARDI , 1 990) . Local grain production has to be

expanded in order to reduce imports and to save foreign exchange.

Table 2

Total Area Grown to Corn in Malaysia

Year Hectare

1 980 51 1 8

1 984 4744

1 985 4750

1 986 4591

1 987 5904

1 988 6063

(Source: AgricuHure, Livestock and Fisheries Statistics for Management. Ministry of AgricuHure, Malaysia , 1 988).

Table 3

I mport of Corn (unmilled) into Pen insular Malaysia

Year Quantity Value (000 metric ton) (M$ CIF)

1980 418.7 160.4

1981 459.6 181.0

1982 672.9 226.5

1983 742.2 256.6

1984 834.4 293.5

1985 916.3 273.5

1986 944.6 244.7

1987 1,030.9 271 .5

(Source: AgricuUure, Livestock and Fisheries Statistics for Management. Ministry of AgricuUure, Malaysia, 1987).

Water Stress and Com Growth

10

Plants require water for the manufacture of carbohydrate, maintain

hydration of protoplasm and for translocation of food and mineral

nutrients. I nternal moisture stress causes reduction both in cell division

and elongation, hence growth and final yield .

The combination of high incidence of solar radiation , moderate wind

speed and low relative humid ities plus the loss of water through the

soil-plant system (evapo-transpiration), speeds up moisture stress. At