Concept of Yield Potential

CONCEPT OF SITE YIELD POTENTIAL AND ITS APPLICATIONS IN OIL PALM PLANTATIONS K.J. Goh, K.K. Kee, P.S. Chew, H.H. Gan, Y.C. Heng and H.C.P. Ng [Presented at the OFIC2000 Conference, Sept. 4, 2000, Kuala Lumpur]

Abstract: Abstract: The oil palm industry in Malaysia must further improve its productivity and efficiency by maximising land resources in order to be sustainable. Increasing productivity and profitability are largely reliant on maintaining high yield levels. Nevertheless the scenarios of stagnating yields of major plantation groups, ever increasing production cost of crude palm oil and the declining real price trend of palm oil continue to be disconcerting to the industry. One way to mitigate against this disconcerting trend is by reducing the cost of production, which is closely related to productivity per land area. In the case of the oil palm industry, achieving the highest possible yield for any given site or the site yield potential (SYP) could prove to be the best way in maximising our land resources, hence cushioning against the uncertainty of palm oil prices with the reduction of production cost. Information on SYP could also be used as an objective yield target and as a benchmark for evaluation of estate’s performances besides being used to draw up appropriate implementations implementations according to priority.

Introduction The oil palm industry in Malaysia must further improve its produ producti ctivit vity y and and effic efficien iency cy by maxim maximizi izing ng land land reso resour urce cess in orde orderr to be sust sustai aina nabl ble. e. Incr Increa easi sing ng productivity and profitability, which are largely reliant on main mainta tain inin ing g high high yiel yield d leve levels ls,, are are cruc crucia iall to a 1 sustai sustainab nable le planta plantatio tion n indus industry try.. Howe However ver,, three three scenarios continue to be disconcerting for the oil palm indu indust stry ry.. Firs Firstly tly,, aver averag agee yiel yields ds from from the the major ajor plantation groups, the ‘backbone’ of the industry, have stagnated since the mid-1980s. They hovered between 20 and about 22 t fresh fruit bunches (FFB) per hectare per year against the reported genetic yield potential of about 45 t FFB per hectare per year.2,3 On the other hand, production cost for crude palm oil has increased almost linearly since 1994. This increase is expected to follow

through if the monthly wage scheme demanded by the plantation workers is adopted. Thirdly, the real price trend of palm oil according to Fry4 has been declining since 1960s as shown in Fig. 1. The main ain cons conseq eque uenc ncee of thes thesee scen scenar ario ioss is declining profits, which may lead to non-sustainability of oil palm plantations. One way to mitigate against this disconcerting disconcerting trend is by reducing the cost of production. Labo Labour ur is the the bigg bigges estt cost cost item item in the the esta estate te constituting about 47% of the ex-estate production cost. Labour cost over FFB yield per unit area is the main component affecting the ex-estate cost as seen in Fig. 2. Incr Increa easi sing ng FFB FFB yiel yield d per per unit unit area area will will lead lead to a corresponding reduction in the ex-estate cost. The best way of real realis isin ing g this this is by maxi maximi misi sing ng our our land land resourc resources, es, i.e. achieving achieving the highest highest possible possible yield for any given site, which is the site yield potential.

2000 1800 1600 n 1400 o t r 1200 e p $ 1000 S U 800 7 9 9 600 1

400 200 0 1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

Year Year

P a lm Oi l P ri ce

Tre nd i n Re a l P ri ce

Source: Fry (1998) 4

Figure 1. Real price trend of palm oil since 1950

Malaysian Malaysian Oil Science Science and and Technology Technology 2002 Vol. 11 No. 2

57

Concept of Site Yield Potential and its Applications in Oil Palm Plantations

Labour cost FFB per ha

Ex-estate cost

Figure 2. Labour cost over FFB per unit area is the main component affecting ex-estate cost

Definitions of Yield Genetic Yield The The gene geneti ticc yiel yield d pote potent ntia iall of a crop crop has has been been defi define ned d as the the larg larges estt yiel yield d obta obtain inab able le if all the the environmental conditions and agronomic decisions were perfect and there are are no management constraints constraints5. Corley computed the genetic yield potential of oil palm to be about 44 to 46 t/ha/yr at peak yield.3 However, However, such ideal conditions and yield are seldom attained except in special growth chambers, small experimental plots and probably occurs in less than 1% of oil palm plantings.6 More realistic FFB yields of 30 – 37 t FFB/ha/yr were reported by Tarmizi et al. on a wide range of soils in fertiliser trials and by Ng and Thong, Lee and Toh and Goh et al.7-10 in commercial fields. Site Yield While the genetic yield potential is a useful concept particularly to plant breeders, it cannot be used as yield targets on a large scale, which is how the oil palms are currently cultivated and managed.6 Oil palms are planted under under many many differ different ent enviro environm nmenta entall condi conditio tions ns and and therefor thereforee there there will be yield limiting limiting factors factors in these these areas. areas. These These yield-lim yield-limiting iting factors factors may restric restrictt light utilis utilisati ation, on, water water avail availabi abilit lity y and and rooti rooting ng activ activity ity.. e n i l c e d d l e Not easily i y f amenable o n factors o i t c e r i D

Different Different planting patterns and densities for example can affect light utilisation by the palms as the total leaf area per unit ground area will vary.11 On the other other hand, hand, diff differ eren entt rain ainfall fall,, soil soilss and ter terrain rain affec ffectt water ater availability to the palms. Other soil factors such as soil depth, consistence, structure and drainage will affect the palm rooting activity. These yield-limiting factors will limit the achievable yield to a level below the genetic yield potential, i.e. the site yield potential (SYP).5 The SYP therefore is the maximum yield realisable given a set of site characteristics characteristics in a particular environment.12 Actual Yield Agro-ma Agro-managem nagement ent ineffici inefficiencie enciess and constrain constraints ts will reduce yield further and widen the gap between the actual actual yield and the site yield potential. potential. Examples Examples of these yield-reducing and yield-loss factors are poor palm nutrition, canopy damage by pests and herbicides, poor drainage drainage,, weed competiti competition, on, poor harvestin harvesting g standard standardss and poor crop recovery. A schematic diagram illustrating the three definitio definitions ns of yield yield is portr portraye ayed d in Fig. Fig. 3. Yield-reducing and yield-loss factors are amenable and by correcting these limitations, the actual yields can be improved to the SYP. On the other hand, yield –limiting factors e.g. irrigation in dry regions, are usually difficult and costly to overcome. overcome.

Genetic yield potential: maximum yield obtainable without any environmental, agronomic and management constraints

Yield limiting factors: light utilisation, water & rooting activity

Site yield potential: maximum yield realisable, given a set of site characteristics

Amenable factors

Yield reducing factors: mainly agromanagement, e.g. nutrition, drainage, canopy damage, weed competition, etc.

Yield loss factors: mainly management, e.g. poor harvesting standard including crop recovery, etc

Actual yield: yield recovered from the field Figure 3. Schematic diagram of different definitions of yield Malaysian Malaysian Oil Science Science and and Technology Technology 2002 Vol. 11 No. 2

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Concept of ASYP The ASYP (AAR Site Yield Potential) is an empirical model developed to predict the site yield potential (SYP) of oil palm palm for any giv given envi envirronm onment ent or site chara characte cteris ristic tics. s. ASYP ASYP is expre expresse ssed d as a functi function on of various various plant, plant, soil and environm environmental ental factors factors that may influence yields as follows: ASYP = f (F 1 x F2 x F3 x … Fn) x G Where F1 to Fn are are the site-s site-spec pecifi ificc facto factors rs that that influence yields. Each factor has a score from 0 to 1. G is the genetic genetic yield potentia potentiall of oil oil palms palms 13 (taken as 45 t FFB per hectare per year). From Light to Yield For the palms to grow and produce crop, they must have have sunlig sunlight ht and and soil. soil. Sunligh Sunlightt provi provides des ener energy gy for for photosynthesis and the soil acts as the medium for water and nutrient supply. Solar radiation needs to be captured efficiently in order to maximise photosynthesis. This is best done by the correct planting density and pattern in the field in order to ensure that optimum light is captured for photosynthesis by the oil palms. According to Tan and and Ng, Ng, 14 the optim optimum um densit density y is depend dependent ent on the the degree degree of inter-palm inter-palm shading shading and competition competition at their resp respec ecti tive ve age age and and vigo vigour ur.. It is also also repo report rted ed that that equilateral triangular plantings give the best cumulative

yiel yield. d. In addi additi tion on,, ligh lightt use use effi effici cien ency cy need needss to be 15 optimised through good planting materials. For the uptake of water and nutrients from the soil, three factors are involved that is the rooting activity of the palm palms, s, and and nutri nutrient ent holdi holding ng capac capacity ity and water water hold holdin ing g capa capaci city ty of the the soil soil.. Thes Thesee fact factor orss can can be influenc influenced ed by soil soil volume, volume, soil structur structure, e, consiste consistency ncy and terrain. One final factor is climate, which affects the rate rate of photosynthesis photosynthesis and potential potential amount amount of water store stored d by the soil. soil. The The latter latter will will affec affectt sever severity ity and and frequency of moisture stress experienced by the palms, which hich will ill have have an impa impact ct on FFB FFB yiel yield. d. Fig. Fig. 4 summarizes these factors and their relation to dry matter production for both both growth and yield. ASYP Computati Computations ons ASYP ASYP takes takes into account account all the factors factors that may influence the yield of oil palms, namely: (a) Plant lantin ing g mater ateria ials ls (e.g. e.g. AAR, AR, Golde olden n Hope, ope, Chemara, HRU, etc). (b) Quali uality ty of plan planti ting ng which hich is depe depend nden entt on the the planting density and planting pattern. pattern. (c) (c) Soil Soil facto factors, rs, which which are influ influenc enced ed by soil soil volume, volume, structure, consistency and terrain. (d) (d) Clima Climatic tic factor factorss by takin taking g into into acco account unt moist moisture ure stress severity and frequency.

Light Planting Density Capture Photosynthe is Climate

Planting Pattern Efficiency

Planting Material

Dry matter: Growth and Yield Volume Uptake

Rooting activity Structure Nutrient Nutrient Capacity Water Capacity

Soil

Water

Consistency Terrain

Nutrients Nutrients

Figure 4. From light to yield: what does it take?


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Concept of Site Yield Potential and its Applications in Oil Palm Plantations These These factor factorss are are trans translat lated ed into into mathe mathema matic tical al equations and along with the historical data, i.e. rainfall data, they are then built into a model. This model, the ASYP 2.8, is programmed into AA AeGIS®, which is a Decision Support System (DSS). Using this model, the site yield potentials of an oil palm field from year 3 to year 30+ after planting can be generated for any set of given given site characteri characteristics stics.. An example example is known of a 1985 planting of an estate where the site yield potential in year year 2000 2000 was was 38 t/ha t/ha/yr /yr.. The AeGI AeGIS S DSS DSS also also contains the yield records of the estates on a per field basis so that actual yields obtained can be easily compare compared d against against the SYP. SYP. With this, palm and field performances performances of the estates can be assessed objectively and quickly.

Validation of Results The accuracy of ASYP computation depends largely on the accuracy accuracy of the inputs; inputs; namely namely the yield limiting limiting factors factors stated stated earlier earlier.. Accurate Accurate spatial spatial informa information tion of soils and terrain, moisture stress computation etc. will therefore improve the accuracy of the SYP generated by the model. The The model model was was valida validated ted using using data data from from three three indep independ endent ent trials trials,, i.e. i.e. one one irrig irrigati ation on trial trialss and and two two maximum yield trials and in three commercial estates with different rainfall patterns. However, only the results (Figs. 5a and 5b) from the two maximum yield trials carr carried ied out in centr central al Selan Selangor gor (for (for young young palms palms on

Munchong series, Typic Hapludox) and central Johore (for mature palms on Kawang series, Typic Kanhaplud Kanhapludult) ult) are discussed discussed as they have the longest, longest, 13 accurate yield records. records. For young palms, there was a response to fertiliser applicati applications. ons. Thus, best treatment treatment yields yields are the best best indi indica cato torr of SYP. SYP. Tria Triall resu result ltss show showed ed that that best best treatment yields followed closely to the SYP predicted by the ASYP model. The only exception is the yield from the first year of harvesting (Fig. 5a) whereby the actual yield was far below the SYP. This was mainly due to the effects of rhinoceros beetle damage on the palms in the firs firstt year year after after planti planting. ng. Howe However ver,, for for matur maturee palms, there was no response to treatments. treatments. Thus, mean trial yields are good indicators of SYP. The mean trial yield yield fluct fluctuat uated ed aroun around d the SYP as seen seen in Fig. Fig. 5b. Cumulatively the actual yield achieved was 96% of the SYP. Therefore, ASYP is capable of providing realistic and achievable yield targets for both young and mature palms for a three three year period. As more accurate data is obtained for an area, the ASYP SYP can can be rege regene nera rate ted d to take take into into acco accoun untt the the updated conditions. The accuracy of field yield records in plantations can vary considerably especially for block hectareage.2 It is important to ensure that block hectarage are are corr correct ect so that that actua actuall yields yields achie achieved ved refle reflect ct the actual potential of the block. Actual results can then be compared more realistically for the SYP generated by the model.

45 40

t ( 35 d l e 30 i Y 25 B F 20 F

ASYP2.8

15

Best tr trt yield

10 3

4

5

6

7

Age(yea ears) 13

Source: Kee et al. (1998)

Figure 5a. Comparison of ASYP and actual yields achieved for young palms on Munchong series soils 45 40

t ( 35 d l e 30 i Y 25

B F 20 F

ASYP2.8

15

Best tr trt yield

10 3

4

5

6

7

Age(yea ears)

Source: Kee et al. (1998)13

Figure 5b. Comparison of ASYP and actual yields achieved for mature palms on Kawang series soils Malaysian Malaysian Oil Science Science and and Technology Technology 2002 Vol. 11 No. 2

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Limitations of ASYP The ASYP model like all models, has its limitations, i.e. (a) (a) The The ASYP ASYP model model is not a yieldyield-fo forec recast asting ing tool tool as seasonal yield trend has not been taken into account (b) (b) The The model model does does not not predi predict ct accura accuratel tely y for for the first first year of harvesting and also for palms above 20 years old. This is because for the first year of harvesting, variation in the field is usually greater in terms of growth of palms and number of supplies. Also, the palm age when it is brought into harvesting varies considerably between plantings. For palms over 20 year years, s, over over-p -pru runi ning ng is usua usuall lly y nece necess ssar ary y for for harvesting purposes and this has not been taken into account by the model. (c) The ASYP ASYP uses rainf rainfall all record record of at least least ten years. years. Therefore short-term moisture stress effects are not totall totally y taken taken into into acco account unt.. Their Their effec effects ts on the growth growth and yield yield of oil palms palms are still still not not fully fully understood and thus cannot be modeled. (d) The effects effects of by-produ by-products cts utilisation utilisation i.e. i.e. empty fruit fruit bunches (EFB) and palm oil mill effluent (POME) (POME) which which can improve improve poor, poor, shallow shallow or lateritic lateritic soils are also not accounted for by the model.16 (e) The ASYP ASYP assumes assumes a good good standard standard of plantin planting g and thus fields, which are poorly planted or planted with inferior quality palms (such as etiolated seedlings etc.), cannot be accurately predicted. (f) (f) The The detr detrim imen enta tall effe effect ctss of floo floodi ding ng are are also also not not included in the model.

Applications of ASYP As a Benchmar Benchmark k SYP generated by the model can be used as an obje object ctiv ivee benc benchm hmar ark k to asses ssesss palm palm and and esta estate te performances. performances. For example, the actual yield achieved can be expressed as % of the site yield potential. If the figur figuree obtain obtained ed is 85% or more more,, the area or estat estatee is likely likely to have good managem management ent standard standardss with only minor or very few agronomic problems as seen in Table 1. However, if it is 50% or less, then that area/estate is likely to have very serious agronomic problems and/or poor management management standards. Gener Generati ation on of the SYP SYP using using the model model requi require ress character characterizati ization on and quantific quantification ation of all factors factors that affec affectt SYP. SYP. The The exerc exercise ise will will quickl quickly y identi identify fy and and quantify the most critical problem or constraint present in the given block. block. There Therefor fore, e, if the actual actual yield yield is gro grossly ssly low lower compa ompare red d to the the SYP, YP, the the fact factor orss

contributing to ASYP (or yield limiting factors) should be reworked reworked first. If the yield limiting factors were correctly identified, then the yield gaps are likely due to yield reducing and yield loss factors (e.g. manuring and harvestin harvesting g standard standards). s). Appropr Appropriate iate measure measuress to rectify rectify these yield reducing and yield loss factors can then be drawn up to improve yields. Table 1. An example of a benchmark to assess performance of an area

Benchmark Criterion (%)

Potential Agronomic Problems

Potential Management Management Standards

> 85

Minor

Good

70 – 85

Moderate

Good or Satisfactory

50 – 70

Serious

Satisfactory or Fair

< 50

Very Serious

Poor

Note: Benchmark Benchmark criterion to assess estate estate performance performance = (

Actual Yield Site Yield Potential

) x 100%

To Set Targets The SYP is the maximum yield that can be achieved for the given site. Thus, it can be used as an objective yield target for the estates to attain. Thus, we would not expect the oil palms on shallow lateritic soils to yield more than 30 t/ha/yr when the site yield potential for that area is only 22 t/ha/yr, and vice versa. Fertiliser rates to be recommended recommended for each field can therefore be drawn up in relation to the SYP based on the nutrient balance appr approac oach. h. This This will will avoid avoid both both excess excessive ive or under under application of fertilisers. fertilisers. To Set Work Priority Estates have limited resources and manpower. Thus, it is necessary to prioritise the work programme on the estat estate. e. The The concep conceptt of SYP can can be used used to help help set set priority of work in the estates. For example, priority of work should be given to fields with the largest yield gaps between the actual yield and the site yield potential instead of fields with the lowest yields. This is because, the lowest lowest yieldi yielding ng field field (Field (Field B of Table Table 2) may alrea already dy be close to the site yield yield potent potential ial and thus, thus, further improvements improvements are limited. Conversely in Field A, the potential for yield improvement improvement is higher and priority should be given to i mprove yields in this block.

Table 2. Comparison of fields with different yield gaps Field

Major Soil Type

Actual Yield (t/ha/yr)

ASYP (t/ha/yr)


A

Deep clayey soil

22.1

28.0

79

B

Shallow lateritic soil

20.7

22.0

94

C

Alluvial soil

22.9

27.0

85


64

Concept of Site Yield Potential and its Applications in Oil Palm Plantations Table 3. Comparison of estates in different regions / states Estates in (State)

Average Actual Yield (t/ha/yr)

Average ASYP (t/ha/yr)


Selangor

22.0

27.0

81

Negeri Sembilan Sembilan

20.0

21.0

95

In the the same same way, way, perfor performa mance ncess of estate estatess on a regional scale can be compared as shown in Table 3. Estat Estates es in Selan Selangor gor are are actua actually lly underunder-per perfo form rming ing compared to estates in Negeri Sembilan even though the average yield for Selangor estates is 22.0 t/ha/yr or 10% higher than those in Negeri Sembilan. Estates can be ranked according to the yield gaps between actual and SYP. Estates with more than 20% yield gaps may be identified for special attention. Within these estates, we can go a step further and investigate the fields with the largest yield gaps. Dominant factors or yield constraints constraints that account for the large large differen differences ces can then be identified and rectified. Other Potential Uses of ASYP The ASYP can also be used as a tool to help in strategic strategic planning planning e.g. when to replant, replant, by identifyin identifying g fields with large yield gaps where correction is best done by replanting. This is because because the low actual yields could could possibly be due to the decrease in density caused by dise diseas ases es,, very very tall tall palm palmss whic which h redu reduce ce harv harves estin ting g effi effici cien ency cy etc. etc. A stud study y on the the viab viabil ilit ity y of land land conversion to oil palm should also include the SYP for that land so that only those with high SYP should be purchased for long-term long-term sustainability.

The benefits of achieving the site yield potentials are obvious. obvious. It can cushion cushion against the uncertain uncertainty ty of palm oil prices, help reduce the cost of production and avoid both under-application (which can be detrimental to the palms) and excessive application (which can be detrimental detrimental to t o the environment) of fertilisers.

Acknowledgements We wish to thank Applied Agricultural Research Sdn. Bhd Bhd and and our our Princ rincip ipal als, s, Mess Messrs rs.. Bous Bouste tead ad Esta Estate tess Holdings Bhd. and Kuala Lumpur Kepong Bhd. for their permission permission to present this paper. We also acknowledge the inputs of our colleagues at AAR who have made the preparation preparation of this paper possible.

References 1.

2.

3.

General Remarks In the ASYP model, the site yield potential levels are generall generally y predeter predetermine mined d after after planting planting and very very little can be done to change the yield limiting factors after that as they they are are usual usually ly diffic difficult ult and and costl costly y to amend amend,, for for 2 exampl examplee irriga irrigatio tion n in dry regio regions ns.. Thus, Thus, work work and and emphasis should be on eliminating yield reducing and yield loss factors, factors, which which are more amenable amenable so that the actual yield achieved is as close as possible to the site yield potential.

4.

5.

Conclusions In conclusion, ASYP provides an objective yield target for estates and as a benchmark for evaluation of estate performances. performances. It can also be used as a tool to help the managem management ent and agronomist agronomist to be more focus on the main problems i.e. fields with large yield gaps and not necessar necessary y fields fields with low yields. yields. Dominant Dominant factors factors or yield constraints constraints can then be identifie identified. d. Appropr Appropriate iate correcti corrections ons can then be drawn drawn up for implementat implementation ion accordin according g to priority. priority. In addition, addition, the ASYP can also help help in plan planni ning ng for for exam exampl plee when when to repl replan ant, t, and and whether or not to acquire a certain piece of land.

6.

7.


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