Anais Malcolm Sumner

8/11/2019 Anais Malcolm Sumner

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The Diagnosis andRecommendation Integrated

System (DRIS): Theory andPractice

Malcolm E. Sumner1

INTRODUCTION

oliar diagnosis is a tool which is useful in diagnosing which nutrients are likely to belimiting the performance of a crop at any point in time. The DRIS approach has theparticular benefits of taking nutrient balance into consideration in making a diagnosis and

can also be applied without modification over a wider range of plant ages than the Critical Value

approach. It should be borne in mind at the outset that the growth of a crop depends on a host offactors from those which are uncontrollable such as light and temperature to those that are largely

controllable such as row spacing and cultivar selection !igure "#. $ll these factors condition the

plant%s response which is assayed using foliar analysis. $s a result& some factors such as drought&

waterlogging& low temperatures& pests& etc can alter the composition of a leaf without any changein the level of nutrients in the soil. The nutrient status of the soil is not a uni'ue function

governed only by the fertility of the soil. (ther factors can and do have marked effects.

Conse'uently& diagnosis based on foliar analysis that a particular nutrient is limiting in the plantdoes not necessarily mean that that nutrient is also limiting in the soil. !or e)ample& the presence

of parasitic nematodes in a soil can affect the ability of the roots to assimilate *. Conse'uently& if

a tissue sample is found to be deficient in *& that does not necessarily mean that the soil is alsodeficient. (ne has to consider other factors as well. Thus DRIS is simply a tool which assesses

nutrient balance and the order of limiting importance of nutrients of crop yield. To make effective

fertili+er recommendations& it ,-ST be used in conunction with the assessment of other factors

such as soil analysis& disease and weed conditions& moisture cultural practices& etc. $t best& foliardiagnosis merely informs the diagnostician of the nutritional status of the plant. /is e)perience

together with supporting information on other factors determining yield are re'uired in order to

make a fertili+er recommendation with the ma)imum chance of success. This process C$00(Tbe automated by a computer. 1ack of a clear understanding of the chain of events set off by a

fertili+er application is responsible for many of the problems that some workers have had in

applying DRIS correctly. This is illustrated in !igure 2 from which it can be seen that theinteraction between a fertili+er treatment and soil properties is conditioned by weather conditions

and cultural practices. The result of this interaction is the soil response measured by a soil test#

F

1Regents Professor Emeritus, University of Georgia, Athens, GA.

E-mail: malcolm.sumnergte.net


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to which the plant in turn reacts to give a plant response assayed by foliar analysis#. !or

e)ample& if a topdressing of urea on the soil surface is made and the ensuing weather is hot anddry& much of the 0 will be lost by volatili+ation and will not be reflected in changes in the soil or

tissue analyses. It should be borne in mind that a plant does not respond directly to a soil

treatment. Rather the plant responds to the soil response to a soil treatment. !or e)ample& in two

situations in which the level of * is comparably insufficient in a sandy soil on the one hand and aheavy ferruginous soil on the other& the application of a given 'uantity of * will definitely result

in different plant responses on the two soils. In the latter case& the soil response to the treatment

will be less in terms of an increase in available * than in the former. 3oth weather conditions andcultural practices can influence the soil and plant responses. !or e)ample& application of urea on

the soil surface followed by dry weather conditions will result in considerable volatili+ation

losses of 0 and conse'uently less 0 available for use by the crop.

3earing these considerations in mind any change in the conditions to which a crop is subected is

indeed a treatment and therefore the effects of both induced and natural treatments on crop

productivity should be studied. 3ecause these treatments can influence other factors in the wholedynamic plant4environment system as a result of a chain reaction5like mechanism& these

interrelationships should be studied. !inally& because any set of observations for a particular site

represents only one sample from the whole population& all sets of observations should be studiedirrespective of their origin& location or conditions at sampling.

In the classical approach to soil fertility research& field e)periments have been used to study theabove interrelationships. /owever& field e)periments have certain disadvantages in this regard&

notably the relatively small number of factors which can be varied simultaneously and the local

applicability of the data derived from a given e)periment. In order to overcome these difficulties&3eaufils "67"& "678# developed a scheme of e)perimentation which has culminated in the

Diagnosis and Recommendation Integrated System. 3efore developing the basic tenets of this

system and describing how the norms are derived& a word of definition is re'uired. $ccording to

the ()ford Dictionary& diagnosis is defined as 9a formal obective and reliable statementconcerning a given situation: or 9thedetermination and identification of the nature of a diseased

condition by investigation of its symptoms and history:. This is the initial aim of DRIS to

identify and set out the parameters of the problem but not to solve it automatically. The secondphase is that of recommendation of remedy and bridging the gap between the two phases re'uires

that other factors many of which are subective such as the knowledge& e)perience and

observational 'ualities of the specialist who makes the recommendation be taken into account.

$fter a brief description of the DRIS approach& consideration will be given to making diagnoses

under a variety of conditions to illustrate the importance of considering as many factors as

possible in making a diagnosis.

ESTABLISHMENT OF NORMS

In contrast to the classical field e)perimental approach to soil fertility& the DRIS approach

employs a survey techni'ue representative of the industry for which norms are desired. In this

survey& a large number of sites randomly distributed throughout the industry are selected. These


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sites can be both production fields or plots from e)isting field e)periments. ;ach site is analogous

to a plot in a field e)periment so that the survey approach yields a large number of sets ofobservations which can be considered as constituent plots in a large 9field: e)periment replicated

in time and space. $t each site samples of soil and leaf tissue are taken for analysis and details

concerning farming practices& weather variables& cultivar& irrigation& nature and amounts of

fertili+er applied& etec.& are recorded. The soil and leaf samples are analy+ed for a number ofessential elements by conventional means. $ll this information constitutes a data bank and is

stored in a computer in readily accessible form. (nce a data bank of this nature has been formed&

it enables one to study and calibrate these interrelationships. In this presentation only the foliardiagnosis aspects of DRIS will be dealt with. The norms are the means of the various forms of

e)pressing the leaf analysis data for a subpopulation of high yielding observations selected from

the data base together with their respective coefficients of variation. ;)amples would be 0


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deviations of the particular form of e)pression for the sample under diagnosis from the

corresponding norm value.

INTREPRETATION OF INDICES

The DRIS indices have positive and negative values which sum to +ero as they measure therelative balance among the nutrients. The order of plant re'uirement is given by the most

negative inde) indicating the most re'uired and the most positive& the least re'uired nutrient or

most e)cessive. This is illustrated in Table ". 0utrient balance is maintained in Table "a but withincreasing severity indicated by the 0utrient 3alance Inde) 03I# which is the sum of the indices

irrespective of sign and is a measure of the relative intensity of nutrient insufficiency. In Table "b&

the relative order of nutrients is maintained as e)tra nutrients are considered.

MEANING AND INTERPRETATION OF A RATIO

3efore proceeding& a short discussion on the meaning and intrepretation of a ratio is appropriatehere. 3ecause a nutrient ratio is the 'uotient of a numerator and a denominator& it is merely astatement of their relative proportions and does not give any information about the actual

magnitudes of either. 1et us assume that a ratio such as 04* has an optimum range corresponding

to the range found in high yielding crops and denoted by a hori+ontal arrow 6# indicating the

balance between 0 and *. In this situation& three possibilities e)ist?

04* @ 6& 064*6 or 084*8 or 094*9

3oth numerator 3oth numerator 3oth numerator

and denominator and demonitor and denominator optimal e)cessive insufficient

It is not possible from the ratio alone to detect which of the above possibilities represents thesituation in the plant. $ll that can be said is that 0 and * are in relative balance. If the 04* ratio is

either above 8# or below 9# the optimal range& two possibilities e)ist in each case?

04* @ 8 064*9 or 084*6

* insufficiency 0 e)cess

04* @ 9 064*8 or 094*6

* e)cess 0 insufficiency

In these two situations& the ratio does not distinguish between the two possible situations which

may e)ist in the plant. $ response to * would only be obtained if * is in fact insufficientJ if 0 ise)cessive and * normal& a yield response to * cannot be e)pected. The same is true for the second

case.

The relationship between the value of a nutrient ratio and crop yield is schematically illustrated in


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!igure 8. Khen the value of the ratio $43 is below the optimum& yields decline because either $

is insufficient or 3 is e)cessive while when it is above the optimum& yields also decline becauseeither $ is e)cessive or 3 is insufficient. Lields are potentially at a ma)imum when the value of

$43 is at the optimum but do not necessarily reach the ma)imum because some factors other than

$ and 3 are limiting..

VALIDATION OF DRIS NORMS

In order to test whether the norms established are capable of making valid diagnoses& it isnecessary to use independent e)perimental data preferably from factorial e)periments in which

yield responses were obtained to the particular nutrients under study. If the indices are able to

predict the pattern of the behavior observed in the e)periment& confirmation would result. Suchan e)ercise using the data from an 0)* factorial will now be undertaken Table 2#. 3eginning

with the 0"MG*Gtreatment& the DRIS indices diagnose that * is the most limiting of the three

nutrients under consideration. $ddition of * in treatment 0"MG*2Nresults in a decreasedre'uirement for * with a concomitant yield increase but * is still the most limiting. $ddition of

further * in treatment 0"MG*"GGresults in a further yield increase with 0 now becoming mostlimiting. $ddition of 0 in treatment 02OG*"GGgives a further increase in yield indicating that the

indices can correctly predict the pattern of response in the e)periment. If inappropriate treatmentsare made& for e)ample& applying 0 in treatment 0"MG*Gwhere it was not called for resulted in a

yield decrease. The same was true for treatment 0"MG*2N. $ response to 0 was finally obtained but

only after the * re'uirement has been satisfied& a trend correctly predicted by the DRIS approachbut ambiguous in the Critical Value approach.

EFFECT OF AGE OF TISSUE ON DIAGNOSIS

Kalworth and Sumner "6O7# has shown that if the data for the population of high yielding

plants are used& the variation with age in nutrient elements e)pressed as a percentage of the valueat a given point in time follows the pattern illustrated in !igure F. The concentration of some

elements such as 0& *& and = decrease with age when e)pressed on a dry matter basis while

others such as Ca and ,g increase with age. /owever& if one takes the reciprocal of Ca& i.e.&"4Ca& the latter also decreases with age similar to 0& * and =. ;)ploitation of this will be

illustrated later in the presentation. This effect of age of tissue on diagnosis is a factor that has

always presented problems because of the so called 9dilution effect:. 3ecause of this near

parallelism of the lines for 0& *& = and Ca& calculation of ratios such as 04*& 04=& etc used in theDRIS inde) calculation results in the near constancy of these ratios making them nearly

independent of age of tissue sampled as illustrated below?

04* @ "GG04D,#4"GG*4D,# @ "GG04D,# ) D,4"GG*# in which D, cancels out.

To illustrate that consistent diagnoses can be made over a range of crop ages& the data in Table 8are offered. The same order of re'uirement& namely& * H = H 0 is obtained irrespective of the

stage at which the crop was sampled. The Critical Value approach was unable to make a

diagnosisuntil the OGthday of the crop. This clearly illustrates the advantage of the DRIS approach in being


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able to make diagnoses at an early age which facilitates making corrective treatments. This is

particularly true with perennial crops such as sugar cane as illustrated in the e)ample in Table F.

EFFECT OF VARIETY

(ften varieties have differential abilities to assimilate nutrients and sometimes because they

grow at different rates& sampling of leaves at a given time results in the assaying of leaves of

different age. The effect of variety on diagnostic precision is measured in Table N. The DRISindices consistently diagnose the same order of re'uirement whereas for the Critical $pproach&

only * is deficient in two cases& and 0 and * in the remainder.

USE OF THE DRY MATTER INDEX

DRIS indices as normally calculated according to e'uations "5FE have values which are notfi)ed to a reference as they simply measure the relative balance between nutrients. In order to do

this& one may include the $4D,& 34D,& C4D,& etc ratios D, @ dry matter# in the inde)calculations as follows?

$ inde) @ Af$43# B f$4C#.... B f$4D,#+

3 inde) @ A5 f$43# 5 fC43#..... B f34D,#4+

C inde) @ A5 f$4C# B fC43#.... B fC4D,#4+

.

.

D, inde) @ A5 f$4D,# 5 f34D,# 5 fC4D,#.... 5 f,4D,#4+

where $4D,& 34D,& C4D,& etc are simply $


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/owever when the D, inde) is introduced& nutrients are limiting in the last two lines in Table M.

USE OF RATIOS AN PRODUCTS

Khen nutrients increase or decrease in opposite directions with the age of the crop& the use of

products instead of ratios becomes appropriate in the inde) calculations. $s illustrated in !igureN& 0& * and = usually decrease with crop age while Ca and often ,g increase with age. 3y

taking the reciprocal of Ca< and ,g< defined as P @ "4Ca and L @ "4,g& this results in forms

of e)pression which are products when combined with nutrients that decrease with the age of thecrop. Thus& 04"4Ca# @ 0>P and 04"4,g# @ 0>L. In the inde) calculations& the normal

e'uations are used e)cept for Ca and ,g# reciprocal values are used to calculate P and L

indices. The signs of these indices P and L# are then changed to give the Ca and ,g indicesreflecting the opposite directions in which the nutrients are varying with age. In this mode the

indices do not sum to +ero. (ne can thus develop a rule for calculating indices as follows? If thenutrients vary in the same direction with age& nutrient ratios are appropriate while if they vary in

opposite directions with age& nutrient products of the elements involved are appropriate. This isillustrated in Table 7 for a peach crop sampled at different ages. Khen indices are calculated

using ratios& the diagnosed order of re'uirement for nutrients varies with the age of thew crop

whereas when products are used& consistent diagnoses are made over the entire period sampled.

USING DRIS INDICES IN COMBINATION WITH OTHER GROWTH

LIMITING FACTORS

$ few e)amples will be presented to illustrate the importance of taking factors other than foliar

analyses into account when making a diagnosis of what the most limiting factor is and how itshould be corrected.

E!am"le 1

1et us assume that the following are the DRIS indices for a sugarcane crop sampled at 2 months

of age growing under favorable moisture conditions?

0utrient 0 * = Ca ,g S Qn

Inde) 52 52" 5"G M N 7 "N

The foliar diagnosis shows that * is the most limiting nutrient followed by = and 0 with Qn

being slightly e)cessive. The results of a soil analysis are as follows?

*arameter p/ * = Ca ,g S Qn

Rating M.G2 /igh ,edium $de'uate $de'uate ,edium /igh


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The soil analysis results are not congruent with those of the leaf diagnosis particularly in terms of*. The soil test for * is high but the DRIS diagnosis indicates that the plant was relatively

insufficient in *. $ddition of * fertili+er is unlikely to result in a yield response because sufficient

* is already present in the soil. This state of affairs points to the possibility that some other factor

in the soil was limiting * uptake. In view of the fact that the p/ was M.G2 above the value atwhich $l becomes to)ic& the most likely causes of this poor * uptake are nematode damage& root

diseases or root damage due to insects. The ne)t step would be to inspect the roots for damage

and identify the culprit. If the roots show that nematodes the appropriate action would be toapply nematicide such as Temik.

E!am"le #

1et us assume that the following is the DRIS foliar diagnosis for a corn crop that is 8 weeks old

growing and was planted very early in the season at a high elevation. The leaves are pale yellow

in color and e)hibit some striping.


Inde) 57 5N "2 O M F 5"O

The soil analysis is as follows?

*arameter p/ * = Ca ,g S Qn

Rating N.ON /igh /igh $de'uate $de'uate ,edium /igh

$gain the diagnoses are incongruent in respect of Qn and * indicating some factor that is limitinguptake of these nutrients. 3ecause both Qn and * in the soil are high& there is little likelihood of aresponse to additions of these elements to the soil. The problem most likely stems from low soil

temperature which limits root respiration. $s the root needs to take up both Qn and * against a

concentration gradient by active uptake& high root respiration is re'uired for this to take place.The best course of action will be to do nothing as once the soil warms up as the season

progresses& root respiration will increase and overcome the problem. $ topdressing of 0 will be

re'uired to overcome the 0 insufficiency.

E!am"le $

$ crop of soybeans is growing on an ()isol and at " month after planting is showing differentialgrowth in strips across the field in the direction of planting. The crop had been fertili+ed with

band place * and broadcast Sulpomag. Tissue analysis results in the following DRIS indices?


*oor N N 5"8 M 5F 5N M


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ood 58 G 8 2 " G 58

!rom these results it is clear that during the application of the Sulpomag& the applicator skipped

the poor strip in the field resulting in relative insufficiencies of =& S and ,g. $pplication of

Sulpomag to this area should cure the problem.

REFERENCES

3eaufils& ;.R. "67". *hysiological diagnosis? $ guide for improving mai+e production based on

principles developed for rubber trees. Fert. %oc. %. Afr. . "?"52O.

3eaufils& ;.R. "678. &iagnosis an' Recommen'ation (ntegrate' %ystem )&R(%*.Soil Sci.3ul ". -niversity of 0atal& South $frica.

3ishop& T. "6M7. Improved tissue diagnostic techni'ues for sugarcane. ,.Sc. $gric. Thesis&-niversity of 0atal& South $frica.

osnell& .,.. and $.C. 1ong. "67". Some factors affecting foliar analysis in sugarcane. Proc. %.

Afr. %ug. +ech. Assoc. FN?2"75282.

1ut+& .$. and ./. 1illard. "678. ;ffect of fertility treatments on the growth and chemical

composition and yield of no5tillage corn on orchardgrass sod. Agron. .MN?78G578M.

,elsted& S.K.& /.1. ,otto& and T.R. *eck. "6M6. Critical plant nutrient composition values

useful in interpreting plant analysis data. Agron. .M"?"752G.

Sumner& ,.;. "6O2. The Diagnosis and Recommendation Integrated System DRIS#. Council onSoil Testing and *lant $nalysis& $naheim& C$.

Sumner& ,.;. "6ON. +he &iagnosis an' Recommen'ation (ntegrate' %ystem )&R(%* as a

gui'e to orchar' fertiliation. !ood and !ertili+er Technology Center ;)t. 3ull 28"&!!TC4$S*$C& Taipei& Taiwan.

Sumner& ,.;. and ,.*.K. !arina. "6OM. *hosphorus interactions with other nutrients and lime infield cropping systems. A'v. %oil %ci.N?2G"528M.

Kalworth& .1. and ,.;. Sumner. "6O7. The Diagnosis and Recommendation Integrated System

DRIS#. A'v. %oil %ci. M?"F652"N.


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!igure ". Schematic representation of the interrelationships between crop yield and 'uality&

metabolic processes and e)ternal and genetic factors 3eaufils& "678#.

!igure 2. Schematic representation of relationships between soil treatment& weather conditions&

cultural practices and yield and 'uality of a crop Sumner& "6O2#.

!igure 8. Diagrammatic representation of the response of a crop to a number of limiting factors

Sumner and !arina& "6OM#.

!igure F. The effect of age on the different forms of e)pression for leaf composition of peaches

Sumner& "6ON#.

Table "a. Interpretation of DRIS indices

DRIS indices 0utrient balance

inde)

(rder of

re'uirement0 * =

F 58 5" M *H=H0

2F 5"O 5M FO *H=H0

FO 58M 5"2 6M *H=H0


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Table "b. Interpretation of DRIS indices

0utrient 0 * =

Value F." G.2N 2.GM

Inde) 2F 5"O 5M

(rder *H=H0

0utrient 0 * = Ca ,g

Value F." G.2N 2.GM G.NN G."O

Inde) "M 5"" 58 N 57

(rder *H,gH=HCaH0

0utrient 0 * = Ca ,g S Qn ,n 3 Cu

Value F." G.2N 2.GM G.NN G."O G.2F "7 O2 "G "8

Inde) "" 57 58 2 5M 5" 5"N O N N

(rder QnH*H,gH=HSHCaH3@CuH,nH0


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Table 2. Validation of DRIS corn norms for 0& * and = using independent data of 1ut+ and1illard "678#

Treatment kg4ha# 1eaf composition


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Table 8. ;ffect of corn crop age on DRIS and Critical Value diagnoses

$ge of

cropdays#

1eaf composition


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Table F. ;ffect of age of cane sampled on leaf composition and DRIS and Critical Value

diagnoses Data from 3ishop& "6M7#

$gedays

1eaf composition


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Table N. ;ffect of variety on leaf composition and foliar diagnosis of sugar cane Data fromosnell and 1ong& "67"#

Variety 1eaf composition


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Table M. Illustration of the use of the dry matter inde)

1eaf composition


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Table 7. Comparison if DRIS indices calculated using ratios and products for a peach crop

sampled at different times

$ge

days

1eaf composition

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Anais Malcolm Sumner