Buletin USAMV-CN, 63/2006 (-) ISSN 1454-2382

EVALUATION OF THE NUTRITIONAL STATUS OF PERENNIAL CROPS – POSSIBILITIES AND PITFALLS OF LEAF ANALYSIS

Schaller, Klaus

Research Centre Geisenheim, P.O. Box 1154, D-65356 Geisenheim, Germany

e-mail: k.schaller@fa-gm.de

Key words: leaf analysis, training system, clonal material, varieties, plant parts, Vitis vinifera, rootstocks, bud load Abstract: In a series of experiments the influence of training systems, clonal material, varieties and rootstocks on the nutritional composition of leaves was tested. It was found out that a strict sampling programme is necessary to get reliable result, which can further be used for the development of fertilizer recommendations.

INTRODUCTION

Analysis of plant foliage for diagnostic purposes has been practised since the last century and has gained considerable attention among agriculturists. However, the most and basic premises underlying foliar analysis, especially of perennial plants, have received relatively little attention.

The fundamental principles of plant analysis were created by Atterberg (1901), Lagatu and Maume (1934), Goodall and Gregory (1947), Lundegårdh (1951) and others. Walworth and Sumner (1987) summarized foliar diagnosis on the basis of their newly developed system and findings with annual agricultural crops. Assessing most of the proposals for leaf diagnosis it can be stated that they are useful with annuals and some tropical perennials, however, the transfer of these findings to temperate perennials shows some traps, which should be fully elucidated.

Grapevines are normally grown in soils with low or medium fertility levels, especially when they are used for winemaking. The basic idea is, that the influence of terroir should be transferred to the final product wine, which can only be achieved when a limited fertility level restricts growth and fruiting (INRA, 1996). Normal fertilizer application and fertility control via leaf analysis tries to develop a nutrient management system with which a yield maximum combined with a high profitability can be achieved. Therefore the proposed nutrient levels in plant organs, which are listed in the literature, cannot be directly used; only considering the restrictions that nutrient ranges have to be found which will indicate distinct and reduced yield levels combined with high quality expectations.

In addition, grapevines are perennials with a low plantation density and a lifetime of 20-30 years. In that specific case only indicator organs can be used for nutrient analyses because a whole plant analysis would remarkably reduce the production basis in contrast to annual agricultural plants where that procedure is more or less common.

Establishing a reliable plant analysis system it is necessary to decide on the different sampling procedures e.g. organ, time, insertion place and influence of varieties and rootstocks.

In order to get a deeper insight into the relationships between leaf composition and exogenous as well as endogenous influences a series of experiments was used to elucidate these relations.

MATERIAL AND METHODS

The Research Centre Geisenheim had established during the last two decades several viticultural trials dealing with different training systems, spacing, bud load, clonal material, rootstocks, new varieties and also fertilization.

The scheme of the trials is shown in Table 1. Table 1

Scheme of the trials under investigation

Trial Variety Clone Root stock Training system

Load (buds/m2)

Spacing (m2/plant

1. Testing leaf positions

Riesling 239 Gm 26G Half bow 12 2,5

2. Clonal material

Riesling 198 Gm, 110 Gm

5 BB Half bow, cordon

3, 3.75, 7)

3. Bud load Riesling 239 5 C Half bow 8, 12 2,5 4. Root stocks Riesling 239 5BB, 8B,

125AA, 5C, SO4, 3309,

SORI, 112D, NA: 1201,

61109, 37158, 5004, 76Z, 54Z, 579

Half bow 12 2,5

5. Varieties Riesling, Ehrenfelser,

Kerner, Thurling, Optima,

Schönburger, Kanzler

5C Half bow 8, 12 2,5

All trials were laid out in a block design with 4 replicates and observed with exception of the rootstock trial for five years. In contrast rootstock trial was planned on two different sites and observed for one year; trial on leaf positions was observed for two years.

Leaf sampling Leaves were sampled at three developmental stages:

1. Full bloom – after bloom (80% of flowers shed) 2. Version 3. Ripeness (60 0Oe / 14, 7 Brix)

Only leaves positioned opposite the first cluster and from the cane nearest to the stem were sampled. Leaves were separated in lamina and petiole. In the trial with different rootstock varieties leaves were divided in petioles, laminas and leaf veins. In the leaf positioning trial leaves were sampled opposite the cluster on the first shoot and the following ones up to the 10th. Within a shoot leaves were sampled beginning with the leaf opposite the cluster (1st position) and subsequently every 2nd up to the 5th.

Immediately after sampling leaves were cleaned with distilled water containing a detergent. Dry matter was determined by drying at 105 oC to constant weight. The dried plant material was milled and stored in plastic bags prior to analysis.

Analytical methods The dried plant material was wet ashed following a method described in Schaller

(199?). Nitrogen and phosphorus were determined with flow injection analysis (Schaller et al. 198?), potassium and calcium with flame photometry, magnesium with AAS. Results are expressed on a dry matter basis.

RESULTS AND DISCUSSION

Position of leaves The results for N, P, K, Ca and Mg were analyzed with a multidimensional analysis of

variance and a subsequent calculation of the components of variance the following results were achieved (table 1).

Table 1 Influence of leaf position on nutrient contents (component of variance %)

Compound Source of

variation

Year Shoot Leaf Date Y x S Y x L Y x D d.m. 11.8*** 5.9** N 30.8*** 1,5* 16.4*** 2.7*** P 15.8*** K 53.5*** 2.7*** 6.1*** 1.0* 4,1*** Mg 1.9* 3.5* 2.4* 8.6*** 8.1*** 3.4** Ca 32.4*** 2.1*** 7,9*** 30.9*** 1.3* 1.6*** *) p <5%, **) p <1%, ***) p <0.01%

From table 1 it can be derived that the year has a very high influence on nitrogen, potassium and calcium contents in leaves and a lesser impact is found on magnesium. The position of the shoots on the cane influences only the more mobile elements K, Mg and Ca; in general the more distant the shoot is positioned from the trunk the higher are the changes in nutrient element concentration.

The position of the leaves on shoots shows only a small influence on the concentrations of nitrogen, magnesium and calcium, but the shoot’s influence is more important.

Besides the year’s action on the nutrient composition of leaves the second important factor is sampling date. As can be seen, all nutrients are influenced by that factor with a different strength of action. The ranking in decreasing order is Ca, N, P, Mg, and K.

In addition some interaction could be determined between year x shoot, year x leaf, and year x date. The observed interactions are all significant and indicate that leaf analysis may be a useful tool for observing the nutrient balance throughout the development of a perennial.

Other important finding is that it is absolutely necessary for leaf analysis to standardize the sampling procedure in order to get reliable results.

Out of these findings it is recommended to make the following choices when leaf sampling is planned:

1st or 2nd shoot Leaf opposite the first cluster, if not fully developed use the 2nd or third in upward

direction sampling time should be full bloom – 80% of flower caps shed Clonal material In today’s viticulture most varietals are derived from clonal material. In some cases

only a small number of clones dominate a growing area. For example, Riesling in Germany as the dominating white wine variety occurs in five to ten clones. Therefore it is important to know if they have a significant influence on the nutrient composition of leaves.

From this 5 years trial it can be seen that there exists a small influence of the clonal material on the P content of leaves: ca. 10% of the complete variability of P in leaves can be referred to the clonal material. In absolute values the P-content of leaves varies between 0.18-0.24 % P in. dm, e.g. the clone is responsible for a variation of ±0.006 %. This range is quite small and is in the same magnitude as the analytical precision. The N content in leaves shows no

Fig. 1: Influence of clonal material and training system on the composition of grapevine leaves

(component of variance %)

influence from the clones, and K, Mg and Ca are in a range of 4, 2 and 1 percent resp.. Therefore it can be stated that for a normal leaf analysis it is not necessary to consider the clone.

A similar assessment can be made for the training system: N, P, K, Mg, and Ca show components of variance ranging from 1% for N up to 2,5% for P. The most important sources of variation are the sampling date and the year.

Fig. 2: Influence of clonal material and bud load on the composition of grapevine leaves

(component of variance %)

The influence of clonal material and the spacing, i.e. differing yield load, is demonstrated in fig. 2. Concerning the macronutrients N, P. K, Mg and Ca the most important sources of variation are the year and sampling date. Clonal material has only a minor effect on N and K, whereas the variability of P is influenced by a rate of 12% of the total variability. The influence of spacing varies in a range of 2 to 4% for N, P, Mg and Ca. For P and K a significant interaction between clone and spacing is observed with 18 and 6% respectively.

Varieties During a testing period of 5 years the leaf nutrient contents of six varieties were tested

at three sampling dates. The results of an analysis of variance are shown in fig 3. The

influence of the main sources of variation, variety, sampling date and bud load, show that only potassium is stronger influenced through variety (ca. 18%). The observed interactions between variety x sampling date (8%), variety x year (10%), and sampling date x year (6%) proof that the different varieties have differing developmental cycles (from early to late ripening) and consequently pass the stages under investigation not at the same time. In addition nutrient acquisition is also dependant from the year and the weather course.

Fig. 3: Influence of varieties and bud load on the composition of grapevine leaves

(component of variance %)

Plant parts, production sites and rootstock This experiment was conducted on two different sites with the variety Riesling grafted

on 15 different rootstocks. Leaves were sampled at three dates as indicated in the chapter material ad methods and at every sampling leaves were separated in petioles, veins and blades. The final results of the analysis of variance are shown in fig 4. The influence on the leaves nutrient contents is of minor importance: it ranges from 2 – 8% depending on the mineral nutrient. Especially K, Mg and Ca are more affected through he rootstock than N and P. There exists also a distinct influence of the site on the accumulation of K and Mg. This information is in good agreement with other tests, which show that soil and soil type are responsible for differing nutritional effects with plants. Sampling date exerts a highly significant influence on N, P and K in the different plant parts. The plant parts themselves take over a great part of the total variability for N, K and Mg.

Fig. 4: Influence of rootstock, production site and different leaf parts on the nutrient composition of grapevine

leaves (component of variance %)

CONCLUSION

Leaf analysis as a tool to evaluate the fertility status of perennial plants is wide spread. Results are mainly used to develop fertilizer recommendations. In that specific case results should have a high degree of reliability because the decisions derived from those analysis may have distinct influences on farm economy, environment and plant’s qualitative and quantitative development. Therefore is it necessary to develop a sampling system that is free from uncontrollable bias.

A great source of variation in leaf sampling is the position of leaves in a given canopy system. Results reveal that in common training systems based on cordon or half bow, the variability coming from shoot position on the cane as well as the leaf position is highly significant. As a first and important consequence the position of leaves intended for sampling has to be strictly fixed. According the calculated LSD5% it is recommended to sample the leaf opposite the first cluster or in case that this leaf is not fully developed to use the 2nd or 3rd in upward direction; it is also without any influence on the analytical results to sample horizontally up to the 5th shoot on the cane.

The other viticultural factors, which were tested, are of minor importance: training system, spacing and bud load. Their influence is sometimes significant but their part on the total variation is too small to be taken into consideration in a general leaf sampling programme (fig 1, 2).

The part dealing with the influence of varieties on leaf composition it was found out that they accumulate differing amounts of K.Mg and Ca in leaf blades. If these results can be used for sampling programme is questionable because the importance of the varieties, which were tested is by no means given. Their share in the complete varietal spectrum in Germany is quite low (3-5%). On the other hand if new varieties are introduced in the market developping an important market share, it is necessary to check the existing values.

Evaluating the influence of rootstocks and differing plant parts on the nutrient composition it was found out that the rootstocks have a quite small influence on the nutrient’s variability but the plant parts take over an important part of the total variance. In view of the circumstances that plant organs should give some information about the sites and time course of growth, the variability of nutrients in petioles is very small. Therefore it is more complicated to get definite facts for a reliable fertilizer programme. The conclusion drawn from our findings is to focus on the lamina as an indicator organ.

BIBLIOGRAPHY

Atterberg, A. 1901. Die Variationen des Nährstoffgehalte bei dem Hafer. Journal für Landwirtschaft 49: 97-172 Goodall, D. W. and F.G. Gregory. 1947. Chemical Composition of Plants as an Index of Their Nutritional Status. Imperial Bureau of Horticulture and Planatation Crops. Technical Communication 17 INRA 1996: Les Terroirs Viticole. Concept-Produit-Valorisation. 1er Colloque International 17-18. Juillet Angers, France Lagatu, H. and L. Maume. 1934. Action d’un engrais simple annuel sur l’alimentation NPK d’une même espèce végétale au cours de quatre annés successives de culture dans le m^me sol. Comptes Rendus Hebdomadaires des Séances de L’Academie d’Agriculture de France 20:549-563 Lundeghard, H. 1941. Die Tripelanalyse. Theoretische und praktische Grundlagen einer pflanzenphysiologischen Methode zur Bestimmung des Düngerbedürfnisses des Ackerbodens. Lantbrukhögskolans Annaler 9:127-221 Walworth, J.L. and M.E. Sumner. 1988. Foliar diagnosis: A review. Advances in Plant Nutrition 3:193-241