For this purpose several approaches like soil testing, specific range approach, critical leaf nutrient concentrations, nutrient ratios, DRIS, SSNM etc. have been exploited. But there are certain limitations to each of the above mentioned approaches. Which among the above is the best and why?
Each technique has got its advantage and limitation. That is why it is recommended to make a mix of them. For instance, soil test values can indicate adequate level, but it cannot accurately predict growth condition thereafter as this will inevitably affect the availability of the nutrients found by soil test, for instance soil moisture. However soil test did give a precise measure of the fertility status provided that the test method is resilient and reliable. On the other hand, tissue analysis provide a snapshot of the plant nutrient status at one point in time disallowing at the same time the possibility for crop recovery granted better environmental condition prevail afterward.
So if possible, plant and soil testing should not be seen in isolation but they do complement each other and at the same time prevailing crop growing condition should not be ignored if not controlled in the interpretation of test results.
Regarding ratios they do address issues such as varietal differences and some time soil types, but they may fail to identify impending deficiencies if all element being tested are for example at suboptimal levels. In a few word there is no straight answer to this complex issue especially when exposed to the vagaries of environmental conditions.
Each technique has got its advantage and limitation. That is why it is recommended to make a mix of them. For instance, soil test values can indicate adequate level, but it cannot accurately predict growth condition thereafter as this will inevitably affect the availability of the nutrients found by soil test, for instance soil moisture. However soil test did give a precise measure of the fertility status provided that the test method is resilient and reliable. On the other hand, tissue analysis provide a snapshot of the plant nutrient status at one point in time disallowing at the same time the possibility for crop recovery granted better environmental condition prevail afterward.
So if possible, plant and soil testing should not be seen in isolation but they do complement each other and at the same time prevailing crop growing condition should not be ignored if not controlled in the interpretation of test results.
Regarding ratios they do address issues such as varietal differences and some time soil types, but they may fail to identify impending deficiencies if all element being tested are for example at suboptimal levels. In a few word there is no straight answer to this complex issue especially when exposed to the vagaries of environmental conditions.
@Jean Paul: I'd like to apply a basket of tests, in several locales. Cost & execution present risk. Your thoughts please on a mix of 4-6 lowest entry, highest relevance yield substantive tests. Your preferred recommendations etc.
Understanding which strategies yield the most important information for diagnosing soil condition. Time, budget & cost restraints always limit what can be accomplished in a field settling.
For diagnosing nutrient deficiency/sufficiency, several approaches like soil testing, specific range, critical leaf nutrient concentrations and nutrient ratios have been exploited. But there are certain limitations to each of the above mentioned approaches as
Soil testing does not take into account factors such as soil temperature and aeration, and even the higher or lower absorption due to the own plant nutritional needs.
Plant analysis has been considered a very practical approach for diagnosing nutritional disorders and formulating fertilizer recommendations.
But Plant analysis, in conjunction with soil testing, becomes a highly useful tool not only in diagnosing the nutritional status but also an aid in management decisions for improving the crop nutrition. Plant analysis is the quantitative analysis of the total nutrient content in a plant tissue, based on the principle that the amount of a nutrient in diagnostic plant parts indicates the soil’s ability to supply that nutrient and is directly related to the available nutrient status in the soil.
Critical leaf nutrient concentrations have frequently been used to diagnose nutritional causes of crop under performance. However the critical concentration approach is somewhat erroneous in that ‘critical nutrient concentration’ is not independent diagnostics, but can vary in magnitude as the background concentrations of other nutrients increase or decrease in crop tissue.
Recognition of this problem has led to the use of nutrients ratio pairs in certain situations, e.g. N/K and N/S, rather than single nutrient concentrations, as more reliable diagnostic criteria. However, this approach only assesses the sufficiency status of a single nutrient (e.g. K) on the basis of its abundance relative to one other nutrient (e.g. N), and makes no allowance for potential imbalances with other essential nutrients.
The flaws in nutrient ratios can be overcome by employing the technique of Diagnosis and Recommendation Integrated System (DRIS). As DRIS goes much further than single nutrient ratio approach, in that it employs a minimum of three nutrient ratios per diagnosis, and often as many as six or seven. Hence, The DRIS evaluation method of the plant nutritional status is considered an effective tool for nutritional diagnosis, because it is relatively complicated, compared to traditional methods such as critical level and sufficiency range. Nevertheless, it is promising for the nutritional diagnosis of perennial crops, for which calibration tests are generally time consuming and costly.
Hi again Duane,
Thanks for explaining yourself, and from Mumtaz post (thank you) he explains in more details the limitations of the different diagnostic techniques. To add on to his input and being aware that the cost involved in analysis is often a serious limitation, we ought to consider the past history and fertility management practices of the land. This will allowed an informed decision with regard to the test that should be entertained in other word its relevance since we can beforehand identify the potential limiting factors to productivity.
For instance if P fertilizers has been applied continuously we may expect accumulation of the same in the soil so analyzing the soil for residual P availability can demonstrate that there is no need for more P fertilizer which represent saving on input and the same approach may be adopted when it come to tissue testing.
The soil environment is critical to nutrient availability consequently test like soil pH and salinity (for those dealing with saline soils) are essentials since they regulate and often dictate the fate of applied fertilizers as well as inherent the soil nutrient supplying capacity.
From the plant perspective I would also consider the previous crop yields, (1) is to identify the yield potential of the site that can improve fertilization maintenance or optimize its rate and (2) it provides some guidance on the possible residual value of past fertilization for the present crop - the Replacement Concept.
The idea is to collect all existing information relevant to fertility management analyze them with a view to identify the most limiting element(s) ( sound easy-but challenging) with reference to local standard especially for soil testing (develop to suit local condition-empirical testing) and there decide on the most critical tests.
Analysis of snap shot soil samples is virtually useless in case of the macro-nutrients P and N. For the reasons you may consult my paper with Esselink on ResearchGate about cereals and grass ( Spain). Leaf samples of plants may be the better choice. However, you need to give plant phenology and season due attention in sampling. On the latter I may provide additional references on request.
Hello Hein,
Thank you. Glad if you can email your paper at [email protected]. With regard to N I agree buT for P I will disagree, soil test is a reliable index for fertilizer recommendation, granted that the soil test precisely measure the available P.
In my opinion the DRIS method has advantages over traditional methods for being based on nutritional ratios instead of average levels of each nutrient, eliminating dilution and concentration effects that are not dealt with adequately by traditional methods. In addition, variations in the ratios are considered, which allows the development of standardized indices, which are less onerous because they do not require extensive local calibration tests.
Dear Mumtaz,
DRIS does improve and extend scope for the interpretation of foliar diagnosis provided that there is an extensive and reliable and robust database that includes the three classes of nutrient because as I mentioned earlier from a balance uptake viewpoint operating at suboptimal fertility condition for any essential element may fail to disclose the impending deficiencies, all being on the low side. So critical or threshold approach assist as a check and balance. Moreover, DRIS is based on the classification of high yield versus low yield which by default has a logical subjectivity, which again revert to the risk of overlooking suboptimal condition prevailing in the high yielding category.
Mumtaz and Duane,
Your strategy will depend on your scale of operation and the purpose for collecting the information. You probably need to understand your site and your species independently and then how they interact.
If it's across large scale, I'd be thinking about the increasingly cost efficient options like multispectral or hyperspectral remote sensing (landscape), or at a decreasing scale, soil mapping (catchment), Electrical Conductivity mapping (paddock or farm). This soil information becomes your base resource information, then in parallel learn about your plant species grown under environment matched controlled conditions with a range of nutrient supplies to determine optimums.
Some of this information may have been collected previously, time spent researching the literature may assist at this point to drastically costs.
From here you build a basis for matching the plant species with the site. Then once planted into sites with adjusted/suitable base fertiliser dressings go to your plant analyses for uptake information which can be related back to see how close you are from optimums. Do this after a suitable establishment period (partially environment and crop dependent) and consider management implications.
regards
The crop nutrient equivalent (CNE) approach developed by Janssen (1998, 2011) can be used to estimate the level of nutritional balance.
You can find more details in this papers:
Janssen, B.H., 1998. Efficient use of nutrients: an art of balancing. Field Crops Research 56: 197–201.
Janssen, B.H., 2011b. Simple models and concepts as tools for the study of sustained soil productivity in long-term experiments. II. Crop nutrient equivalents, balanced supplies of available nutrients, and NPK triangles. Plant and Soil 339: 17–33. DOI: 10.1007/s11104-010-0590-0.
Excelentes discusiones sobre como medir la disponibilidad nutrimental para un rendimiento sostenido. ¿Pero que pasa con esa relación final de nutriente que se obtiene como demanda del cultivo en ese producto final, llámese fruto? o parte útil? ¿No es a caso la relación que debe tener una dosis de recomendación que debemos de aplicar a nuestro cultivo en cuestión?, considerando una eficiencia de uso particular para cada uno de ellos, o es que acaso nuestros métodos de análisis tradicionales no predicen la disponibilidad nutrimental en el sistema complejo suelo.
DRIS and other methods have methodological biases due to redundancy, scale dependency, sub-compositional incoherence, non-additivity and non-normal distribution of variables, leading to pathological behavior and conflicting diagnoses. The nutrient balance concept can be solved using the Egozcue et al. (2003) method for compositional data. Application to nutrient data has been successful.
Parent, S.- É., Parent, L. E. Rozane, D. E. Hernandes, A., Natale, W. (2012). “Nutrient balance as paradigm of plant and soil chemometrics” Chapter 4 in Soil Fertility, ed. Issaka, R.N., [NY: InTech Publ.], 83:114, http://www.intechopen.com/books/soil-fertility.
Parent, S.É., Parent, L.E., Rozane D.E. and Natale, W. 2013. Nutrient balance ionomics: case study with mango (Mangifera indica). Frontiers Plant Science 4, article 449.
Parent, L.E., Parent, S.-É., Hébert-Gentile, V., Naess, K., and Lapointe, L.. 2013. Mineral balance plasticity of cloudberry (Rubus chamaemorus) in Quebec-Labrador. Am. J. Plant Sci. 4(7):1508-1520.
Marchand, S., Parent, S.E., Deland, J.P., and Parent, L.E. 2013. Nutrient signature of Quebec (Canada) cranberry (Vaccinium macrocarpon Ait.). Rev. Bras. Frut. 35(1):1999-209.
Hernandes, A., and Parent, S.-É. , Natale, W., and Parent, L.E. 2012. Balancing guava nutrition with liming and fertilization. Rev. Bras. Frutic.. 34(4): 1224-1234.
Parent S-É, Parent LE, Egozcue JJ, Rozane D-E, Hernandes A, Lapointe L, Hébert-Gentile V, Naess K, Marchand S, Lafond J, Mattos D Jr, Barlow P and Natale W (2013) The plant ionome revisited by the nutrient balance concept. Front. Plant Sci. 4(39): 1-10. doi: 10.3389/fpls.2013.00039
Parent, L.E., Parent, S.É., Rozane, D.E., Amorim, D.A., Hernandes, A., Natale, W. 2012. Unbiased approach to diagnose the nutrient status of guava. Proc. 3rd Int. Symp. on Guava and Other Myrtaceae. ISHS 2012. Eds.: C.A.F. Santos et al. Acta Hort. 959:145-159.
Parent, L.E. 2011. Diagnosis of the nutrient compositional space of fruit crops. Revista Brasileira de Fruticultura 33:321-334.
Hi Mumtaz: Thanks also to you for inniating this interesting plant nutrition topic. Furthermore, this info is also interesting for readers followers of Q&A of Researc Gate.
Dear Ganie.
To my experience, there are no perfect method for diagnoing nutrient deficiency in crops. Actually, the use of several methods for a single case study should be the most appropriate approach. It must be anticipated that this would produce varying and maybe contradicting results, but even so, this is the way to take the best decisión on fertilizer application. For forest species I have successfully used DRIS.
Cheers!
Mumtaz, i got an interesting PDF , i thought , let me share with you , an excellent work...
Application of sequential statistical data-mining methods to determine
tissue nutrient concentrations related to yield of the ‘Hass’ avocado
Abstract : Plant tissue analysis completed sufficiently early in a growing season can identify nutritional problems in time to take corrective actions andsafeguard commercial yield of perennial fruit crops. Leaf analysis is an established method for precision agriculture, however, with reference to ‘Hass’ avocado, leaf analysis may not provide adequate guidance for optimal yield, fruit size or fruit quality during the current or following season. For these reasons tissues other than leaves were collected and analyzed. The objective was to estimate the strength of the associations between yield and concentrations of N, P, K, S, Ca, Mg, Fe, B, Zn, Mn and Cu in the following tissues: cauliflower and full bloom stage inflorescences collected in March and April, respectively; pedicels collected monthly from fruit set through harvest; and spring flush leavescollected in September (industry standard). Samples were collected from six commercial ‘Hass’ avocado orchards located in the northern and southern production areas of California for two consecutive crops. Sequential analysis of the data by statistical methods that included least squares multiple linear regression, principal component analysis and factor analysis provided evidence that cauliflower stage inflorescences may provide the best predictive and descriptive models for expected yield. Within this tissue, yield was significantly related to the concentrations of Mg, Cu, K, S and N (R = 0.7075; P = 0.0002). Envelope analysis was used to estimate the concentration ranges of each nutrient (% dry mass) in cauliflower stage inflorescences related to yields > 40 kg/tree: 0.18 < Mg < 0.27; 0.76 x 10-3 < Cu < 2.15 x 10-3; 1.70 < K < 2.15; 0.25 < S
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