Biostimulant data: What crop categories and trials are used?

EBIC suggestions on underlying principles to justify a biostimulant claim:
Crop categories and Number of Trials

Six groups of crops have been identified for confirming biostimulant efficacy:

The number of trials required for a product depends on the crop range to which the claim is being made

 

Trials must be conducted by qualified personnel who will record, document, and archive the trial study plan, the results, the final report and all the supporting raw data. 

Data from GEP/GLP-certified facilities can be considered credible, even if they belong to the manufacturer. Nonetheless, it is desirable that manufacturers can demonstrate that at least some of the research was conducted with impartial and competent third parties. 

As much as possible, trials to support product claims should be conducted with an independent and competent partner, such as one of the following: 

  • National research agencies and extension officers; 
  • Institutes (including but not limited to universities and other institutes of higher learning and private research stations) 
  • Researchers with published research in agriculture and agronomy, and
  • Certified private research centres (GLP/GEP or GLP/GEP equivalent conditions). 

Trial conditions

The relevant conditions of the plot and crop should be adequately described, for example: 

  • For an annual crop, sowing or planting date and density, row spacing; 
  • For a perennial crop, arrangement and spacing in rows or as single plants, pruning or training system, rootstock, canopy height, plant width, age, whether in production; 
  • For a glasshouse crop, arrangement within compartments, on benches, in soil-less culture, etc.; 
  • The cultivation practices of the crop could be described, such as tillage, fertilizer and irrigation regimes, and any other additional inputs; 
  • Information should be given on whether the crop was growing normally or was under stress at the time(s) of treatment [e.g., drought, frost, wind or effects of other overall chemical treatments, and/or effects of other pests (including diseases and weeds)]; 
  • For a soil-applied product, the temperatures at the root zone level in topsoil should be recorded during at least the first month of the trial at 2-h intervals), and 
  • Soil characteristics should be described, i.e. pH, the percentage of sand, clay, silt, organic matter 

Design and lay-out of trials 

  • The design and lay-out of the plots should be described, preferably with a plan, the number, size and shape of plots, whether defined by plot dimensions on the ground or a certain lay-out of plants.
  • The type of experimental design should be indicated. 
  • The arrangements made for the untreated control (included, imbricated, and excluded) should be precisely indicated, together with details on any other control treatments. 
  • Completely randomized blocks should be assured, while maintaining a scientific design that avoids any interference of experimental conditions between plots (for example, with regards to drought stress mitigation trials, the well-watered condition will have to be set up as a band reference beside the trial. 
  • Enough replicates should be assured to obtain 12 degrees of freedom in the trial, so that a consistent difference between treated and untreated crops can be demonstrated. 

Control data 

The control data set can be from a completely untreated plot or an “omission” plot i.e., the treatment regimen is the same with the exception of the biostimulant, which is absent from the “omission” plot. 

Where possible, control groups selected for an improved nutrient uptake claim should include: 

  • Untreated 
  • The following additional control groups, when a biostimulant is included in a “support” nutrient-containing formulation: 

1. the support formulation alone, if the support provides nutrient elements; 

2. the biostimulant formulation alone (without the nutrient elements). 

  • Abiotic stress resistance claims should include the following control groups: 

1. stress condition object(s); 

2. no-stress condition object(s); 

There should be some attempt to characterize the applied stress level. 

Application of treatments

Information should be provided on the formulation, application method, concentration and amounts of the test product as well as climatic and soil data. 

Mode of application: 

The information provided should be sufficient to establish that good agricultural practice is being followed, for example: 

  • The application method and equipment used 
  • Any significant deviations from the intended dosage 
  • The operating conditions, insofar as they may affect claims (e.g., for sprays, pressure, nozzle type, spray quality and speed of travel of sprayer) 
  • The number of applications 
  • The date of each application (including year, preferably by dd-mm-yyyy) 
  • The growth stage of the crop at the time of each application 
  • The doses used (cc-g/hL or L-Kg/ha), and the spray volumes (L/ha). 

Mode of assessment:

  • Type, time and frequency of assessment 
  • The type and date of each assessment 
  • The methods used should be described. Any assessment scales used should be specified. 
  • Direct effects on the crop. The presence or absence of phytotoxic effects should be noted for each plot, with an accurate description of any symptoms, for example: modifications in the development cycle, thinning, modifications in colour, necrosis, deformations, effects on the quantity and quality of the yield. 
  • Yield and quality should, when specified, be recorded, taking careful note of the specific parameters required in each crop. 

The trial series report 

The trial report should include: 

  • The aim of the trial series 
  • The list of test and reference products, with doses and application times of frequencies 
  • The assessment methods 
  • Results including statistical analysis if any were conducted. 

How biostimulants can help solve the fertiliser problem

We’ve previously shared with you our insight on the effect of biostimulants on plants in the context of the global over usage of fertilisers.

We’ve looked at the need for biostimulants as a way to enable plants to better use the nutrients available to them,  therefore allowing producers to use less fertilisersthe effect of biostimulants on plant rootshow they can reduce nitrogen requirement, and most recently  their influence on soil structure and the microbial activity in soil.

In this final article we round up our conclusions on the effect and opportunity of biostimulants to help reduce global fertiliser consumption. And share the insights we’ve evidenced using Maxstim biostimulants in trials.

Can plant biostimulants improve microbial activity in soil?

There are a number of strategies where biostimulants can help the fertiliser problem.

Our previous articles gave insight to the fertiliser problem we are facing globally and demonstrated the nitrogen cycle. We introduced the need for biostimulants as a way to enable plants to better use the nutrients available to them, therefore allowing producers to use less fertilisers , the effect of biostimulants on plant roots and how they can reduce the nitrogen requirement.

Can plant biostimulants improve soil structure?

There are a number of strategies where biostimulants can help the fertiliser problem.

Our previous articles gave insight to the fertiliser problem we are facing globally and demonstrated the nitrogen cycle. We introduced the need for biostimulants as a way to enable plants to better use the nutrients available to them, therefore allowing producers to use less fertilisers , the effect of biostimulants on plant roots and how they can reduce the nitrogen requirement.

Can plant biostimulants promote nitrogen reduction?

There are a number of strategies where biostimulants can help the fertiliser problem
Our previous articles gave insight to the fertiliser problem we are facing globally and demonstrated the nitrogen cycle. We introduced the need for biostimulants as a way to enable plants to better use the nutrients available to them, therefore allowing producers to use less fertilisers and also the effect of biostimulants on plant roots.

The influence of biostimulants on plant roots

There are a number of strategies whereby biostimulants can help the fertiliser problem.

Our previous article gave some insight to the fertiliser problem we are facing globally and demonstrated significance of the nitrogen cycle. We introduced the value of biostimulants as a way to enable plants to better use the nutrients available to them, therefore allowing producers to use less fertilisers. Read it here.

So what are the specific strategies where biostimulants can make a difference?

The following article shares insight specifically on the influence of biostimulants on plant roots.

Improve plant nutrient (especially nitrogen and phosphorous) uptake by altering plant morphological characteristics (Halpern et al., 2015) e.g. Changes to root parameters (e.g. structure and morphology – we have evidence that Maxstim formulations can achieve this)

Plants can respond to the application or availability of biostimulants by changing their root growth. Changes in root architecture and surface area can enable plants to explore a larger volume of soil and capture nutrients more effectively. Consequently, soil containing a lower level of nutrient can deliver the same amount of nutrient to the crop if the plant roots are growing through and accessing a larger soil volume.

Imagine being able to have 20% more crop for the same amount, or less, of fertiliser.

Root morphology: It is known that root morphology is important for acquiring nutrients with low mobility in the soil (Nye & Tinker 1977). However, for more mobile nutrients, e.g. NO3 – and NH4 +, root morphology is often considered of lesser importance. Forde and Lea (2007) reported a significant effect of the amino acid glutamate, even at very low concentrations, in changing root architecture by inhibiting primary root growth and increasing root branching near the root apex. The increase in root branching induced by glutamate application can enhance the density of the root system improving the plant’s ability to explore the soil volume and to uptake nutrients and water.

Biostimulant effects of protein hydrolysates (which contain amino acids) can also result from changes in the microbial community of the rhizosphere. For example, Luziatelli et al. (2016) in a lettuce trial reported that the application of a plant derived- protein hydrolysates increased the population of bacterial species producing the auxin, 3-indoleacetic acid, and other auxin-like compounds. Changes in plant growth are often due to the presence of bioactive peptides inducing hormone-like activities e.g. auxin, gibberellins, and brassinosteroids, which involve complex interactions among phytohormones (Colla et al., 2015; Kim et al., 2019).

Root to shoot ratio: One way for a plant to access more nutrients is to develop a larger root system. However, this strategy comes at a cost. Larger root systems may divert more carbon away from the shoots, limiting photosynthesis and a crop’s capacity to fix and store carbon in the harvested yield. Some studies indicate that the relationship between root size and yield at low N is not clear and may be negative (Gallais & Coque 2005), so developing larger roots may be a sub-optimal strategy for some crop plants. With high levels of nutrition, root to shoot ratios are generally lower   and under these conditions, parameters such as pH and temperature may be more important for N uptake than root morphology. The root to shoot ratio also changes as the plant develops, with the general trend (at least with herbaceous plants) being towards a relatively smaller root system as the plant ages, independent of nutrient level.

Root length density: Root length density is the root length per volume of soil. Greater root length density (e.g. greater numbers of smaller diameter, as opposed to fewer large, roots) can improve nutrient acquisition by increasing the root surface area without requiring an increase in carbon allocation to the root (Marschner 1995). Accordingly, it has been suggested that increasing root length density may improve N acquisition in some crops.

The image below shows the effects of Maxstim’s complex biostimulants on rye grass root – untreated vs treated.
Image showing Maxstim biostimulant effect on rye grass root

 

Root vigour: Simply having a larger root to shoot ratio over the plant’s lifespan may not always be useful for increasing Nitrogen usage efficiency in some agricultural situations but the ability to develop a large root system early would seem to be of some benefit in certain conditions. Liao et al. (2004, 2006) found that, in sandy soils with high leaching potential, the ability of plants to rapidly explore soil and capture available NO3 – was important for optimising nitrogen uptake from the soil. These plants did not have a higher root to shoot ratio at final harvest, but their root development was more rapid than in less vigorously rooted plants.

Root proliferation in response to Nitrogen: While root growth relative to shoot growth is generally reduced when soil N levels are high, it is known that roots will proliferate in response to localized patches of high N (Drew et al., 1973; Drew, 1975; Drew & Saker, 1975; Laine et al., 1995). This would appear to be an evolutionary adaptation so that root allocation is not wasted in areas of the soil containing little N.

Deep roots v shallow roots: Deeper roots clearly have the potential to access more water and nutrient than shallow roots but root length densities are generally lower deeper in the soil profile (Barraclough 1986; Wiesler & Horst 1993, 1994). In porous soils where surface applied N is rapidly distributed deep within the soil horizon, plants which can develop a greater root mass further down the length of the root system would have an advantage in enhancing N uptake and reducing N leaching losses from the soil.

Root hairs: Root hairs can contribute 70–80% of the total root surface area and therefore play a critical role in nutrient uptake.  These structures are important in increasing the surface area of roots through a larger effective root diameter with a relatively low investment in dry matter and allocated Carbon. It has been demonstrated that root hair number and density increase in response to nutrient stress. Exogenous application of amino acid has also been shown to have an effect on root morphology. Specifically, L-glutamate application to the root, inhibited primary-root growth and stimulated root branching (Walch-Lui et al., 2006). It also stimulated root-hair development close to the root tip (Walch-Lui et al., 2006). This effect was specific to L-glutamate, and did not occur in response to applications of 21 other amino acids, including D-glutamate.

Look out for our future posts part 3-6 on the Fertiliser Problem to follow in the coming weeks. If you want to make sure you get to read our insight first do sign up here.

The search for naturally occurring highly active biostimulants

At the heart of Maxstim is a passion to drive research, development and innovation towards a more sustainable way to practice agriculture, horticulture and turf management. Over recent years our CEO Richard Salvage has been on a mission to continue to improve the effectiveness of the complex biostimulants we manufacture. Having clearly identified that bioflavonoids and polyphenols are important bioactive components, he has now created a unique range of highly effective biostimulants. Alongside this, Maxstim has honed specific production techniques which increase, optimise and harness the abundance of these bioactive compounds. These are being patent protected and have been named AmphenoxTM.

This exciting development heralds a new era of biostimulants. We can demonstrate that AmphenoxTM is rich in secondary metabolites and highly active bioflavonoids which enable plants to turbocharge their immune systems and stimulate essential biochemical metabolic processes influencing key functions such as growth, chlorophyll production, root development and stress management.

In the technical paper we have released we share detailed insight in to how we have evaluated AmphenoxTM, the results and our methodology for creating some of our products.

What data is required to show biostimulants are effective?

Type of information that can support a claim

Various types of data and empirical evidence can support a claim justification. While not strictly speaking hierarchical, it makes sense to begin with published peer reviewed scientific literature and existing data and then to complement that information as needed with new experimental data from controlled conditions and field trials 

Data generated under controlled conditions (glasshouse, growth chambers, phenotyping, etc.) from outside the European Union should be admissible if the climatic conditions tested could conceivably apply within the EU and: 

  • if it is from a manufacturer’s own GEP/GLP-certified facilities. 
  • if the independent research partner (contract facility, university, etc.) that generated the data is considered reputable, or 
  • if the manufacturer can otherwise demonstrate that the quality of the methodology and the data obtained are substantially equivalent to what would be achieved by a GEP/GLP facility. 

Use of Published Literature and Existing Data

Peer-reviewed scientific literature can support a claim.

Literature can be used to describe the mode of action of the product, the biology of the microorganisms used, or any preliminary studies described in relevant published papers supporting the basis of the proposed claim.

Scientific literature can be used to support a claim if it is of acceptable quality, (e.g. as per the criteria outlined in Klimisch et al. (1997). At the same time, the synergistic or emergent effects that result from the combination of substances within a product mean that it is unlikely literature alone will be enough to fully justify a claim.

Experimental Data

Biostimulant claims can be supported by experimental data generated under controlled conditions (laboratory, greenhouse, growth chamber, phenotyping, etc.) and/or in the field (field trials).

Additional data from small-scale laboratory and growth chamber studies will often form a vital component of the overall claim justification package provided.

If field data are used, at least some EU data should be included.

Field data from outside the EU may support EU data if both are generated under similar geo-climatic conditions (and those correspond to the intended context for product use). Guidelines exist for determining the comparability of geo-climatic conditions (European and Mediterranean Plant Protection Organization [EPPO], 2014).

The importance of data in assessing the efficacy of biostimulants

Background: As the need for biostimulants becomes better understood and their place in the armoury of agronomists more established, creating a credible means of generating and assessing their use and efficacy becomes more important. Maxstim Ltd is a leader in biostimulant design and manufacture and understands the need to demonstrate the integrity and quality of the supporting data that underpins the performance of our products. 

This document describes in detail how our product development and technical team carry out the assessment of product performance and how the efficacy data is generated and assessed for quality and reporting. At the same time recognising that having solid data on product effects is irrelevant if it makes no contribution to real farmer/grower value. 

Maxstim procedures for supporting biostimulant claims 

In order to enable access to the European Union single market, CE marking is required for all fertilising products (the definition of which now includes biostimulants). 

This is covered by Regulation (EU) 2019/1009 FPR published in July 2019 and which will be fully operational in July 2022. 

The European Biostimulant Industry Council (EBIC) have developed some guidance to follow when justifying plant biostimulant claims. These principles are expected to be incorporated into harmonized European standards currently being developed by the European Committee for Standardization (CEN) to support the implementation of the regulation (Ricci et al., 2019; General principles to justify plant biostimulant claims. Frontiers in Plant Science Volume 10, article 494). 

Maxstim has adopted these procedures for evidencing biostimulant claims. These are based on the EU definition of biostimulants: 

An EU fertilising product the function of which is to stimulate plant nutrition processes independently of the product’s nutrient content with the sole aim of improving one or more of the following characteristics of the plant or the plant rhizosphere:
(a) nutrient use efficiency
(b) tolerance to abiotic stress
(c) quality traits
(d) availability of confined nutrients in the soil or rhizosphere
(e) yield improvement (yield increase or yield security) 

Note that the effects of biotic stress cannot be entirely separated from abiotic stress. Consequently, reducing abiotic stress can have an indirect effect on the impact of pests and diseases on crop plants. 

Plant Biostimulants “shall have effects that are claimed on the label” 

  • A conformity assessment dossier will be compiled for Maxstim products and include evidence of the product’s effects 
  • Harmonized European Standards will indicate what constitutes compelling evidence 

Underlying Principles to Justify a Biostimulant Claim: Data 

  • Existing data (pre Regulation 2019/1009 FPR) can be used 
  • Existing data sets and new data should comply with acceptable Experimental Quality Criteria (this can be generated by the manufacturer, independent researchers, distributors or growers) 
  • Data should have agronomic relevance (i.e. yield improvement, must demonstrate a biologically relevant agronomic trend) 

Data should be of sufficient quality to support any claim: 

To assess data quality a Klimisch score (Klimisch et al., 1997) can be used to evaluate data robustness. Scores of 1 and 2 are acceptable, though data with scores of 3 and 4 can be used as part of a wider assessment e.g. supporting observations of consistent “agronomically” positive data trends (i.e., not necessarily statistically significant) compared to untreated plots in field trials.