GUIDELINE FOR SOIL BIOLOGY DATA COLLECTION IN ETHIOPIA: NATIONAL STANDARD Ethiopian Institute of Agricultural Research (EIAR) EIAR’s mission is to conduct research that will provide market competitive agricultural technologies that will contribute to increased agricultural productivity and nutrition quality, sustainable food security, economic development, and conservation of the integrity of natural resources and the environment. www.eiar.gov.et Citation: Mnalku A; Demissie N; Assefa F; Tamene L. 2020. Guideline for soil biology data collection in Ethiopia: National Standard. Ethiopian Institute of Agricultural Research (EIAR). Addis Ababa, Ethiopia. 29 p. This document has been peer-reviewed by Dr. Endalkachew Woldemeskel. Cover photo: EIAR/Abere Mnalku Design and layout: Communications team, Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT). Content contributors: Task force members of the Coalition of the Willing (CoW). Some Rights Reserved. This work is licensed under a Creative Commons Attribution NonCommercial 4.0 International License (CC-BY-NC) https://creativecommons.org/licenses/by-nc/4.0/ © Copyright EIAR 2020. Some rights reserved. September 2020 PO Box 2003 Addis Ababa, Ethiopia Tel. (+251) 116 454452 GUIDELINE FOR SOIL BIOLOGY DATA COLLECTION IN ETHIOPIA: NATIONAL STANDARD Abere Mnalku,1 Negash Demissie,1 Fassil Assefa,2 and Lulseged Tamene3 1 Ethiopian Institute of Agricultural Research (EIAR) 2 Addis Ababa University 3 Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) Acknowledgements We wish to acknowledge the technical and financial support from the International Center for Tropical Agriculture (CIAT) (now part of the Alliance of Bioversity International and CIAT) and the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Ethiopia. The technical and institutional support from the Ethiopian Institute of Agricultural Research (EIAR), particularly that of Dr. Temesgen Desalegn, is also highly valued. We also appreciate the engagement and contributions of the members of the Coalition of the Willing (CoW) in the effort to support agricultural transformation through digital solutions. Prof. Mitiku Haile has played a very important role by providing technical support and coordinating the key moments of the process. Photo: CIAT/G. Smith Photo: Neil Palmer Contents Preface ..............................................................................................................................................................vi Rationale .........................................................................................................................................................vii Introduction .................................................................................................................................................................2 Rhizobia ...................................................................................................................................................................... 3 Nodule and soil sampling .................................................................................................................................... 3 Isolation and identification of rhizobia from natural habitats ........................................................................ 3 Characterization of rhizobial specimens ........................................................................................................... 3 Counting rhizobia .................................................................................................................................................. 4 Performance evaluation of rhizobial specimens ............................................................................................... 4 Greenhouse experiments ........................................................................................................................................... 5 Field (on station or on-farm) evaluations .............................................................................................................. 7 Mycorrhizae .............................................................................................................................................................. 9 Collection of mycorrhizae .................................................................................................................................... 9 Characterization of mycorrhizal specimens ..................................................................................................... 9 Performance evaluation of mycorrhizal specimens ......................................................................................... 9 Plant growth-promoting microbes .....................................................................................................................10 Collection of PGPMs .......................................................................................................................................... 10 Characterization of PGPM specimens .............................................................................................................10 Performance evaluation of PGPM specimens in greenhouse/field ..............................................................11 Earthworms and vermicompost .........................................................................................................................11 Collection of earthworms ................................................................................................................................. 12 Characterization ..................................................................................................................................................12 Bio-indicators of soil quality and sustainable use ...........................................................................................18 References .....................................................................................................................................................................19 Appendices ....................................................................................................................................................................21 Preface Recently, recognition has been growing of the power of data and information for better decision- making and service provision in agriculture. To ensure good data quality, an agreed standard to collect, store, and share data along the agricultural value chain is required. With this background, the purpose of this guideline is to provide guidance on standardizing soil biology data collection and thereby enhance temporal and spatial data interoperability. Standard field research design, data collection, and data reporting are required for well-informed meta-analyses and syntheses of agricultural research data as well as for making these data more accessible for calibration and evaluation of process-based models. Hence, this guideline is a contribution toward enabling meta-analysis of different data collected over years and/or space to accumulate evidence and generate new knowledge or insights to facilitate informed decision-making in the agricultural sector in general and in the crop development subsector. This guideline is compiled and intended for use by researchers, academicians, students, and other interested professionals in Ethiopia and beyond. The guideline is developed based on accepted standards and procedures in the field. Nevertheless, it is not exhaustive in its coverage of the soil biology data types and crops grown in the country. Hence, additions and updates depending on the development of research facilities, the ever-changing focus of agricultural research and production systems, and advances in technology are warranted. vi Rationale Aggregates of data are sources of technology, innovation, information, and knowledge. In addition, the generation of such data through a series of research activities and their documentation in a well-organized and usable way is the most important aspect of research and development. With the advent of agricultural research in Ethiopia, a wealth of soil biology datasets has started to be collected and will expand in extent with time. Integration of these data enables new scientific discoveries, facilitates informed decision- making, and can transform the agricultural sector. Nevertheless, integration of data has been difficult because of the lack of uniformity in approaches and standards in data collection and measurement. Most data collected so far are held by individual researchers and only a few are published in journals and proceedings. Many projects in the past several decades have generated data that are not accessible for data synthesis and model testing. Limited accessibility and non-interoperability of these datasets and poor infrastructure development have limited wider use of the data. Ensuring the sustainability of agricultural systems has become increasingly complex and requires a coordinated, multifaceted approach in developing new knowledge and understanding. The collection of soil biology data using predetermined standards facilitates interoperability and integration and allows extended use of the data (Eagle et al., 2017; Kladivko et al., 2014). Hence, this guideline aims to set a standard in the collection of minimum datasets in research and development in soil biology. The purpose and scope of this guideline are, therefore, limited to setting a standard for the collection of data and a minimum dataset on soil biology-related data for Ethiopia. It is assumed that detailed manuals for data collection and templates will be developed following the guideline. Photo: Georgina Smith vii Photo: Abera Mnalku Introduction The soil biota profile contains an enormous of data sharing and metadata analysis that would species diversity (more than 15,000 different ultimately help organize national information for species per gram of soil) that plays a major role development and policy making as a subsector. in nutrient recycling and ecosystem functioning This document contains the most important and servicing. The scope of this work, however, parameters and information recorded in is limited to bacteria, fungi, and earthworms laboratories, greenhouses, and fields across as they encompass the dominant soil-related the different soil biota groups such as rhizobia, services such as soil structure improvement mycorrhizae, plant growth-promoting microbes (e.g., earthworms), nutrient supply regulation (PGPMs), and earthworms from assessment (e.g., diazotrophs, phosphate solubilizers, and (landscape) to designed (plot/farm) level research mycorrhizae), litter transformation (e.g., micro- and monitoring scales. Moreover, the document arthropods), and biocontrol (e.g., Trichoderma, attempts to include the minimum parameters Beauveria, etc.). For many years, a lot of scientific to be considered during the estimation of bio- efforts have been made to manipulate soil biota indicators of soil health and fertility at the farm or to fully realize the benefits for development and landscape level. As to the datasets, the following environmental protection globally and locally. considerations are taken into account: The hitherto data collection, measurement, and reporting approaches regarding soil biology are, • GIS, soil and plant tissue testing, and some however, inconsistent, without using state-of-the- agronomy-related datasets are scarcely art methods, and are key challenges in Ethiopia. touched and details can be obtained from These challenges often constrain the deployment data standardization documents for Cross- 2 Data Management Standardization Guideline on Soil Biology cutting; Soil, Water, and Plant Testing; and or landraces, (2) plant infection technique in Agronomy themes, respectively, prepared growth pouches, or (3) growing plants in pots that in parallel sections. contain soils with native rhizobia (Howieson and • It is assumed that detailed dataset collection Dilworth, 2016; Mnalku et al., 2019). The simplified manuals and templates will be prepared as initial steps include the following: a follow-up to the guideline. • Mapping of potential collection sites • This guideline contains datasets that can and crops. be measured in our capacities/facilities • Collecting and preserving nodules. currently. Revisions can be made when • Measuring soil total N, organic matter more facilities or capacities are accessible. (%), pH, and available P (ppm) (refer to The objective of this work is therefore to develop the Soil, Water, and Plant Testing Data a standard for data collection protocols/guidelines Standardization Guideline, 2020). for minimum datasets. Rhizobia Biological nitrogen fixation (BNF) is a process by which molecular nitrogen in the air is converted into ammonia (NH3) or related nitrogenous compounds biologically. BNF is a viable option that can enhance crop yield sustainably, among several different types of biofertilizers that are known to affect plant growth and development. The most commonly mentioned microbes used as biofertilizers include nitrogen fixers, phosphate solubilizers, growth promotors, and decomposers. Rhizobia is a collective name for symbiotic bacteria capable of invading and forming roots or stem nodules on leguminous plants to convert atmospheric nitrogen (N2) into ammonia (NH3) in plant roots. Rhizobial biofertilizers are the most highly exploited across the globe, and their use and importance are expanding in Ethiopia. Legume- Photo: Abere Mnalku rhizobia symbiosis plays an important role in sustainable agriculture. This technology can deliver enormous benefits through the judicious Isolation and authentication of rhizobia use of fertilizer, for example, phosphorus, and Rhizobia are isolated from root nodules following the exploitation of genetic diversity and symbiotic the updated procedures of Howieson and Dilworth effectiveness of the hosts (leguminous plants) and (2016). Desiccated nodules must be rehydrated their corresponding endosymbionts (rhizobia). before isolation. The authenticity of a pure culture To tap the potential benefits from rhizobia-legume of rhizobia must be proven by inoculation to a symbiosis, it is essential to follow sequential steps, compatible legume. Isolates that do not form which go from nodule collection, isolation of nodules are not considered rhizobia and are rhizobia, and authentication to field evaluation therefore discarded in the next steps. Under the of pure strains for N-fixing effectiveness authentication process, the legumes are assessed (Appendix Figure 1). for only nodules. Nodule collection and soil sampling Characterization of rhizobial specimens Nodules can be collected from the targeted Isolates should pass through routine checks for legumes through (1) bio-prospecting wild relatives diagnostic features on various culture media Data Management Standardization Guideline on Soil Biology 3 (Howieson and Dilworth, 2016; Mnalku et al., 2019). These checks involve the following: • Cultural characteristics: colony diameter (mm) and colony texture (nominal) • G rowth characteristics (growth rate, acid base production) • Physiological characteristics (salt, acid, pH, etc.) with +/- for presence and absence of colony growth • Substrate use (carbon, nitrogen, etc.) • Agrochemical tolerance of rhizobia: growth inhibition effect (%I) is computed as: or Counting rhizobia Rhizobia are counted essentially to assess rhizobial populations in soil and how they vary, to follow the growth of cultures in the laboratory, or to assess the number and viability of rhizobia in commercial inoculants for quality control (Howieson and Dilworth, 2016). The population size of rhizobia in the soil guides the need for inoculation of the soil. The number of rhizobia in the soil is dynamic and varies within and between seasons, so any enumeration must be placed in context. The process involves the following: • Serial dilution (up to 10-6) • P late counts of rhizobia in sterile diluent • Indirect counts by plant infection to estimate most probable number of rhizobia • Estimate of cell number by optical density (540 nm) • D irect counts under a microscope Performance evaluation of rhizobial specimens The authenticated isolates are screened for their effectiveness in fixing nitrogen in relation to standard strains (reference strains), first in the greenhouse (in pot-sterile inert material and non-sterile soil) and then under field experiments in plots (on-farm). The experiments should include + and - nitrogen controls (Howieson and Dilworth, 2016). Photo: Georgina Smith 4 Data Management Standardization Guideline on Soil Biology Photo: Georgina Smith Greenhouse experiments The nitrogen controls are supplied with 0.5 g L-1 KNO3 harvested and evaluated for nodulation (nodule during the growth period of the plants and grown number and nodule dry weight), shoot dry weight, for at least 35 days, after which the plants will be and other parameters, as follows. Parameters Units References Remarks Vigor rating: 0 = dead; 1 = seedling growth only; 2 = 2 to 3 leaflets with Vigor rating Unitless Friedericks et al. (1990) yellowing; 3 = 2 to 3 green leaflets; 4 = 3 to 4 leaflets and 1 to 2 primary leaves; 5 = > 4 leaflets and primary leaves with no yellowing. Nodule count -1 (active and non-active) no. plant Pink are active whereas white, green, and brown are non-active. Nodule dry weight mg plant -1 Dry for at least 2 hours at 65 °C or air-dry for 1-2 days. Nodule volume cm3 Measured by water displacement method. Nodule position Nominal (main root, lateral roots, root hairs). R = (a*10)+(b*5)+(c*1)+(d*0)Total number of plants uprooted Nodulation rating % Nif Tal (1979) where a = taproot, b = close to taproot, c = scattered nodules, and d = without nodulation. Shoot total N per plant % Modified Kjeldhal (1954) Seed N mg g -1 Data Management Standardization Guideline on Soil Biology 5 Parameters Units References Remarks N derived from air % Howieson and Dilworth (2016) N difference method. Crude protein % Common for forage legumes. Root dry weight g plant-1 Shoot dry weight g plant-1 Root-to-shoot ratio Unitless Dividing root dry weight by shoot dry weight. Symbiotic effectiveness % Beck et al. (1993) Proportion of inoculated dry mass to N-fertilized treatment. Plant height cm Dry biomass yield kg ha-1 Dried at 80 °C in oven for 2 days Seed yield kg ha-1 Moisture is adjusted to 14% Isolates are classified into highly effective, effective, and ineffective (Equation 1 or 2 below) and those with superior growth to or the same growth as the standard strain or the nitrogen controls are selected for the field work. The top-performing isolates are selected for further nitrogen-fixing potential. DWt of inoculated - DWt of uninoculated control * 100 DWt of Nitrogen control - DWt of uninoculated control or DWt of inoculated - DWt of uninoculated control * 100 DWt of standard strain - DWt of uninoculated control Where DWt is oven- dry weight biomass Photo: Abere Mnalku 6 Data Management Standardization Guideline on Soil Biology Photo: Abere Mnalku Field (on-station or on-farm) evaluations A few selected isolates, often the two top-performing Pre-planting information ones, will be evaluated in the field in the presence The following information is important: of reference strains and nitrogen (+ and -) control treatments following an appropriate field layout • Geographic coordinates (in decimal degrees) (Appendix Figure 2). The treatments are the isolates • T opographic information (slope, aspect, (with 106 to 109 cells, the maximum number of steepness, etc.) rhizobia cells that can be added to achieve optimal yield); the nitrogen control (100 - 120 kg N ha-1), • Farm-gate price of labor and inputs measuring the yield of the legume when nitrogen • Land-use/cropping history is not limiting; the uninoculated control, measuring • Climate history the potential of soil nitrogen and native rhizobia; and a standard strain. Nodulation, shoot biomass, • Most probable number (CFU per g of soil) biological nitrogen fixation, and grain yield are (Woomer, 1994; Howieson and Dilworth, 2016) among the data that are recorded. When possible, • I mportant soil physicochemical characteristics it is best to measure the amount of nitrogen fixed such as organic matter, pH, Total N, using the natural abundance method. However, Exchangable acidity, available and total other methods such as nitrogen difference are also P, textural class, micronutrients, EC, etc. possible (Howieson and Dilworth, 2016). (appropriate methodology can be referred from to the Soil, Water, and Plant Testing Data Standardization Guideline, 2020). Data Management Standardization Guideline on Soil Biology 7 Post-planting data required The following data are required on post-planting. Parameters Units Nodule count nodule number plant -1 Nodule dry weight mg plant -1 Nodule volume cm3 Nodule position Nominal (main root; lateral roots; root hairs) Nodulation rating % Total N in plant % Nitrogen derived from the air % Root dry weight g plant -1 Shoot dry weight g plant -1 Root-to-shoot ratio Unitless Seedling vigor Refer to Section 4.2.3 Plant height cm Biomass yield kg ha-1 Grain yield kg ha-1, at seed moisture adjusted to 14% Farm-gate price of outputs and inputs (inoculant, labor, fertilizer, straw, seed, etc.) USD Weather information in the growing season mm, min, and max oT, daily or monthly total rainfall (mm) P-use efficiency % (can be adapted from Agronomy Data Standardization Guideline, 2020) N-use efficiency % (can be adapted from Agronomy Data Standardization Guideline, 2020) Nodule Collection Field Evaluation Isolation Sequential Data Collection Authentication Illustration 1: Sequential data collection activities of plant growth promoting rhizobacteria. 8 Data Management Standardization Guideline on Soil Biology Mycorrhizae Characterization of mycorrhizal specimens Arbuscular mycorrhizal fungi (AMF) are one of the mycorrhizal groups that colonize roots of more The following steps are involved (Schenck and than 80% of higher plants, particularly in the Perez, 1991; INVAM, 2019): tropics (Smith and Read, 2008). In relation to soil, • S pore count (no. 100 g-1 dry soil) mycorrhizal symbiosis enhances the formation and stability of soil aggregates via a complex • Spore size (mm) glycoprotein (glomalin) (Wright and Upadhyaya, • S pore ornamentation/color (qualitative) 1998) and uptake of N, P, and water ( Jakobsen, • S pore wall structure 1999). Though growing AMF on growth medium was a great challenge and difficulty, its inoculum • H yphal attachment of spores (presence or has been produced for use in agroforestry, absence of stalk) horticulture, landscape restoration, and site • R oot colonization of mycorrhizae remediation for almost two decades. (mycorrhization) (%) is measured following The manipulation of these organisms thus starts Wang and Jiang (2015) method: Percent from acquisition from their natural habitat as colonization = (Total number of infected indicated below. roots intersecting gridlines/total number of Collection of mycorrhizae roots intersecting gridlines) × 100 The following steps are involved (Schenck and Perez, Performance evaluation of mycorrhizal 1990; INVAM, 2019): specimens • Soil will be collected from the rhizosphere of Estimation of AMF colonization (%) is carried out by the plant cleaning with 10% KOH and clearing with 2% HCl and then staining with trypan blue. The gridline • Spores will be extracted from the soil intersection method will be used (INVAM, 2019): • Trap culture will be used to obtain • Plant tissue total P (%) monospecific culture • S eedling establishment (%) • Quantification will be done via a dissecting microscope • P -use efficiency (refer to Section 1.5.2) • I dentification is based on spore morphology • N-use efficiency (refer to Section 1.5.2) • Plant height (cm) 1. Sampling 6. Field trials 2. Isolation 7. Potential biocontrol endophytes 5. Inplanta screening under controlled conditions 3. Identification 4. Colonization efficiency and mass inoculum production Illustration 2: Mycorrhizal development (Adapted from Cambridge university press, 2019) Data Management Standardization Guideline on Soil Biology 9 Plant growth-promoting microbes through various forms of antagonism such as competition and the production of antibiotics, lytic Plant growth-promoting microorganisms (PGPMs) enzymes, and hydrogen cyanide. Nowadays, these are microorganisms that colonize the surface and microorganisms are selected and commercialized inner tissues of roots and promote plant growth as bio-stimulants and bio-pesticides with and health (Drogue et al., 2012; Sharma et al., different trademarks for the production of many 2013). Since almost 90% of these microorganisms horticultural and forest products and expected to are bacteria, they are often called plant growth have a market share of more than USD 5.83 billion rhizobacteria (PGPR). PGPR that enter and colonize by 2023 (Timmusk et al., 2017). interior plant tissues are known as endophytes. More than 30 bacterial genera have been Collection of PGPMs recorded so far as PGPR, the most dominant ones Their collection involves the following: being Pseudomonas, Bacillus, Azotobacter, and • Collection of soil sample Rhizobium (Antoun and Prévost, 2005). • I solation of microbes in the laboratory PGPR have many biochemical properties to stimulate plant growth (Glick, 2012). The most • Identification of microbes important direct or indirect plant growth • E valuation in vitro, in pots, and enhancement mechanisms are nutrient acquisition in field conditions (asymbiotic N-fixation, phosphate solubilization, and siderophore production), modulating Characterization of PGPM specimens phytohormones (direct mechanism), and the ability The following shows the items involved in to act as a biocontrol against phytopathogens characterizing PGPM specimens. Parameters Remarks/references Cultural characteristics Colony diameter (mm), colony texture Physiological characteristics Growth rate, acid base production Functional characteristics Plant growth promoting Phosphate solubilization on solid medium Edi-Premono et al. (1996) P solubilization on liquid medium On different inorganic P sources Production of phytohormones (such as IAA) Bric et al. (1991) Siderophore production Schwyn and Neilands (1987) Growth inhibition % inhibition effect over control (Landa et al., 1997) Enzyme assay Chitinase and protease production (Ryden et al., 1973) 10 Data Management Standardization Guideline on Soil Biology Plant Root Root Exudates Root Border Cells(doughed root caps) Rhizo-deposites Attraction Repulsion Benefitial or Other Microbes Deliterious Microbe’s (Rhizobacteria or colonizing pathogenes) (Plan Pathogenic Bacteria, Fungi Nematodes and Virus) Biological Control of Exant Pathogen and Plant-growth Promotion Plant Growth Promotion Illustration 3: Interaction of PGPMs in the rhizosphere (Smith, 2029) Performance evaluation of PGPM specimens in greenhouse/field The following shows the parameters to be evaluated. Parameters Remarks/references Plant tissue N % Biomass yield kg ha-1 Grain/tuber/fruit yield kg ha-1 Plant tissue total P ppm Plant height cm Disease incidence and severity scaling % P-use efficiency Refer to Section 1.5.2 N-use efficiency Refer to Section 1.5.2 Earthworms and vermicompost adoption of ecological and sustainable farming practices can reverse the declining trend in Environmental degradation is a major threat global productivity and protect the environment confronting the world, and the rampant use of (Wani et al., 1995). Earthworms are important chemical fertilizers contributes largely to the biological organisms that help nature to maintain deterioration of the environment through excess nutrient flows from one system to another use of fossil fuels, generation of carbon dioxide and minimize environmental degradation. For (CO2), and contamination of water resources. a range of agricultural residues, all dry wastes Now, a growing realization exists that the Data Management Standardization Guideline on Soil Biology 11 can be converted into vermicompost. In short, earthworms, through a type of biological alchemy, are capable of transforming garbage into gold (Crescent, 2003). Anus Posterior Earthworm external morphology Dorsal pores Mouth Clitellum Anterior Vermicomposting is a simple biotechnological Collection of earthworms process of composting in which certain species Collecting earthworms involves the following steps of earthworms are used to enhance the process (Brown, 2018): of waste conversion and produce a better end-product. • Mapping potential collection area Vermicomposting differs from composting • Soil pit sampling in several ways. Sustained vermiculture practices • T otal abundance (# m-2): count of adult and the use of vermicompost improve the earthworms per square meter moisture-holding capacity of soil, which decreases -2 water for irrigation. Vermicompost also improves • Biomass (g m ): live weight of adult worms the physical, biological, and chemical properties per square meter of soil, soil porosity, and softness of soil. Ample • Ratio of adults to juveniles (with no clitellum) opportunities also exist for a decrease in uses of energy and greenhouse gas emissions in • Preserve, record, and identify the adults vermicompost production locally on farms by Characterization the farmers themselves (Hussani, 2012; Singh, It is essential to characterize the earthworms, 1993). The cost of producing vermicompost is the substrate (feedstock and bedding materials), insignificant compared with that of chemical the vermicompost, and the vermiwash following fertilizers. The rejuvenation of degraded soils standard methods. This process follows. by protecting topsoil and the sustainability of productive soils are major concerns internationally. 12 Data Management Standardization Guideline on Soil Biology Characterization of earthworm specimens Morphological parameters Units/remarks/references Body length mm (total length from head to tail) Pigmentation Qualitative Total number of segments no. Number of setae no. Clitellum width mm Position of female pore nth segment from head Position of male pore nth segment from head Growth/Multiplication Parameters Initial total matured worms no. Final total matured worms no. Initial total biomass g Final total biomass g Rate of increase in worm number % Rate of increase in worm weight (biomass gain) % Individual initial body weight g Individual final body weight g Individual weight gain % Individual initial length cm Individual final length cm Length increment % R = End EW biomass (mg) - Initial EW biomass (mg) , where EW = earth worm Growth rate determination Time period (days) (Suthar, 2005) Data Management Standardization Guideline on Soil Biology 13 Morphological parameters Units/remarks/references Cocoon count Number of cocoons laid week -1 Count of cocoon production Cocoon production worm-1 day-1 (Ismail, 1997) Mortality rate of worms % Biomass conversion rate Lalander et al. (2015) Proximate Analysis (For Processed Earthworms) Crude protein % Ash % (Srilakshmi, 2014) Dry matter % Earthworm Evaluation Based On Vermicomposting Vermicomposting period Number of days No of days, From day 1 to harvest Vermicompost yield kg kg, weight of air-dry vermicompost produced Vermicompost quality See section 4.2.3 VR = Final compost dry weight (kg)Vermicomposting rate *100Initial substrate dry weight (kg) Earhworms Potential As Chicken Feed g,W = Wieght gained at time t (g)Average daily weight gain Day chicken Feed consumption g d-1 FCR = Average daily feed intake (g)Feed conversion ratio Average daily weight gain (g) Average egg weight g g Total egg production # no. Egg quality (albumen, shell and yolk weight, and shell thickness) 14 Data Management Standardization Guideline on Soil Biology Characterization of feedstocks and bedding materials The following parameters are involved in characterizing feedstocks and bedding materials. Parameters units pH Unitless EC dS m-1 Total N % Total P g kg-1 Total K % Organic carbon % Ash % C/N ratio (dividing %C by %N) C/P ratio (dividing %C by %P) Water holding capacity Ahn et al., 2005 Characterization of vermicompost The following parameters are involved in characterizing matured vermicompost. Chemical characteristics Parameters units Total organic carbon % Total nitrogen % (Bremner and Mulvaney, 1982) Ammonium/nitrate (NH4:NO3) Ratio C/N Ratio (%C divided by %N) Total phosphorus (P2O5) g kg-1 (John, 1970) Total potassium (K2O) K2O (%) Total calcium (Ca) % Total magnesium (Mg) % pH 1:10 w/v (Bhat et al., 2017) vermicompost in g: distilled water in ml EC dS m-1 (1:10 w/v) Moisture content % (gravimetric water content): (weight of water/weight of dry vermicompost) × 100 Data Management Standardization Guideline on Soil Biology 15 Chemical characteristics Parameters units Plant growth promotion characteristics Vermicompost Efficacy Test in Pot/Nursery Shoot length cm Root length cm GI(%) =x Seed germination * Root length of treatment 100 Germination index (GI) Seed germination % * Root length of control (Bhat et al., 2017) Seedling vigor index Germination percentage×(root length+shoot length) Shoot dry weight g Chlorophyll content µg cm-2 , Darvishzadeh et al. (2008) Vermicompost efficacy test in on-station/on-farm Historical and Biophysical Characteristics of the Site Geographic coordinate In decimal degrees Topographic information % Farm-gate price of labor and inputs USD ha-1 Land-use pattern nominal Cropping history nominal Climate history nominal Post-planting Data Required Seedling vigor Germination percentage×(root length+shoot length) Plant height centimeter (cm) Shoot dry weight g Grain yield kg ha-1 Harvest index %: (Grain yield/biomass yield) × 100 Straw biomass kg ha-1 N-use efficiency Refer to Section 1.5.2 P-use efficiency Refer to Section 1.5.2 16 Data Management Standardization Guideline on Soil Biology Vermiwash/vermicompost tea Vermiwash is the brownish-red liquid that comes from the body of earthworms and vermicompost filtration. The following parameters will be required to describe it in minimum detail. Parameters Units/reference pH 1:10 w/v Electric conductivity (EC) dS m-1 (1:10 w/v) Organic carbon % Available N ppm Dissolved oxygen mg L-1 (APHA, 2005) Available P % Available K % Plant Growth Promotion Effect Worm Collection Major subsequent activities Vermicompost Characterization Worm Characterization Substrate Feed Suitability Characterization for Chicken Illustration 2: Major subsequent activities of earthworm and vermicompost research. Data Management Standardization Guideline on Soil Biology 17 Bio-indicators of soil quality • P otentially mineralizable nitrogen (PMC) (mg and sustainable use N kg-1 d-1) is the fraction of nitrogen easily decomposable by soil microorganisms and is Like physical and chemical indicators, biological considered an indirect measure of nitrogen indicators have a relationship to soil functions availability during the growing season and can evaluate these functions to assess soil (Piconne et al., 2002). quality. These indicators respond rapidly to soil -1 management and land-use changes and can be • S oil microbial biomass (SMB) C (µg C g dry candidates for soil quality indicators. Limitations soil) is measured by the substrate-induced exist, however, in directly measuring soil respiration (SIR) method (Anderson and organisms as indicators of soil quality. Because of Domsch, 1978). this, biological dynamic properties [respiration, where B is the mean volume of HCl consumed POM (particulate organic matter), PMN (potentially by blanks (mL), S is the mean volume of HCl mineralizable nitrogen), and microbial biomass] consumed by samples (mL), 4 is incubation time are often regarded as the minimum dataset to (h), 100 is a conversion factor (100 g DM), 2.2 is a describe the microbial part of soil organisms while conversion factor (1 mL 0.1 M HCl corresponds the rest measure soil quality and fertility. to 2.2 mg CO2), SW is initial soil weight (g), and DM is soil dry matter (%). A respiratory quotient of one is assumed. • Soil microbial biomass nitrogen (SMBN): the fumigation-extraction procedure according to Solaiman (2007) is the determination way and often reported in mg N kg-1 dry soil. • Soil organic matter (%): see Nelson and Sommers (1982). • Soil aggregate stability index (SASI): , where A and B are the weights of aggregates passed through a 0.25-mm sieve after 5 and 60 min, respectively (Pagliai et al., 1997). • Soil bulk density: see (Al-Shammary et al., 2018). • Soil organic carbon (SOC) where SOCi = soil organic carbon of a given soil depth, mg C ha−1; BD (bulk density) = soil mass per sample volume, kg soil m−3 (equivalent to kg m−3); di = horizon, depth, or thickness of soil layer, m; and CFi = % volume of coarse fragments/100, dimensionless. Coarse fragments can be Physical appearance of matured vermicompost (Photo: Abere Mnalku) determined as percentage weight of soil greater than 2 mm. • Soil respiration measures the potential N or • Microbial abundance: The Gram-positive C mineralization role of soil biota (Ryan and bacteria, Gram-negative bacteria, fungi, and Law, 2005). actinomycetes could be enumerated using • Particulate organic matter (POM) comprises the dilution plate count technique; see (Acea all soil organic matter (SOM) particles less and Carballas, 1996; Tateishi et al., 1989; than 2 mm and greater than 0.053 mm in Mabuhay et al., 2004). size. POM is biologically and chemically active, • L itter decomposition: A common method for is part of the labile (easily decomposable) estimating decomposition rates is to use pool of SOM, and is estimated according to litter bags, detail is found on Moore and Diovisalvi et al. (2014). 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Nodule Collection and Preservation Isolation of Rhizobia From Nodules Presumption Test (Congo Red, BTB, etc Media Authentication/Infection Test on Sterile Media Effectiveness Test of the Top Performing Isolates on Sterile Medium in Greenhouse Effectiveness Test of the Top Performing Isolates on Non-Sterile Medium in Greenhouse Evaluation of the Top Performing Isolates (Carrier-Based) in the Field Molecular Characterization of Outstanding Performing Strains Data Management Standardization Guideline on Soil Biology 21 Appendix Figure 2: Field layout and dimensions of a trial with three replicate blocks containing five test strains and three controls (a) and a replicate block containing five test strains and three control treatments, a commercial inoculant, nitrogen fertilizer, and a non-inoculated control (b). 12 m Block 1 One Meter Pathway Block 2 17 m One Meter Pathway Block 3 12 m 5 m Strain 1 Strain 2 Strain 3 Strain 4 Strain 5 Inoculant +N -N Non-inoculated Check Rows Test Rows for Sampling 22 Data Management Standardization Guideline on Soil Biology Appendix Table 1: Sample data recording sheet of MPN count. Replicates Dilution level Total 1 2 3 4 5-1 + + + + 4 5-2 + + + + 4 5-3 + + + + 3 5-4 - - + - 1 5-5 - - - - 0 5-6 - - - - 0 Experimental results = 4-4-3-1-0-0, replications = 4, tabular MPN = 165. Population estimate = 165 cells per gram of sample. Inoculation volume = 1 mL. Appendix Table 2: Nodule sampling passport data. Collector Authority Side ID Data Collected Location Latitude Longitude Altitude (m) Rainfall (mm) Soil Colour pH (Kit) pH (Water) Photo Ref. Parent Material Habitat Soil Type Soil Depth Aspect Granite Pasture Sand 0 - 10 cm Flat Basaltic Fallow Sandy Loam 10 - 20 cm North Schistic Crop Loamy Sand 20 - 40 cm South Calcareous Wood Loam >40 cm East Limestone Market Clay Loam West Alluvial Roadside Clay Sandstone Stoney Dune Gravel Organic Slope Water Relations Area Sampled Grazing Pressure Level 0-3% Free Draining 1 m2 Nil Ondulating 3-8% Water Table 1 - 10 m2 Light Rolling Gently 8-16% Swamp 10 - 100 m2 Moderate Sloping 16-30% 100 - 1000 m2 Heavy Steep >30% >1000 m2 Accession Host Common Name Bottle Number Notes Data Management Standardization Guideline on Soil Biology 23 24 Data Management Standardization Guideline on Soil Biology Appendix Table 3: Observation recording sheet of rhizobia study (adapted from N2 Africa-Ethiopia). Treatment descriptions installation crop establishment phenology Gross Rep Trt Plot Plot Planting Date Date of Germination Date of 50% Date of 50% Date of Full No. Size Germination Count Percentage Flowering Podding Maturity # # [m2] DD MM YY DD MM YY [%] DD MM YY DD MM YY DD MM YY Data Management Standardization Guideline on Soil Biology 25 biomass sampling at maximum biomasS Fresh Active Inactive Weight of Nodules Nodules Area of No. of all above Fresh Above Nodule (Sum (Sum of Nodule Biomass Plants in Ground Weight of Dry Weight Ground Mean of Pink, White, Dry Date of Biomass Sampling Sampling Sampled Biomass Biomass of Biomass Biomass Score Red, Green, Weight Plot Area From Subsample Subsample Weight From 10 Brown Black From 10 Biomass (Calculated) Plants Colour) Colour) Plants Plot From 10 From 10 Plants Plants DD MM YY [m2] # [kg] [g] [g] [kg Dry] # # # [g] 26 Data Management Standardization Guideline on Soil Biology Final Harvest Total Total Fresh Fresh Weight Fresh Fresh Dry Weight Total Area of No. of Weight of all Weight Weight Dry Weight of Empty Dry Weight Dry Stover Date of Harvest Harvest Plants in of all Haulms of a of a of Grains Pods of Haulms Weight Grain Haulm Empty Yield Harvested Pods (Without of the (Husks) in the of 100 Yield Yield Pod Yield (Haulm Plot Area in the Pods) Subsample Subsample (Calculated) (Calculated) (Calculated) + Empty Harvest in the of Pods of Haulms Subsample in the Subsample Seeds Subsample Pods) Plot Harvest (Calculated) Plot DD MM YY [m2] # [kg] [kg] [g] [g] [g] [g] [g] [g] [kg/ha] [kg/ [kg/h] [kg/ha] Appendix Table 4: General information (metadata) sheet. Data Management Standardization Guideline on Soil Biology 27 General information recording sheet for rhizobial study Farm ID Season/Year Country Ethiopia Woreda Kabela Latitude Longitude Altitude (m) Experiment site GPS Coordinates (e.g. Coordinate in decimal degrees 7.2458) Name of organization implementing EIAR-HARC the trial Data Entry by Type of Experiment Test Legume Soil Data (Composite Soil Samples Before Planting) pH (H O) Total Carbon Total Nitrogen P (Olsen) CEC Exch. K Exch. Ca Exch. Mg Exch. Na Sand Silt Clay2 % % ppm cmol/kg cmol/kg cmol/kg cmol/kg cmol/kg % % % Field history Previous Season Season before last season Crops Grown in the N2A Plot: Mineral Fertilizer Used: Organic Input Used: Inoculant Used: Location of the Plot in the Landscape: 1) Plains, 2) Valley bottom, 3) foot slope, 4) slope, 5) plateau Soil Drainage in the Plot: 1) Good, 2) Moderate, 3) Poor Are there Signs of Soil Erosion in the Plot: 1) Yes, 2) No Please fill in the dates at which the following events occurred on the strain by legume Varieties Field Trials. Activity DD mm YYYY Date of Land Preparation Date of Organic Manure Application Date of Planting Date of Mineral Fertilizer Application Date of 1st Weeding Date of 2nd Weeding Date of 3rd Weeding Date of Pesticide Application 50% Flowering 50% Maturity Date of (final) Harvest Pesticide Name 28 Data Management Standardization Guideline on Soil Biology Please record rainfall data in the growing period using the following table. The data can be sourced from the nearby weather stations either owned by research center or NMO. Name latitude longitude Altitude (m) Nearby Weather Station GPS Coordinates (e.g. Coordinate in decimal degrees 7.2458) Rain (mm) DD MM YYYY Data Management Standardization Guideline on Soil Biology 29 Partners: Alliance