 Good morning, everyone. Nice to see you again for the second day of the virtual training on the SDG 241. I hope you have had the nice end of the day yesterday and that you have taught a bit about the discussions we have had yesterday. Before starting, I would like to recap quickly what we have learned yesterday. So we have seen the 21 SDG indicators that are under the FAO custodianship. We have focused, of course, on the SDG 241 and we have seen its background, the scope, periodicity, levels, limitations, policy use, and so on. And finally, we have moved to the framework, which is the core content of this training. We have seen the details, the entire economic dimension, and the methodology to calculate it with the three subindicators, which are the farm output value per hectare, net farm income, and the risk mitigation mechanism. We have then passed to the environmental dimension with its five subindicators, so prevalence of soil degradation, variation in water availability, management of fertilizers, and management of pesticides. And today, we are going to see the last one, which is the use of agro-biodeversity supportive practices. Then we will move to the last dimension, the social one, with the other three subindicators. Moreover, today, we will see the SDG 241 data collection questionnaires and the results of the pilot exercise, where some of your countries took part. And finally, a colleague from Statistics Canada will illustrate their experience in the SDG 241 reporting. If you have a look at the original agenda, you can notice that there is one presentation, which is missing today, the one about the agri-survey program. For your information, we have moved this presentation to tomorrow. So yesterday has been a very interesting day full of concepts and many doubts have been clarified through the question and answer sessions. In case some of you have some questions already, considering what we have seen yesterday, please feel free to raise it now. So in the chat box, of course, you are always more than welcome. Let me see. Okay, there is only one good morning message. Thank you. So in case you don't have any questions so far, we start immediately. And with the next subindicators, and I leave the floor to Asfanya. Thank you very much, Stefania. Can you confirm if you can hear me? Yes. Okay, perfect. So as Stefania mentioned, yesterday we covered the conceptual and methodological basis for SDG 241, the fact that we are focused primarily on agriculture holdings that produce crops and livestock. The periodicity of the indicator is three years and the data is collected using agriculture surveys or farm surveys. Now, today we have to cover the last indicator in the environmental dimension. So let me share my screen. So this subindicator is the last one in the environmental dimension. To give you some context, the subindicator was subject of discussion and refinement in 2019 as part of the 2020 comprehensive review of the global indicator framework. The discussion involved country-led working group, which was coordinated by Canada, with Brazil, USA, Argentina, Chile, France, and Russian Federation as the members. After an year-long discussions and consultations, towards the end of 2019, a compromise solution on the indicator criteria was reached, after which it was tabled again for IAEG-STG review, where the group pre-approved and re-endorsed the indicator methodology in November 2019. From a methodological perspective, the subindicator measures the level of adoption of agro-biodiversity supportive practices by the farm and ecosystem species and genetic levels for both crops and livestock. One important point to note is that specifically in case of this indicator, the scope is the entire agriculture area of the holding as opposed to agricultural land area that is used as a denominator for other subindicators. So based on whether organic certified agriculture is practiced at a country level, two set of criteria are proposed. One for countries practicing traditional agriculture, and another one for countries where organic agriculture is practiced by and large. So here are the set of the criteria for countries with no organic certification. I'm not going to go again through the criteria because these concepts are well explained in the enumerator manual. And if you would like to understand more about the definitions about these term terminologies, you can go to that particular document, which we will of course share with you post this training for you to better understand as to what these are about. So for countries with no organic certification in place, we propose five criteria. For countries with organic certification, we are proposing six criteria. The five are the same from the previous slide. One additional one which is highlighted in red here is added, which is farm produces agriculture products that are organically certified or its products are undergoing their certification process. Again, let me reiterate that it applies only to countries with organic certification. Now in terms of thresholds, of course we are providing two sets of criteria. So we have a device, two sets of threshold to assign from and the agriculture area that it owns manages and operates sustainability statuses. So depending as to whether if the countries are practicing organic agriculture, then the farms will be classified as green. If the agriculture holding meets at least three of the before mentioned criteria, it will be highlighted as yellow. If the agriculture holding meets at least one of the criteria listed on the previous slide and the agriculture holding is labeled red if it meets none of the criteria. Similarly, for countries with no organic certification, because we have five criteria. So in this case, the farms will be labeled green if the agriculture holding meets at least two of the listed criteria. Agriculture holdings are assigned yellow status. If it meets at least one of the before mentioned criteria and the agriculture holding is labeled red or unsustainable if it meets none of the above criteria. And the last step of course is the same from the previous slide. Once we label the farms and its agriculture area green, yellow and red statuses, we then add up the agriculture area by sustainability status and divided by the nationally representative agriculture area that is collected using the sample survey to arrive at the proportions for this indicator. Are there any questions? No. Okay. So with this, we come to the end of the five sub indicator in the environmental dimension. Now we'll quickly move into the social dimension, which is the last one within the framework of SCG 241. It constitute of three sub indicators wage rate in agriculture, food insecurity experience scale, and secure rights to land tenure. So the first sub indicator in the social dimension is wage rate in agriculture. The theme is decent employment, the reference to last calendar year. One important point to note is that the coverage or the applicability of this particular sub indicator is only for the farms that hire unscaled external labor. So this theme provide information on the deumination of unscaled workers working on the farm that belong to the elementary occupation group as defined by the International Standard Classification of Occupation Code 92. It is published by ILO or International Labor Organization. In other words, it informs about the economic risks faced by the unscaled workers who are performing simple and routine tasks requiring the use of simple hand-held tools and very often considerable physical effort. To exemplify unscaled workers who are involved in digging, shoveling, loading, unloading, stacking, raking, spreading of manure or fertilizer, watering, weeding, picking fruits or vegetables and various seeds or plants, feeding animals, cleaning animal quarters and so on. So once we collect information on the unscaled labor deumination, then what we do is we benchmark it against the prevailing national minimum wage rate in agriculture sector or national minimum wage rate to assign farm green yellow and red statuses. So in terms of the thresholds, the farms are assigned green status if the wage rate paid to unscaled labor, which I defined already, is above the minimum national wage rate or minimum agriculture sector wage rate if available. And again, as this indicator is not applicable to farms that are not hiring any labor, so by default those farms will be highlighted as green. The farms will be classified yellow or acceptable if the wage rate paid to unscaled labor is equal to or is equal to the minimum national wage rate or minimum agriculture sector wage rate if it is available. And the farms will be assigned red status if the wage rate paid to unscaled labor is below the minimum national wage rate or minimum agriculture sector wage rate if available. So again, depending on the daily average wage rate paid to agriculture unscaled worker, the farm will be classified green yellow and red statuses and then we combine the agriculture area assigned desirable acceptable and sustainable status and we divide it by the total agriculture area. This is a similar step that we perform for all of the sub indicators to arrive at the proportion under each color. Srifanya, any questions on this part? Not yet, no questions. So then we move to the 10th sub indicator within the framework of SD241, which is food insecurity experience scale. This is a well-known indicator. It's already here one, it's SDG 2.1.2 meaning that it has an established methodology and data on it is regularly collected by countries and is reported regularly by FAO. This particular sub indicator is customized or tailored in the context of 241 and it tries to measure the extent to which household of the holder or the owner of the farm are food secure despite having some agriculture production. I will not go into the details of how to estimate the severity of food insecurity using food insecurity experience scale. First assuming that many of you may know about this indicator because it's already here one and data is regularly collected and reported by countries and secondly because of the shortage of time. However, I will touch upon the basics of the methodology which while referring you to the training material on the indicator which is already published by FAO. In short, PH is a metric of severity of food insecurity that is measured at a household level. It is a statistical measurement scale designed to measure unobservable or latent traits and is measured based on people direct yes or no responses to the eight FIES questions regarding their access to adequate food. The FIES questions refers to the experiences of the individual respondents or of the respondent household as a whole. Obviously these answers are answered by the holder or the owner of the agriculture holding. The question focuses on self-reported food related behaviors and experiences associated with increasing difficulties in assessing food due to resource constructions. Here are the eight FIES questions that include data on the food insecurity of the household of the holder of the farm. I will again be framed from going into details of explaining each question, a detailed explanation on what this question entails is given in the PDF file that I have attached to this slide. So once the data on the eight FIES question is collected using agriculture survey, the first step is to prepare the data for analysis where the standard labels are eight to the eight FIES questions. In the second step the data is inputted into the model prepared by FAO FIES team for parameter estimations. That is a calculation of the level of severity of food insecurity associated with each questions and each respondent is estimated using a model which is called a RASH model. In total two parameters are estimated, item parameters also technically called the difficulty parameters which refers to and are derived from the eight FIES questions using the model and the respondent parameters or ability parameters that are derived from the number of people who responded to the eight FIES questions. The third step is statistical validation where an assessment is made as to whether depending on the quality of data collected the estimated parameters are valid that is both the item parameters and respondent parameters and to check if the data are consistent with the theoretical assumption that informs the model. Finally as a last step the calculation of sustainability status of agriculture holding is carried out once a measure of severity of food insecurity condition experienced by each respondent that is the holder of the agricultural holding. Based on their answer to the eight FIES questions has been derived the sustainability status of the holding that is desirable acceptable or non-sustainable as per SCG 241 methodology is then derived accordingly. Let me elaborate the steps described on the previous slide based on the data collecting using the eight FIES questions it is prepared for analysis where each data item is coded where two is assigned for no response and one is assigned for for yes. After the coding standard labels are added to the eight FIES questions as per the model developed by FAO FIES team so for these codes which are shown on the previous slides in this row of course this code will be different based on the on the on the country survey and the coding mechanism used by the country however we will then label it with the standard labels for the question number one we call it worried, healthy, few foods, skipped, ate less, run out, hungry and and hold it so and then the one and two on the previous slide the the codes are then replaced with the standard label as to as to whether the holder of the agricultural holding you know gave yes or no answer to the to the eight FIES questions. So once the data has been properly codified and standard labels are added to the eight FIES questions the next step involves estimating the parameters associated with the with these questions. The methodology underlying the estimation of the parameters for prevalence of severity of food insecurity is based on the item response theory which is used to analyze responses to the survey or the test questions in this case the eight FIES questions. The item response theory is a quantitative traits or latent traits that can be derived from a set of dichotomous or binary variables that take a value one or two. Thereafter as I mentioned earlier rush model which is developed by FAO which is in fact used by FAO is applied for the analysis of the of the FIES data. So once the data is inputted into the model the responded parameters are estimated from the raw scores the raw scores are the number of affirmative or yes responses given to the eight FIES questions. The raw score is an integer number with a value between zero and eight. Thus the total number of parameters are nine. So as you can see here once we input it input them the data into the model you know we will we will arrive at difficult parameters or the respondent parameters whereby the the the one in the top which is shown as negative is the least severity while the the last one which is the whole day shows the highest severity in terms of food insecurity. The sub indicator so the second set of parameters that we derived are the respondent parameters as I mentioned to you earlier the respondent parameters raw score is used to calculate calculate this this parameter and I mentioned that earlier that the raw score is the number of affirmative or yes responses given to the eight FIES question an integer number with a value between zero and eight and hence the total number of respondent parameters are nine. So once we once we derive the respondent parameters or the ability parameters which are which are depicted here the standard errors and the frequency of the of the agriculture holdings that responded yes to each FIES questions we then estimate this frequency and then you know this information the responded parameters standard errors and frequency and the item parameters which are the difficulty parameters are then used to estimate the probability of severity of food insecurity at the household level. So once we have the difficulty parameters estimated we then plug it into the excel file prepared which can be accessed here this this information is then inputted into this excel file for the difficulty parameters and as well for the ability parameters along with the standard errors and the number of and the frequency of the of the agriculture holding that responded yes or no to these questions to arrive at the probability of severity of food insecurity. So once we derive this probability of moderately in severe food insecurity and probability of severe food insecurity we arrive at two numbers and these are in fact the the values of SDG indicator 2.1.2 which is which is the FIES indicator. Now in case of 2.1 we go one step beyond this process and we then use these probabilities and then we start comparing the individual household probabilities based on their RAS scores and item and respondent parameters and then we compare it with the probabilities of the distribution to assign the farms and agriculture area that it owns manages and operates sustainability statuses. So just to go through the green yellow and red statuses that are assigned to agriculture holding and agriculture area it owns manages and operates the farm is assigned green status if the probability of household of the holder of the agriculture holding to be moderate to severe food insecure is less than 0.5 and the probability to be severely food secure is less than 0.5 then you know we consider this particular agriculture holding to be to be classified as as desirable or green. The holdings are classified as yellow or acceptable or moderately food insecure if the probability of a household of the holder of the holding to be moderately to severe food insecure is greater than 0.5 and the probability to be severe food insecure is less than 0.5 then we classify this farm as yellow and the farms are classified as red if the probability of the household of the holder of the agriculture holding to be severe food insecure than 0.5 then we classify this agriculture holding as red. So here is an example based on the data that we collected processed and analyzed for Bangladesh pilot test. So as you can see here the agriculture holding one has the probability to be moderately severely food insecure is 0 as well the probability to be severely food insecure is 0 which is less than 0.5 in both these cases and hence we classify this agriculture holding as desirable. Another case holding number four the probability to be moderately to severely food insecure is greater than 0.5 it is estimated to be 0.7 however the probability to be severely food insecure is less than 0.5 hence we classify it as yellow and in case of holding 13 the probability to be moderately and severely food insecure for this particular area is greater than 0.5 and as well the probability to be severely food insecure is greater than 0.5 and hence this agriculture holding and the agriculture area that it owns manages and operates is is classified as non-sustainable and once we carry out all these steps the last step remain the same like in case of all other sub indicators then add together all the areas classified as green yellow and red and divided by the nationally representative agriculture area to derive the proportions by by green yellow and red colors okay okay so the last sub indicator within the framework of CG241 is secure rights to land tenure this indicator allows assessing sustainability in terms of rights over use of agriculture land areas since agriculture land is a key input for agriculture production having secure rights over land ensures that agriculture holding have control over a key asset and does not risk losing the land to any external does not lose does not risk losing the land in the short or medium term um evidence has shown us that farmers tend to be less productive as they are reluctant to invest if they have limited access to and control of economic resources particularly particularly land so the way the sustainability criteria for this sub indicator of structure the farm is assigned green status if the if it has a formal document with the name of the holder or holding on it or has the rights to sell or be quet any parcel of the holding okay the farm is classified as yellow or acceptable if the holding has a formal document even if the name of the holder of the holding is not on it and the farm is classified as red if the the farm neither has a formal document um and and and it has no rights to sell or be quet any parcel of the land then we classify it as it is red in terms of the Bangladesh testing exercise holding one respondent to the question yes we do have a formal document and yes we do have our name on the on that formal document and we have the right to sell and we have the right to be quet and hence we assigned it a green status or desirable status the second holding the respondent to the question yes we do have a formal document we don't have the the name of the holder or the holding on the document and we don't have any rights to sell or write to be quet but hence because of the fact that they have a formal document we classify them as acceptable and holding 51 they neither have a formal document and hence they you know all the other questions regarding related to as to whether their name is on it um is is is not relevant as well they don't have any rights to sell it or any rights to be quetted and hence this holding is is classified as as unsustainable again once we once we classify the farms and as agriculture area based on the set of questions that we asked the holder in relation to as to whether they have a formal document and as to whether the name of the holder or the holding is on whether they have the right to sell or be quet any parcel of the land they will be assigned green yellow and red statuses and once these green yellow and red statuses are assigned then we add up the area classified as green yellow and red and and divided by the total agriculture land area to arrive at the proportions for this particular certificate and with this I come to an end of of my presentation on the on the framework of sg241 if you have any further questions related to any of the sub indicator I mean please don't hesitate to write to us using the email address sg241-indicator at fao.org and we will be very happy to answer your questions and address your concerns that may that you may have so thank you very much. Thank you Spangar. In this session we will cover indeed the data collection tools that have been developed by by FAO to support countries in their data collection and reporting efforts on sg241. As highlighted yesterday and today the focus of sg241 is to assess the sustainability of farm holdings and its agricultural land area thus farm surveys offers an opportunity for collecting data through a single instrument for sg241. Now the decision to use farm survey is in line with country efforts which are supported of course by FAO to develop farm survey as the most relevant or appropriate tool for generating agriculture statistics. The choice of farm survey in case of or in context of 241 was made because of the following reasons. Farm surveys does exist in countries in one shape or form or another to collect data on different aspects of agriculture not only for sg monitoring but for many other purposes like say for example to collect data to report on value addition for gross domestic product estimation. The use of farm survey will help collect information on all 11 sub indicators using one data collection instruments thus it avoids the additional work of integrating information coming from different data sources that are usually managed by different institutions or organizations within country. Plus using the farm surveys all information will be collected from holdings selected to a nationally representative sample thus avoiding the problem associated with the use of different data sources. And plus farm survey are expected to be cost effective in comparison in comparison to putting in place monitoring systems such as soil and water sampling and laboratory testing, geographic information systems and robust administrative record systems. To measure farm surveys are well suited to measure the economic dimension of sustainability. It may not be an ideal tool for measuring the environmental and social sustainability of the whole thing. Typically and we have been getting this response quite often that environmental impacts of agriculture are measured through monitoring systems like remote sensing, soil and water sampling or other tools associated with a specific area rather than within a single agriculture holding. In addition we also understand that for several environmental themes it is unlikely that farmers would be able to assess the environmental impact of their farming practices. For example issues like fertilizer pollution or pesticides used so using farm survey instead of environmental monitoring systems therefore implies moving away from measuring outcome or impacts to assessing farmers practices and behaviors. Similarly the information in the social dimension is generally captured through household surveys while in majority of the cases agriculture farm holdings are closely associated with a given household this is not always the case. And therefore care must be given to capturing the information through dedicated service designs. Having said that the methodological note of SD 241 does offer the countries the flexibility of using combination of different data sources other than farm surveys which we call the alternative data sources. So the way the indicator is designed now the methodology of the indicator 241 is designed now we are offering three solutions of which the first two are developed fully. The second one on alternative data sources is the work that we have undertaken now and will be developed towards the fully towards the end of 2021. So for the farm survey approach we have developed a standalone farm survey questionnaire model that I will show you in a bit. It is designed as a module that contain the minimum set of questions needed to collect information on SDG 241 to assess the sustainability performances of the farm. Now it can be administered as well independently or attach a separate module or integrated at appropriate places within the existing existing farm survey currently in place at the country level. The second approach that we have developed is the flagship project of FAO called the Aggress Survey Program in 50 by 2013 initiative. We were supposed to cover this today but as Sifanya mentioned we move this presentation tomorrow so we will I will touch upon this but in detail we will we will cover this in more detail tomorrow. Another thing alternative data sources I briefly talked about the methodological note of SDG 241 does refer and allow country the flexibility to use alternative data sources that is earth observation, geographical information system, remote sensing, administrative records, household survey monitoring system and sensors but that approach is not yet fully developed. We are working on that and the moment it is translated into guidelines hopefully by next year as I mentioned earlier we will we will share that with with the countries. So as I was mentioning earlier the standalone survey questionnaire is designed as a module which contains the set of questions needed to assess SDG 241 sub indicators. It can be administered independently or attached as a separate module or integrated at appropriate places within the existing firm's surveys. We have cognitively tested the questionnaire module in max and Rwanda back in 2017 and 19. Of course the objective was to refine the survey questionnaire from the design flow comprehension respondent recall and judgment perspective. And then you know an additional objective was to assess if the questions asked are sufficient and fully understood by limited number of heterogeneous heterogeneous respondents and based on the feedback that we got through these tests to revise the proposed criteria, determine the time of the survey, revise the status scripts and routines and revise accordingly the methodological note and and and so forth. For this particular standalone survey questionnaire that I will show you in a bit we have also tested it in Bangladesh and you saw the results in the in the previous presentation where we collected data test assessment ability criteria and you know assess the time as I mentioned and revise the support documents. The survey questionnaire is divided into five sections. Of course we start with with an introductory section then the second section focus on the area of the holding. The third section covered the three sub indicators in the economic dimension. The fourth section covered the five indicators in the environmental dimension and in the fifth section covered the all the questions in the in the in the social dimension. So let me just quickly show you the survey module. So this is the SG241 survey module that I was talking about. As you can see here it can be administered in its own right as a standalone survey on SG241 but what we recommend to countries is to go through the survey and then in the light of the survey analyze their current agriculture surveys which are already in place at the country level and see as to what questions are missing and then integrate questions from from this module into their agriculture survey so that those are able to report on SG241. So as you can see here section one is on the introduction to the survey module and identification of the holder of the holding and the holder. Then section two is on the area of the holding and all the aspects that we covered in the in the very first presentation related to SG241 are related to how do we estimate agricultural land area can be can be collected through these questions then we have questions related to the economic dimension of the holding questions related to the environmental dimensions of the holding it covers the five sub indicators in that dimension and questions related to the social dimension of the holding. So it provides you with a very good starting point whereby you can see as to where the gaps are in terms of the questions which are already part of your current agriculture surveys you can see as to what is missing and then you start integrating questions from here into your agriculture survey to make it SG241 ready. Provided you with a link to this questionnaire which is already available on FAO SG241 dedicated webpage. Not only the survey questionnaire but all the support documents that I will now go in a bit. You can go there and download it and familiarize yourself with all the support documents. The support documents for SG241 contains a numerator manual the instruction manual for data integration and analysis guidelines on data analysis to compute the sub indicators sampling guide guidance for SG241 and FAO statistical toolkit which comprise of a code book, tabulation plan and modular status scripts to support data analysis. So let me go into each one of them one by one. So the numerator manual has been developed to train the numerators, surveyors and supervisors before their field deployment to administer the questionnaire that I just showed you. It provides the definition of the key terms concepts and the meaning behind the questions asked. It provides guidance on the use of skip questions and filter questions and provide examples of commonly encountered instances where questions and responses may not be easy to administer or record appropriately. Then we have instruction manual on data into operations which has also been developed and available online. It describes the data into operations that is all the steps that must be performed in order to organize the collected data into excel spreadsheets or other statistical package whether it's SPSS or R or STATA. Then it provides guidance on the procedures to process and analyze data collected and construct the 11 sub indicators according to the dashboard approach which we covered as part of the previous presentation. One important point that I would like to highlight is that basically this document assumes that the numerators and data analysts are familiar with the survey questionnaire and the methodology of STD241 respectively. If not, numerators and data analysts are strongly encouraged to carefully read and get familiar with aforementioned documents before proceeding with reading of the instruction manual on data into operations. Then we have also developed guidelines on data analysis and reporting. So it is primarily used by data producers and data users alike. It's meant for government data and statistics authorities, the private sector, civil society, research and other organization that generate and or use data and statistics for calculating the sub indicator of STD241. It also provides the different steps that are needed for calculation of the thresholds and the final reporting of the 11 sub indicator as a dashboard. Apart from this, I mean we have also developed this document which provides sampling guidance on STD241. This document covers the sample size, sampling unit and frames, who are the reporting units, estimation domains, sampling design estimator and stratification variables that we have been talking about like say for example household and non-household, crop, livestock and mixed and irrigated and non-irrigated agriculture area, sample allocation and stratas and other issues related to STD241 sample selection. As mentioned earlier we have also developed an e-learning course that provides information on the key aspects of the indicator, that is scope and coverage, dimension themes and sub indicators, periodicity, data reporting, data collection and reporting, etc. So if you still need to go through the e-learning course or this training it is also available online and you can go through the course and familiarize yourself more with the indicator. Here are the support documents that I just mentioned. All these are available online on the SDG webpage. So let me just show it to you. So this is the SDG 241 webpage which is regularly updated by us and here you can see all the relevant documents that I just spoke about, the metadata, the methodological note. One more important point that I would like to highlight is that this methodological note has already been translated into Arabic Spanish. So plus the FAO questionnaire that Stefania will go through in the next session plus the survey questionnaire that I just showed you. It's also available in Arabic Spanish and French, the sampling guidance for SDG 241, guidance on data analysis and reporting, instruction manual on data entry operations and numerator manual for the forms of a module that I just showed you. Apart from this you can see all the activities that we have undertaken for SDG 241. So the virtual trainings that are you know that are in progress now. So all the information about these virtual trainings plus previous, our previous capacity development initiatives or activities back in 2019 and before that. The e-learning course is available here. So you can simply click here and go to the e-learning course and refresh your concepts and plus other major documents. If you want to get to know more about sustainability in any culture then it will give you a very broader view of the sustainability issues. So here again are the documents. I'm not going to go through this because I covered it in detail and showed you as to where these are. We will provide you with the link that we have already provided you but you know again for your information all these documents are freely available online. Same documents. So this is the first option that we have designed around the methodology of SDG 241 along with all these support documents. The second option that we have developed is basically we wanted to leverage and capitalize on Agri-Service program which is soon to be scaled up into 50 by 2030 initiative that that is a flagship program of FAO and it is supported as well by World Bank and EFAT that aims to support 50 lower and low middle income countries with survey program by 2030. Now for this particular project what we have done is we analyze the survey instruments of the both Agri-Service program and the 50 by 2030 initiative and we then isolate and identify the questions that are missing in the survey instruments of these two programs from the point of view of SDG 241. We integrated those questions and hence now both this initiative which will support 50 countries by 2030 are SDG 241 ready. So for Agri-Service program we have integrated the questions into the core module and the economy and production methods and environment modules of the Agri-Service program and for 50 by 2030 initiative we have added the questions into the production method and the environment module of the 50 by 2030 initiative. I'm not going to go into detail of this particular slide because it's going to be covered at length by my colleague Mr. Flavio Bolliger tomorrow. So here are the supporting documents related to Agri-Service program and 50 by 2030 initiative. Now the option 3 that I mentioned to you that it's still under elaboration is the methodological note of SDG 241. I assume that you have read the note you may have seen this table you know towards the very end of the methodological note whereby the methodology offers country the flexibility to use alternative data sources. However several aspects need to be carefully considered prior to using you know existing alternative data sources in order to produce consistent reliable data as per recommended periodicity. It is advised that the use of alternative data sources may be considered when available data set fulfill the criteria that I will show you on the next slide but here are some of the potential data sources that can be used for the 11 subindicator of SDG 241. So currently we have developed this approach fully and for this I have shown you the not only the survey questionnaire but support documents as well and now currently at FAO we are working on how to leverage these other data sources potential data sources to report on the respective subindicators. So as I mentioned that the use of alternative data sources is conditional on the fact as to whether these data sets fulfill the following criteria. First of all it should be demonstrated that alternative data sources gives results of at least same quality as the service or the farm service and ensure international comparability. It can be reflected in or attributed to agricultural land area in the country considering different farm typologies and agriculture regions. It can be associated with countries agriculture production systems particularly crops and livestock and its mix. It should capture the same aspect or phenomena as proposed in the farm survey as described in the subindicator metadata sheets with at least same quality considering the scientific standard that we just spoke about. Plus these alternative data sources it needs to be checked as to whether these are representative of the situation at the national level with respect to agriculture land area taking into account the main agriculture region types and we need to also check as to whether these are compliance with international and national standards and classification systems in order to ensure that the indicators is international. We only make sure that the data are available at the same level of territorial desegregation as farm survey and the data collection here and if you are dissenting or homogeneous across the across the subindicators. One important point that I would like to highlight is that using different data sources if countries decide on doing so to report on difference of indicator of Z241 implies that mechanism should be put in place at the country level to coordinate regularly the flow of required information generated by various institutions to the national statistical office. Now alternative data sources can be used to complement and validate farm surveys data. This combined approach has the potential to improve the validity and soundness of the results in particularly in countries that have well established monitoring systems and that are able to produce quality information consistently over time. The information from other sources may be used and leveraged in different ways depending on the quality and regularity of its collection. So just to give you an example the alternative data sources can be used to replace farm survey questions when alternative data sources of information are available and respond to the criteria mentioned on the previous slide. The alternative data sources can also complement farm survey questions by providing additional contextual information helpful to interpret the survey results. As well these alternative data sources can be used to cross check the farm survey results to identify any inconsistencies and ensure the robustness of the indicator. This validation exercise can be done exposed or during the data collection by providing the external data to the numerators before going to the field. And this way the numerators can probe whether the responses to the farm survey questions are consistent with the a priori external knowledge. In any case it is recommended that countries complement the farm survey with other sources of information that is monitoring systems for soil, water, fertilizer, pesticide pollution, biodiversity etc. This will provide additional information and help cross checking the robustness of SG241 with regards to the environmental dimension of sustainability. And I will I will stop here. We can start again. So now we have a presentation on the SVG 2.4.1 data collection questionnaire. We have seen so far of the theoretical parts and notions with Aspanyar and the data collection tools. Now let's move to another practical part. So I will show you now how FAO gets the data on the SDG 2.4.1 from the countries, meaning the questionnaire which you have you must have all received on August 10th of this year and that was expected to be sent back to us by the 30th of September. This year now I have a problem with that. Okay. So we have one single questionnaire that comes in Excel format. It is indeed the key instrument to collect the data from countries. It covers all the three dimensions and the 11 subindicators that we have seen yesterday and today. It is sent to countries once a year even if we have seen that the veracity of the 2.4.1 indicator is three years. But in this way we can monitor the availability of data on an annual basis since it is a very brand new indicator. We can oh sorry we can identify changes and get the data points through the years considering also that often we do not get many data especially now that we are at the starting phase. Assess the country needs in terms of capacity development. For example, technical assistance and training on SDG 2.4.1 exactly how we did for this virtual training. And lastly confirm the national focal points contacts which is always a crucial information for us that we are in contact immediately with the appropriate person. What we have done so far. We have tested the questionnaire in 45 countries through a pilot exercise carried out from December 2019 to April 2020. I'm going to show you the results of this pilot test right after this presentation. Initially the question was only in English. We have translated it in July 2020 into three official UN languages as Fander Yahr showed this two minutes ago. So we translated this in Arabic, French and Spanish. Then we have had our first official dispatch as I mentioned on August 10th, two 203 countries including your countries of course. The questionnaire has been sent to the SDG 2.4.1 focal point to the generic SDG focal point and to the head of NSO with copy all FAO offices and relevant people. As I said the deadline for sending the questionnaire back was set to September 30th. The next activity will be to translate into the remaining official UN languages all the documents so in Chinese and Russian. Here it is shown how the questionnaire is organized so it is composed by eight worksheets. We have three introductory sections, the cover page, the instructions and the definitions. Then we have three data reporting sections, one for each dimension that we have seen and we have two supplementary information sections for the metadata and feedback. We are going to see all these three sections in detail in a minute. This is just a preview on how the questionnaire is displayed so you can see here below all the different sheets that are in the Excel file. So let's see in detail these eight sections. The first one as I said the cover page asks country specific information meaning the national focal point content details that I said for us is really a key information for having a smooth communication with the countries. Then there is a page with only instructions on how to complete the questionnaires so it gives also an overview of the questionnaire structure and followed by another page that explains the definition of the key concept and the terms and the international standards used in the questionnaire. The second section as I said is the core actually of the questionnaire because it's where the data are requested meaning where the country will fill the spaces with the data. This includes the three dimensions. We saw the three subindicators for the economic, the five for environmental and the three subindicators for the social dimensions and this is how it is displayed so for the three dimensions. Then the last section as I said it's about supplementary information so the metadata part. Quantitative it collects the metadata on the country coverage on the source of data, your measurements, frequency of data collection and so on. And finally the feedback sheet that is simply a survey with 10 questions that help us understanding if some area may need some improvements. So let me now show you how to fill properly this excel. The first page, the cover page is like this one. You need to fill the column with the national focal point contact details even if this is already been sent to us in the past because this will help us understand if the focal point has been confirmed or if he or she has been changed. About that, these are the focal points details that we have for your countries. So we kindly ask you to let us know if you know if there have been any changes in particular maybe for United Arab Emirates and South Africa. We still miss the nominations and also the focal point institutions. While for Russia as I said before here and Belarus, we know the focal institution but we still need to have the contact names. So especially for these countries we ask if you can confirm and let us know if there are any news on the nomination of the focal points. And for the others please let us know if there has been any change. For the three data reporting sections, you have two columns to fill. So the first columns need to be filled with the values following this criteria. So we ask only one year so you should report the most recent year that is available in your country. The reference that we use is the calendar year from January to December and the third criteria is if there is no data available in your country, you should insert zero if it is not occurring but potentially applicable. While you should state NA so not applicable if it is really not applicable at all. In the second columns which is the notes, you should insert explanations in case the data are reporting using a different national definitions so not the ones described in the definition worksheets that comes before this or if the data reporting using a different reference period so not the calendar year from December to January to December and here also you can specify the exact year that the data are referring to. So if you have filled the first column with the values, here in the notes you write the year. This last point actually applies to this collection cycle since we are not sure for which year you might have data and this is also to facilitate the collection of all currently available data. So maybe for once with the data you might have last year for example the 2015 which is still good for us but it's important to underline it. In future FAO typically collects data for specific years so usually it's the last four or five years and I would say that probably this question will include such options in the coming years once of course the process becomes more established. The meta data section is composed by a table with all the 11 sub-divigators listed and columns where you can specify all this meta data listed here so type of a variable availability union measurement response. And last one the feedback we have six the question with the scale response from strongly agree to strongly disagree and we have also four open questions in case you want to tell us something more in detail and really open questions. That's all for as far as the data collection question is concerned. I will now show you the real so let me the real questioner. Okay so you should see the excel right? I still have doubts because I always get this strange message. Aspandia maybe you want to confirm you see the excel? Yes we can see it. Okay okay thank you because I also yesterday I got a strange message and I don't know what does it mean. Okay so you see all what I said you have this first cover page where as part of what I already said you have also here below the structure of the quest and also some details that might be relevant. So for example our contact details in case you want to tell us something the deadline that was set as I said at the end of September. The instruction the instruction is so comes in this format with some information and also explains the structure of the questionnaire and here in detail you have all the section what they are about. The definition I would say is the longest part because you have really everything that might be useful for you for filling the questions. So when you have any doubt you go here you have for example you see general terms then you have explanation and details on the denominator of the indicator and then so you go down and you have all the subindicators divided by dimension. So you go down you have the second subindicators etc. So you can really have many information before maybe wandering anything specific you go here and you just read and try to find all the information that you want to or you need to know. Then as I said we have these three the economic the environmental and the social they are all they have all the same structures. So as I said you have here the sustainability status that is from the I explained deeply in these two days the unit on measurement of course and then you have the two columns described all divided by the in subindicators. So you have three for the economic and then you have the five for the environmental and the three for social. So it should be quite straightforward. The metadata also is a quite long sheet because even here it's divided by subindicators. So you see the green separate the different subindicators and you have all these different columns where you can insert whatever you have for let us know of course the information available in your country. And finally the feedback section as I said you see you have six easy questions. You can still anyway specify something concerning that question if you want to tell us something more and then open questions including additional suggestions. So in case you want to help us improving the more and more these questionnaires this question. That's all please let us know if you have any questions because this is as I said this is what you are requested to fill. Okay so the next presentation as I said it's about the pilot testing of the questionnaires that we have just seen. So why we have carried out this pilot phase? What were the objectives? So the main scope was to collect test data from 45 pilot countries using the SDG 241 questionnaires. Specifically we wanted to understand the availability of data although we already knew that the availability of data in 2019 would have been low. Assess the feasibility of data collection. Understand the country readiness in terms of existing national statistical processes and availability of data relevant to sustainable agriculture and of course testing the questionnaire itself. So its structure and clarity and finally also evaluate the country needs in terms of capacity development and technical support. As I said especially we organized this training after we have received these results. How we have selected this 45 oh no sorry so as I mentioned the pilot test was launched in December 2019. There has been a coordination and discussion with several countries and we finally prepared the report with all the results in May 2020. Please note that we had some countries that replied after that time so we received the questionnaire after May 2020 and unfortunately they were not part of the final report so we will not see data data in this presentation. So how we have selected this 45 countries as I said? We had four big criteria. Some countries contributed to the SDG 2 for one methodological development refinements. So informal working groups carried out mostly during 2019. These countries were Argentina, Brazil, Canada, Chile, France, Russian Federation and United States. Then other participated in previous national pilot testing so Bangladesh, Ecuador, Kenya, the Republic, Mexico and Rwanda or participated also in national and regional trainings. So Fiji, Malaysia, Vietnam, Oman, Algeria, Egypt, Ethiopia, Malawi, Cameroon, India, Indonesia and Pakistan. Then we selected some countries that are or will be part of the Agris Survey Program or the 50x2030 initiative. These are Nepal, Burkina Faso, Ivory Coast, Ghana, Mali, Uganda, Senegal, Cambodia, Georgia, Armenia and Kazakhstan. And finally there were other selected countries which are Belgium, Germany, Italy, UK, Austria, Norway, Sweden, Ireland and Trinidad and Tobago. Notes that some of these countries just mentioned the ones that are red columns were member of the Interagency and Expert Group on Sustainable Development Goals Indicators. Now let's move to the results of the pilot test. So what we have got with this exercise, I would call this the pilot testing numbers. So we had 32 countries that acknowledge the recipients of the questionnaire which were 71% of the whole countries. We have received 24 countries and questionnaires back. They were filled completely or partially. So this was 53%. So just a little bit more than a half which was anyway quite an interesting result for us. We had 20 questionnaires that were filled with the survey section. I will show you what is about this section in a minute. And the same 20 field questionnaires received with the feedback sections filled. Among the 24 countries that sent the questionnaire back, seven of them provided actual data which is 60%. While the three stated that they didn't have any data for the moment, which is the 7%. I said that we had seven countries that provided actual data and these are the seven countries. So Canada, which will present their experience immediately after my presentation today. We had UK also, Indonesia and Norway that provided quite a lot of data using existing data, proxies and expert judgment. UK also used the anecdotal knowledge. Burkina Faso and Malawi provided one subindicators each and Kazakhstan provided partial data on three subindicators. Other respondents that didn't report any data anyway highlighted some data were available or partially available for some subindicators and that's where unable to report on the subindicators or its subset. Probably anyway in the next years we will get actual data also from these countries. This is the situation of data availability by subindicators. We consider the 24 countries which are the ones that sent the questionnaires back of course. So in general we can see that the data availability is low or partial for most of the subindicators. I would like here to stress the importance to respond with any data you have. Really at this stage it is asked to begin reporting with virtual or even by using proxies as some countries also have done. So you can see that this is really a key aspect for us and in this light it is shown how also the proxy and the partial data are important for us especially as I said at this starting phase. For this pilot exercise we see that in general data is not available. I would say especially for the subindicators in the environmental and the social dimension we can easily see that indeed the least reported are the prevalence of soil degradation, the management of pesticide and the wage rate in agriculture and also the Fias indicator. Possibly and maybe because this kind of information are not usually collected in agricultural services or census and even if some basic data are collected at the country level the 241 methodology requires specific and additional information for the compilation and reporting of all these subindicators. Instead through this chart we can also see that the most reported are the risk mitigation mechanism and the secure tenure rights to land. Here is visualized the specific overview of the data availability of your countries for the 11 subindicators. This of course takes in consideration only the countries that were part of the pilot test. This is why we have here only Armenia, Burkina Faso, Malawi and Oman. So we can see that Malawi stated to have available or partially available data for four subindicators out of the 11 but they provided data only on one subindicators. Burkina provided data on one subindicators and finally Oman stated to have available data for one subindicators but they didn't provide any data on it. In the legend the legend you see also the orange colors which refer to the methodology of clear and the violet colors since of course other countries informed us also to have data available but through proxy which is as I said absolutely a very important information anyway. We will talk about this later. Analyzing the answers given by the countries we managed to understand something more specific about the few of the subindicators. Specifically the subindicators are far out of value per hectare and variation in water availability are the ones where first the clarity on methodology was required. The ones that have low data availability are prevalence of soil degradation where 18 countries did not have data to calculate it. Which rate of agricultural 19 countries did not have data to calculate and Fuduga and the Fies indicated 20 countries out of the 24. All these numbers are out of the 24 countries responded that did not have data to calculate it. Use of agribusiness support to practice apparently is the subindicators where information is available but usually only partially. While for the subindicators then your right to land the data situation is relatively good. We imagine this is due to the reason that the information or land tenure is usually collected uses census. In fact in this case nine countries had actual data and only one through proxy. Let's go now to the short service section. So this section is not present anymore in the questionnaire. So the ones that the one that you have received in August. We use this section only for the pilot phase. It included a series of questions that help us assess the country data collection methods, their sources, coverage, the scope and periodicity, technical assistance needs and so on. As I said 20 countries here responded so out of the 24 that sent the questionnaire back. We have asked if the countries was already reporting on indicator on sustainable agriculture and six countries. So 30% replied that they currently use properties. In particular we had Germany that stated to report to organically farmed agricultural land. We had Italy that said reporting percentage of utilized agricultural area under organic farming and Sweden used the proxy organic area. 100% of the countries stated to have agricultural census in place and 13 will have it by next year. So very soon. 66 countries which is 80% have an agricultural survey in place and 12 of them so 84% will have the next round in the couple in the next couple of years. So we really hope to have quite a lot of information through these census and service in the next years. About the coverage of service and census, nine countries for the survey and seven for the census cover both crop and livestock, other social environmental aspects all together in the same survey. Then we have investigated on the technical assistance needed for producing and compiling the 241 indicator. 70% which were 14 countries responded that they needed assistance. Among them 57% stated to need this assistance in the short term. 36 in the medium. That is one of the reasons why we have organized quite quickly these virtual trainings to respond to these country needs. Only two countries are out of the 23 already received technical support and none stated that the indicator is not applicable for the countries. So which means that the 241 indicator is a very relevant worldwide. Concerning the feedback section here we can see in one chart all the questions asked and they answered through the scale from stronger B to stronger this again. We can easily see that the question number one and the question five where the questions were countries were more in agreement. So we have sent the questioner to the right person and no important questions categories and or commodities were missing. While question number three and question number six where the ones were countries were more in disagreement. So not all the definitions were completely clear and the time required to fill the question was quite long. Finally analyzing the open answers we realize that countries found the SDG 241 methodology challenging in general that they needed more guidance on the conversation interactors in aggregating these aggregating results and in maybe clearly instructions and definitions. We already saw that the lack of data availability and lack of time series country level was quite high. Moreover the countries indicated two challenges of indicators net farm income and use of agro biodiversity support practice. And finally we had some suggestions so which which indeed we took immediate in consideration they were to organize the trainings and we did it and evaluate the possibility of using alternative data sources which is exactly what we have started. So on this last slide we have highlighted some conclusions and next steps. Although the law's response rates and the law availability of data there is a high level of interest from all the countries to implement the SDG 241 and we definitely understood that there is a need for capacity development assistance. Looking at the next steps so underlined in the report of this pilot phase as already mentioned before we have translated the material in Arabic and French. We have completed the first dispatch in August this year and in progress we are still in the face of collecting data making analysis gap filling and quality assurance and quality control processes. We have just finished actually the virtual trainings because you are the third and the last group for this year. We are planning to have other virtual training also in 2021 to cover more countries and we are also investigating already on the use of the alternative data sources. So this is also something that we will complete in 2021. Thank you. I give now the floor to Martin Bourdieu. Martin is currently manager of the agricultural commodity program at Statistics Canada. He started to work at Stuttkan in 1991 and over the years he worked in several programs related to crop, livestock, financial taxation and census of agriculture. He was also manager of the new agri-environmental surveys on farm practices and water management. As mentioned during my presentation a while ago he will now present the Canada experience in the SDG 241 data collection and reporting. Martin the floor is yours. Good day. Stefania I will let you if please you can put the presentation on and this was very interesting actually the what I want to say about I should have it would have been great before we start answering the pilot survey if we had your first presentation because it would I think it would have even helped us to better to provide a better answer but it's never too late because we're still looking at you seen my presentation as a way to improve the reply because in several place we use we use a proxy but we're even if we use proxy we're pretty confident that we had good good we still go good show good result. So even for a rich in terms of data we are statistic Canada is pretty rich in terms of holding and having a census of agriculture every five years and having a taxation access to taxation data for all farms. Me and my colleague from our two department we're responsible for statistics but the the department of agriculture as well who are experts in the in the field of especially the environmental helped me to complete the questionnaire so you can go to the next slide please. So so yeah quickly we'll review the I won't spend too much time because I think the questionnaire itself is pretty well developed we and Stefania actually presentation where showed that today we what what we answer as well is we really want to align with FAO methodology uh even if we have data limitation in some place so for some sub-educator the reason why is that uh we believe that when you start you want to compare results across country whether you're developing country or developed countries it I think it will be quite important to to even if the methodology may not seems perfect but at least it's a good starting point next slide please so you you got all the dimension we already talked about it one of the issue we may sometime add this was all to get the data from farm levels data to an aggregate to a higher level and and even then it's creates some some question as I said the surf let's we're fortunate we have a census we have a farm management survey yeah you can and the periodicity is the indicator every three months for us it would be quite a challenge because the base of the report is really some sub indicator it would be possible almost every year like the financial one but the environmental one will be because it's based on the census of agriculture so even some results were based on the 2011 because we didn't have better scientific information to to report so and so the next one will be able to do it it's after we have a census in 2021 next year and data will be available in in May 2022 so I think and the periodicity of three years for us is won't be realistic and we like the the dashboard reporting the indicator as a dashboard next slide please so yes I said metric so we we basically wherever we didn't have the data we so we look at other data source and sometime I think we have to go what even get satellite data or especially for the land covered data and it's where you can see there's some change that could affect some some sub environmental indicator and diversity I think my next two slides will show you what kind of challenge I won't say yet challenge it it it is for for a large country like like Canada and how to extrapolate survey result to and we always have a challenge to limit response burden so we over the last I think since 2012 we we want to minimize the number of questionnaires are sent to farmers we there they have some time it could be for poll it for it could be from university students it could research it could be from a different level of government so they they they really tired with survey but in general they're good parts spent to to our survey conduct by statistic Canada next slide please so just to still illustrate the diversity of of the like it's a large country but it's not all under agriculture so out of the close to a billion actor we have just told farmland is 64.2 million actor and most it's in the the tree that you see the green it's in the pre in the sand prairie province western provinces the average it's it's actors it's 332 actor per farm but however they're much more larger the farms and the distribution is is quite skewed to the right because we we have many several small farms but very few large farms that contribute to most of the production and in last census we had 193,000 farms next slide so just to give you an idea of the also per region there's different different production that are more important and those are the major two or three production in each in each region so that in itself it it could create some it does create some challenge to report just for Canada next slide please and we're fortunate because we also we have different eco zone and eco region which are similar they basically have similar climate soil type or ideology and vegetation so this is this adding up to the mixed of when you again when you just to show the diversity and when you start to report just for a national result for a national sub sub indicator so next slide please okay so I'll go I go from the I mentioned already that the scope is not an issue was not an issue for us was doable for economic most we have we have data for it environmental we struggle that's why we some in some instance would use proxy and in terms of social also we either use proxy or expert expert knowledge so I mentioned response burden that was a large issue for us and I already mentioned the other point so we can skip this slide I will go quickly to some slide because you already have or heard about the question there so so in terms of the economic dimension of the the first one was the output value character was pretty straightforward to report because we have data every every five years for from the census of agriculture the where it becomes a bit more complicated is the profitability the net net operator income but we're getting much better at at at linking the administrative data source with the with the census of agriculture but again it could there's many change within the five years period when it comes time to missing it's really hard to measure at the farm level the value inventory change or income in kind and depreciation so in that we suggest basically that we should use aggregate that we usually report that at national for national accounts and we use within Canada we divide it into province and territory so we can calculate these and for each of these region and report for national account in terms of risk mitigation that was just a fair assumption because here most farmers have access to credit and insurance and very few unless they're too small they don't they don't take advantage of these these are programming place next please so I mentioned the census what one year after census and spins it start actually since 2001 we have a used to be called farm and farm environmental management survey but now it's the farm management survey it's right right a year right after the census so basically it allowed us to link the farms that we census and then we got other additional question we don't repeat the same question and also we have a mentioned scientist researchers and for this I encourage you to have a look at the the report that's been produced by my colleague from the agriculture department next slide please so here that's the place I wish I probably cut and paste from from the questionnaire because it would have also made my presentation the link between the two presentation easier but between our reply from the pilot and this but you can go to the next one so basically for for different the soil degradation we had different indicator that was we were able to to to provide estimate the again this part we refer to these result refer to we were able to report an actor because we had pretty good scientific observation on on the field as well so but we it's for some region of Canada more than others and then so overall what we reply it was when we we made all these measure that it falls under for soil degradation it was acceptable if we following FAO criteria next one please okay just skip to the next slide please so this question is is basically was also this was actually more straightforward because we we have the question directly on the census of agriculture and the area under irrigation actually the only I would say caution I would put here is that irrigation could change and because from in from one year to the next depending of the condition the climate condition saying that so there's two percent of only two percent of carplan area what need irrigation on more constant basis okay so but it's also just to go back it's also more original it's more relate to some regional issue southern part and in the western western provinces the southern part next slide please okay you can move to the next one so we look all and here it's where we we we use a proxy and we just say okay we're talking here we didn't report in hectares we we did report in the terms of percentage of crop or operation of farm crop farm crop farm crop of farms growing crops and however it's with a bit more time we we could maybe revisit this and just to just to compare our our result will change because by linking the result from the census the census with for example the with the farm management survey we we could probably convert everything into acre but it would just require a bit more resource to do it next slide you can pass this is all in the questionnaire so uh pesticide management same thing we we we assessed that it was accept acceptable again in that case we even I put a question mark under the extrapolation for sure we could do a better job similar as the the one on fertilizer management because it's always based on number of farms but we if we take some assumptions saying okay a farm that's report I don't know use use bio biopesticide or use or remove disease plan uh it does it for all these areas so not just for just for part of his farm so we assume that we could assume that practice is is used for the old operation okay next please thank you just skip agree environmental we don't have that many farms that are officially certified organic and it's and the reason for that is because mainly they they do or the register to be organic they develop their markets and there's a cost associate to keep their certification so it really depends of local regulation and if they need to maintain their their certification of course they would continue but otherwise they they after a few after they obtain it or after a few years they will they will remove their it will stop paying to be certified and but we believe that we can get better and more detail from the agency that's responsible to make sure that these these operation report report the proper for example the uh uh but the challenge we always have to as I mentioned the response burden so um it's some farms are in transition or it's not their full operation that's organic because they want to to minimize their the risk so they they did just to uh either into transition or fully like a part or maybe 50 percent of the land is of their crop is into is organic the other one is not so next slide please okay you can move to the so in terms of wage we we assess this was it was desirable and acceptable uh there's no minimum national wage rate it's it's really at uh at the provincial level lower level of government um and due to our label laws which our rates uh are usually desirable acceptable uh again this is an area where we have access to administrative data and we could probably do a better better job next time to report that that indicator because we know which farms have worker and and we have access to the the wage or what's report for uh what what was given to uh to the workers so yeah um next next slide please food and security um um we we don't measure it in our in the census of agriculture or um um however there's uh there we we've been working at the agency level that's that's can statistic canada there we have a canadian community health survey and if it would be possible to get a better measure of uh by linking this survey with the census of agriculture and the census of population however it's back to the question so how many hectares and if we if once we link all the employees to the farm then it's possible to extract the or derive the hectares next please okay next one please uh security error it's uh basically it's well defined property right in in uh in laws so uh there's maybe maybe in some uh indigenous and religious communities where uh it's not personal property so it's more to the community so so that's why we answered it was desirable acceptable next slide please so so conclusion um and gives a bit more time for a question maybe so uh we we at no age it's it's a great challenge to measure sustainability even when we start the exercise we look at the questionnaire and discuss with my colleague we had some also of the industry or farm organization that we're quite concerned as well however it's uh it does we acknowledge it provide a good framework to start measuring sustainability again the global objective is to have measure comparable across countries so uh to keep that in mind uh even sometime we we may think that no so if we improvise too much it might just be very hard to to compare among ourselves and uh so in some case we did not follow perfectly but uh we're confident that the information provided was was sufficient and um and and but we still we still committed to to continue uh it it does take some resource uh we uh but we still commute committed to continue and maybe uh send another revised version once we had made some some progress of of or or we can report some some of the comparison that where we use proxy and where we convert things into into actor if the the value of the would have changed so next slide please so i just leave my two email i'm i'm not sure which one is working i think the first one is the second one is still working but we're in period of transition where the canada.c is going to not work anymore soon so that's why i left the two so uh just here for question and i could not see if there were any comments on the screen so uh so or okay uh apparently no question thank you everybody again for having participated to this second day of the result training on the stg-241 today also has been a very concentrated day we have seen the last the sub indicators of the 241 at the stg-241 we have gone through also the questionnaires we have seen the results of the pilot phase and finally we have also listened the experience from our canada colleagues we can now conclude the day and i wish you a nice evening and see you tomorrow for the last session so where we plan to have a more interactive discussions you will be encouraged to talk of course not all of you unfortunately but some of you we will be happy to discuss and go in deep on in the issues and plan for each county so thank you again and see you tomorrow okay bye bye bye thank you thank you you You