 the most frequency of the topics. So in this slide, I have the link for global strategy where you can find many information, but also the link for the handbook and others and all the materials produced like the extender questionnaires, clinical learning courses, many other materials on others. It's important to highlight that Agris was developing in 2018. In that time, the requirements or the methodology for the 241 educator was not defined yet. So Agris, the standard model and the handbook do not cover all requirements for 241. That's why we developed additional documents describing how to incorporate in the questionnaires, in the process the 241 requirements and so that Ababa has already talked about these documents that were developed by FAO. So on Agris, we developed two options, two standard options. How to address the 241 indicators. One is attached to the core model, a set of questions to complete all data required for 241. And it means 32 additional questions because the core is very basic and 241 has 11 sub indicators with demand of information. This is one option. Going with that, it could be collecting a single year all the data. And in the same year, we can attach another rotating model, but that's one possibility using Agris methodology to complete the requirements for 241. The second option is to use the rotating models. Because some requirements for 241 are already present on the economy model and the environment model, because we should not have an environment model. So in this case, the key is to add just 13 additional questions in the economic model and 10 questions in the environment model. But in this second option, some sub indicators will be produced in a year and other sub indicators in another year. So the complete report of 241 on the table with all information, the 11 indicators in this case will have two different reference years. One year for sub indicators, another year for other sub indicators. We'll talk about a survey that is developed mainly in terms of crop session results. This is not a big issue. Considering that also to sustainability is more or less a stable, not change so rapidly one year to one. So that's the two options that was developed for using hybrids to work with 241. Okay, now we're going to talk a bit about the 5.3 initiative. There are some questions. Would you prefer to... Sorry, but since I'm sharing the screen, I cannot mute the participants. So please everybody, please mute yourself because Flavio is still presenting. Okay. If you have any questions, then raise your hand. Okay, the 5.3 initiative seemed up to the other side of the problem that the idea is to improve the capacity of the countries to produce the crop stock. So this is in a broader sense. We have different new emergency data, new data required nowadays. But have a strong emphasis on the SDG indicator mainly for zero render, the goal number two. In particular the indicator 221, 221, 241. And also gender perspective indicator 521. So the motivation to implement the 5.3 initiative is really linked to the SDGs. And we have the link for the website in the bottom. We can go ahead and next slide, Stephanie. Not working, sorry. Not working. No, I don't know why. Okay. Okay. Well, as I explained, we are working with some countries in the past already. And this initiative involves three main institutions on implementation. That is FAO World Bank and EFAT. In fact, the initiative World Bank is managing methodological development, EFAT data use, and FAO data production. Also three components in the initiative. And some countries across the pre-approved countries that were involved in the past in the RBCI program. So as you can see, next year, Uganda, Cambodia, Senegal, Nigeria, Ethiopia, and Georgia will be supported by 3.3 plus two new countries. In 2022, Burkina Faso, Malawi, Ghana, Tanzania, Armenia, and Nepal plus five countries. In 2013, Mali, Myanmar, Kenya, plus six new countries. That's the proposal. And so on. Up to 2026, the proposal is that we will cover start working with 50 countries, utilizing at least supporting two or three data collections in cycles. Flavio, sorry. There are some participants that are asking if you can speak a little bit louder. Okay. Okay. Yeah, now I need to do the next slide. Okay. Yes. Okay, you can see that the system proposed for 3x30 is very similar to ours. It's based on ours. Again, we have the core model. But in the case of 3x30, three rotating models are defined. The name change a bit. The first income labor and productivity. In fact, the cover economy and labor. The second, they had the same name that they were for artists, production methods and environment, and then machine equipment and assets. You can see that the sequence on artists is a proposal is a bit different. And in the 3x30, the standard is a two year cycle. And 3x30 has two programs. One is agriculture. That's what you're saying. That's very similar to artists. And the target population are the agriculture of household farms and non-household farms. So non-household sector and household sector in agriculture. So the unit of observation are the agriculture holdings. So we have another problem. Next slide, please. Next slide, please. In this case, we have one additional model, name income and living standard. The focus is live standard as an income of the household. So we have an additional unit of observation that is the household linked to the agricultural holding. And also the target population is larger. Adding non-farm households in the rural areas. In this case, all the kinds of indicators in terms of rural development will be produced. And it will be possible to do analysis on cross-stables relating agricultural activities and more deep analysis of social aspects of the household. This is the configuration of the 5.30. In this case, more or less what is covered in LSNS approach. But with annual production of good or bad data to capture agricultural activity. Well, for produce 2.41, the methodology for 3.30 was finalized last July. So after definition of 2.41, so in this case, all requirements for 2.41 is already included. Thank you very much. I'm sorry, I need to stop you. Because even the translators have difficulties to hear you. I don't know if you have a microphone that you can use. No, it is on. We can hear you, but it's very weak. So be very close to the computer. I'm super close. It's good, but please also the translators are asking not to move. So if you are close to the computer we have a translator. Yes, we have a translator. I'm not aware. Speak like this, it's loud now and don't move. Okay. Yes. We are almost in the end. But as I'm saying, on the 3.30 methodology, the requirements for the indicator 2.41 is embedded in the production methodology questionnaire. The tools developed for 3.30 combined the core and the rotating for different years. And the proposal is collecting all information for 2.41 in a single year. The year that covers also all the aspects of environment and production efforts. I'm not sure. Sometimes it's free, I don't know why. I think every time that I open the chat because I see that there are messages then it's not working anymore. I'm trying, I will manage. Be patient. Okay. Just to show a bit about the different tools for the household sector and the non-household sector where some items are excluded that do not apply for non-household sector. And we have some variation. It depends going to to the field one time a year get information about all the year going twice a year to the field or twice or by season where we have adapt the questionnaire, divide questionnaire on two options. There's post planting and post harvest more linked to the season and other compliments but in any case the requirements for 2.41 are included and I will highlight with red the PME questionnaire that covers 2.41. I think this is the last slide. Thank you very much. Thank you for the opportunity and good work for all of you. Thank you. Great, bye bye. So we move on to the next presentation which is the additional mechanism to measure and monitor sustainable agriculture which is the PROSA framework. We have Natana Warren he's a statistician in our team so the environmental statistical team who has worked on PROSA he has worked in the areas of food security statistics and he has also worked for two years as a statistician at the OECD OECD. So Natana, you have the floor. Did you share my screen, Stefania? If you could confirm that my screen is... Yes, we see your screen. Maybe you need to speak a little bit louder as well. I don't know where is your microphone. I don't know. I don't know. I don't know. Okay. So allow me to start the presentation. So as Stefania mentioned... I'm sorry. The interpreter said that there is a little bit of echo. I don't know if you can manage to remove your echo. Okay. So this is the most clearly that I will be able to talk. Can you confirm that this is okay for... Okay, they said it's okay. Okay. So I will try to speak as clearly as possible. So yes, as Stefania mentioned and I am a team member of the environmental statistics team of the statistics division here at the Food and Agriculture Organization. Thank you both to Stefania and Esfandiar for the opportunity to be able to present the results of this report which is named Progress Towards Sustainable Agriculture. So I would like to start off with some background of the document. First, I would like to underline that the report and the data that is used for this report is not meant in any way to be a substitute for reporting for SDG indicator 2.4.1. However, in the meantime as countries are reporting for the indicator, we thought that it was important to come up with some level of assessment of progress that is being made and the data that is used for this report is based entirely on national level statistics. So that is one of the main differences between the data used for this report and 2.4.1 reporting is that we are using entirely national level statistics here and not farm level data. So the way that this report is organized is that we have classified countries into four different farm system topologies and these are the modern food systems, the traditional food systems, the land intensive mixed food systems and the capital intensive mixed food systems. These groupings were characterized by performing for those who are interested in the more detailed statistical information based on a principle component of factor productivities in which the first quartile was defined as the traditional food farm systems. The second and third quartiles were split in terms of the ratio of land to capital intensive and the highest quartile are the modern food systems. So the characterizations of the different food farm system topologies are that the traditional farm system topology is characterized by low labor and low productivity and low capital stocks. The land intensive mixed topology is characterized mostly due to its higher expansion of agricultural land. Whereas the capital intensive mixed are characterized by higher productivity coming mostly from a higher use of agricultural inputs and the modern are characterized by high land and labor productivities due to high mechanization and access to modern technologies. So the coverage for the report is that we have a set of 16 indicators. You will notice some similarities in the indicators and the sub indicators also for 2.4.1 and I will list those indicators in the next slide. So we have a total of 16 indicators that we look at for the report. These are six social and environmental indicators and 10 environmental dimension indicators. The time period in general for the report to look at progress over time because that's again what the report is focusing on is for most indicators dating back to 1961 whereas there are some indicators for the prevalence of undernourishment for example that the time scope is from 1990 onwards. So the data source is exclusively Fausta data and again the coverage is based entirely on national level statistics. This data was computed at the country level and aggregated according to each food systems topology. I want to mention also that these groupings that are listed here overlap well with those that were defined in the 2017 high level panel of experts on food security so in the report we also have a traffic lights approach to that we use to identify sustainability hot spots. So these traffic this traffic light approach also uses a qualitative assessment in terms of classifying countries and then aggregating them by food systems topology in terms of colors which are also red, yellow and green to each of the pros and sub indicators and the way that we classify the color for the traffic light is either in terms of gains and maintenance of that green or decreases across successive periods. So one gain across one successive period is a traffic light qualitative assignment of yellow whereas if it's maintained for a second period the classification is green and the number of increases across any two successive periods are red. So I should highlight that the scope of the report is crop and livestock production systems. Okay, so this is the list of the 16 sub indicators that we look at in the prosa report. So I'm going to go through every single one of them but as I mentioned they come exclusively from FAUSTAT with the exception of water use which comes from Aquastat which is another dissemination platform for water use in agriculture within FAO. So we have a number of sub indicators which are economic, social and environment and we have them classified in terms of these different themes most of which have one indicator per theme and a couple of themes which have more than one indicator mentioned for them. So these are the indicators. So for example, if you're interested on how the diversification indices are calculated for crop and livestock these are basically genetic coefficients that are calculated in terms of area harvested for crops and livestock diversification index. So those are the indicators that we look at for the report and again focusing on trends over time for each of the food systems topologies and trying to identify those key areas for each food system topology that need to be focused on sustainable agriculture. So I'd like to jump right away to the results. So the report is organized by looking at each of the dimensions and indicators separately. We recognize that the area of sustainable agriculture is very multi-dimensional and that the relationships between the different indicators themselves is also multi-dimensional. Nonetheless for the report we try to focus on specific indicators and trends of those indicators separately drawing at the same time of the relationships or the between different indicators and that's part of why we implemented this traffic light approach so that we can see the multi-dimensional aspect. So we're focusing again on national level statistics across the relevant sub indicators and we believe this provides a first order of complete analysis of progress towards sustainability both in qualitative with the assignment of traffic lights and quantitative ways by looking at the trends over time. So I'd like to highlight some of the key results that were identified for each of the themes of economic theme across all of the typologies. We know that progress has been strong with gross output specialization trends still remaining the most emitting factor. So let me just jump back to gross output specialization. So the gross output specialization is looking at the biodiversity indicators in that it's looking at it's looking at how evenly gross production is distributed across different crops and livestock. So the value of gross production is computed by applying gross production quantities by output prices at the farm gate and we use the Gini coefficient to look at how evenly distributed this output value is across the different crops and livestock. From the land use theme the agricultural land expansion continues to be a limiting factor in the development of natural ecosystems in particular forests. And looking at crop and livestock species biodiversity we know in the report that these two indicators are key to climate resilience in that if you have your less easily exposed to disasters that can affect specific crop or livestock species and that you can be more resilient if you have more diversity across crops and livestock. Another one of the dimensions has to do with the soil nutrient balance indicator. So in terms of the chemical pesticides these both remain limiting factors to agricultural sustainability in all food systems to apologies both at high levels and low levels of inputs. So if we look at the soil nutrient balance indicator for those countries where we are applying for all soil health in that if your nutrient balance is too high it's an indication that we are applying too much agricultural inputs for fertilizers and that it can be a detriment to sustainable agriculture and agricultural inputs that they need they can not be able to apply enough of these agricultural inputs and have too low levels of agricultural inputs. So for both at low and high levels the soil nutrient balance can be a limiting factor. So if I I wanted to mention also one of the things that I wanted to mention if we look at specific food system typologies for example in the report we highlight as one of the examples that land intensive and modern food systems so these are two typologies with four levels of diversification but higher levels of gross output specialization they have their area harvested less evenly distributed across crops and they're more specialized in terms of output value on fewer crops and we noted that this is a limiting factor for these food systems because of higher level of exposure to climate risks. So I would like also to mention and talk about the another section of the report that has to do with drivers of change on the path to a sustainable agriculture so this part of the report was done by our colleagues in ESA the economic and social department of the food and agriculture organization and the section on the drivers is broken down in terms of this combined assessment so there were five steps that were performed to perform this combined assessment there was an extensive literature review there were the quantitative indicators that were identified as well as the drivers as well as the drivers to analyze I wanted to mention also how the drivers will analyze so the drivers of sustainable agriculture were selected through a screening of publicly available global data this was based on this review of literature the reliability and country coverage of the driver indicator as well as clear correlations with the sub indicator proxies so these correlations for those interested more in the statistical methods were performed using a lasso approach which is a least absolute shrinkage and selection operator to decrease the dimension of the indicators that were selected for the analysis and that's how the final selection of the driver and sub indicator relationships were identified the report is broken down in terms of these five dimensions drivers including demographics inequality farm structure global integration and government support to agriculture I would like to at least highlight one of the key results across all of the dimensions for the drivers is that government support remains one of the most important and direct mechanisms available to policymakers to encourage sustainable agricultural development so that's an overall review of the report as I mentioned earlier this report has already gone through an internal and external review and it should be made available soon and I'm sure as soon as it becomes available we'd be happy also to share this report with the participants okay so let me give you now the floor to Martin or Martin finally that we didn't manage to have so Martin is currently manager of the agricultural commodity program at Statistics Canada he started to work at STATCAN in 1991 over the years he worked in programs related to crops, livestock taxation and census of agriculture he was also manager of the for the new agri-environmental surveys on farm practices and water management he will now present the Canada experience in the SDG 241 data collection and reporting so Martin or Martin the floor is yours thank you Stefania can you hear me well do you have a favor to flip the chart for me so I will share my screen okay one second because I was not ready so let me I want to apologize for yesterday I had problems for logging in I could not log in can you see it yes perfect okay so we can maybe go to the next slide I will keep an eye on the if I go too fast just let me know so just slow down so just just put it in the slide show mode yeah I did it okay that's good that's perfect so today's presentation is really to talk about our experience with filling out the questionnaire that we received from the FAO about the educator 2.4.1 and what some approach we took that we tried to follow as close as possible the methodology but some place we with the data we had so we had to use a different approach but we believe it was close enough to express the same to express good result and so that's why I said sometimes we had to use some proxy next slide please yes so the scope we follow exactly what's being asked for the FAO and the same dimension and I'm sure many of you are familiar so I won't take too much time on that slide but go over each one so you can go to the next one so sometimes we had problems with the metrics because of the data that we rely and it was basically the agriculture sensors and sometimes we use also remotely satellite data and then cover data the next slide or the next two slides it will show you some challenge we have because it's a large country and it's a different agro-climatic condition different solid types or eco zone and it makes it makes it difficult to provide a national assessment of sustainability for the old country so each region or eco zone or have different challenge so and sometimes as well so we the extrapolation of survey result was not necessarily a challenge but we want to be reflect of what is reasonable assessment so next slide please so just to show you I could also show like just to give you some stats that's the total land area and farmland is 2 million hectares and it's mainly located in the south part of Canada southern part a lot of pasture land too and size it's over 300 hectare per farm but there are farms that are much more larger than that so it's just and the number of farm it's in the last census 2000 actually it was 2016 was 193 just above 193,000 farms next slide and this just give you an idea of the what I was saying the diversity of eco zone and eco region which are based on the same climate and or the soil, hydrology and vegetation so when comes times to aggregate that national level that's where we sometimes we had problems to reflect the result okay next please so just to show you here the scope of the so basically for the land that was used we had good data crop and right and livestock raise so it was not difficult to assess that the economic usually we had good data source as well to provide the sub indicator result and then until it's where we had to use more and it's where you have the question marks where we just showing that we have to use some proxy from sure the reduction the farm level for us was a challenge because we basically when we answer the question the questionnaire and we always come with that in mind that we don't want to increase response burden farmers I've already had to fill out many survey and many it's not just from the from us the national statistics agency but it could also be from university or researchers so so that's why we didn't want to basically it would be hard for us to justify to have a new survey so basically we want to exploit as much as possible the data that we have available so for the sub team was so it was usually okay where we had also the periodicity of the indicator like ideally three years but for the data source we had it was every five years with basically it's after the census or close to the census year and we're fortunate because we have a census every five years so next slide please so as I said for the economic these are the sub indicator and we use the the it was census of agriculture data so it was pretty straightforward to for the first the value per hectare for profitability was not as easy because we were missing some value in the census and for example we think that it's much easier to do that using national statistics at the aggregate level using national account estimates and risk mitigation this was based on assumption okay you can go to the next slide please for the environmental dimension as I said we had some indicators on the census of agriculture we had the farm management survey and it's done usually five years after the census actually it's last time it was 2017 it was actually seven survey because we had different one for example cattle, one for dairy farmers one for fruit and vegetable farmers so what different surveys and we had also this survey what's really the challenge or what specific it's where you have statistician and working together with the scientists to do to build the survey and it's it's a participate in those developing those survey in the past and it's always a challenge to find a compromise with what the scientists need to do a proper assessment and to build the agri-environmental and skater and not increasing too much the burden on farmers for answering the question. A lot of the answer we provide were based on the report I put here as I said it was a collaborative effort with my colleague at the department of agriculture which is agriculture and agri-food Canada and they had this report and the hyperlink is there so the approach is a bit different than FAO but it can give you ideas of how they measure sustainability next slide please. Here I'm going to give you an example and I'm probably going faster for just checking the time but the soil degradation based on the FAO criteria we assessed that it was acceptable we it's a combined area effect by any of the above four selected threats to soil health and because we had as I said okay you can go to the next slide so I don't need to read so we had an assessment of the area that was under at possible soil degradation so and we're able to assess 90% of lands was very low risk 87% for example I know or change or increase in soil organic matter and salization is a very limited area of Canada that's susceptible to salinization however if you were conduct this the same analysis at the subnational level and for some area or some it will for sure the result will change so what I said that see when we extrapolate at the national level sometime you lose the precision next slide please so water availability so desirable all the criteria years farm irrigation breeding crops is more than 10% of agriculture it remains stable over the years so next slide please so yes and this was easy to measure as well because we do have the measure of crop land area that's irrigated on the census so and so this was relatively easier to measure next slide please fertilizer management so our assessment for acceptable we use the criteria and at least we were able to for at least to measure if you go to to the next slide I'll show you exactly the percentage of so basically what we were able to measure is that and now I'm talking about percentage it's where here we're taking I would say a shortcut because we measure the percent of crop operation of crop farms instead of the actual actor that we're under using a recommended rates and so it's the same for percentage of for feed crop that applied liquid manure and so on so in those those and or sub indicator we basically use the the number of operation that we're using the practice next slide please I will go quickly over those because you've seen those in the FDFA questionnaire and again fertilizer pesticide management is it's no different than fertilizer management management you can go to the next slide so basically we use as a proxy we use the number of operation that add the for example they were rotated crop or used bio pesticide and so on so and sometime is it the question just the question mark here is like when we say okay if the for example when you come to 35% of operation with this systematically remove disease plant for these farms can you extrapolate those results to the to the old farm that was always a debate we had then it was like we assume we made the assumption that if the farmer reported practice or then it was likely for the related crops or livestock so next slide please I grew bio diversity so again so you can go to the next slide so just to go so we have few farms that are certified organic doesn't mean that the those that are are not representing a large area but most most likely are usually in the fruit fruits and vegetable but we also have green operator and so it's more and more popular but again some what we don't have is we know if they're associated or they're certified but we don't know the number of livestock or the number of acres or which crops they're the so sorry read someone you can go to the next one okay for social dimension we we wage rates so so where we we're saying that there's no there's minimum rage it's available but there's so it's it's it's not different it depends of always something done have a question here the in that case we haven't done the sampling we just based on what we go to the next slide please we just we just said that there we have minimum wage already we have labor statistics and basically we have laws and it's so it's false it was really either under desirable acceptable it was more qualitative assessment and actual measure and because also it's difficult to link for each director food and security that that's a difficult one as well so next slide please so we for example we have a household survey that's based on like Canadian Community Health Survey and it's possible to link that with the census of agriculture and make those linkage but when you start to link household survey and to the national it's we have a very small sample so again we we know there's some food security but we didn't really the resource to pursue that so next slide so so in terms of tenure rights to land again it was more qualitative assessment because we know that pretty much if not all have a formal documents for ownership or right for property and sometimes it could be a community but there's always some rights to land so next slide please so it's well defined so there might be some cases in indigenous or religious communities where it's not associated to personal properties but it's more for a group so but in general we feel that there's no it was desirable acceptable that was our assessment so next slide please okay so just in conclusion I know that would go a bit fast but so we know we recognize it's great challenge to measure sustainability we so we we know that sorry that the FAO develop a good framework to start measures measuring sustainability it's of course we have the objective to be comparable across countries which is where the challenge I think rely because it's we don't have all the same resource and measuring sustainability for developed country versus developing countries it's quite so we're glad that FAO actually provide that framework and also we are quite confident about the information we provide even if we had more time or we have more resource to spend on it we thought that using proxy measure was close enough and we probably would get about the same assessment if we were going into more using more efforts to measure the different sub indicator so that's it so this is my actually it has changed I think over the weekend it's that can but if I would provide it to Stefania so for an update version of the presentation so now let's go to the last part of this training which is the more interactive part where we kindly not ask you not to use the chat box anymore but we will be happy to listen your voices and of course we just ask the lead representative to talk because you are really so many people today we have 127 so I leave the floor to Asfandiar we would like to have like a sort of round table where each country says his experience we would like to know your expectations your issues so more in the discussion point and in that moment we are going also to answer the two questions that were left over so I leave the floor to Asfandiar so just give me second okay perfect so thank you so over the course of the last two days we discussed the conceptual and mythological basis for SG-241 is data collection instruments and tool and mechanism for reporting it to FAO in this presentation we will cover the progress made by FAO until so far our planned future course of action and expectations in terms of its readiness to report on the indicator in the short, medium and long term our ultimate goal obviously is to maximize country reporting on this indicator and thereby gradually classify it as TR-1 over time in summary we will cover the following aspects so methodological front capacity development aspects data collection and then reporting of the indicator to FAO towards the very end of the presentation as Asfandiar mentioned we will have an open discussion around the constraints that impede country's implementation data collection and reporting efforts and deliberate the means and ways on how to overcome these constraints so by now you may have a very good idea that the methodology of 241 is based on FAM survey that is used as a main data collection instrument for all the sub indicators reaching at this stage where the methodology is now whereby it has been approved and endorsed by the interagency and expert group on sustainable development goals has been a long process of discussion with experts several rounds of testing and follow up technical work on the development of the support of the support document so in this respect we organize three expert group meetings we carried out regular presentations at scientific advisory committee of the global strategy to improve agriculture and rural statistics we also carried out online global consultation whereby when we were developing the methodology at one stage when it was stable enough we shared it with the national statistical offices of all member states and we invited their comments on the framework we incorporated and took into account all their feedback and then we conducted two or three webinars on the methodology secondly as I was mentioning throughout my presentations we tested the methodologies at different stages of its development so we conducted studies in Bangladesh, Kyrgyzstan Republic, these tests were conducted back in 2016 and 2017 then we carried out cognitive tests of the survey questionnaire in Kenya, Mexico and Bangladesh and then we carried out a full-fledged field test whereby we collected information from the agriculture holdings which I mentioned to you the sample was 420 in Bangladesh back in 2018 and 19 then lastly we carried out our data collection questionnaire in 45 countries that Stefania showed to you yesterday but unfortunately because of shortage of time we are not going to be able to show you the findings of those test results but we will happily share the presentation with you that is already sent to you but we are going to make sure that you have that presentation now all the background and relevant documents we will accompany the methodological note and the survey questionnaire have been we have been talking about that those are now finalized and uploaded to the FAO STG portal which I was showing you yesterday on the FAO STG 241 page where towards the right you will see all the capacity development activities and all the relevant documents that we have so these include as I just mentioned the methodological note, the survey questionnaire which will help you collect information from the field the sampling design document, the enumerator manual and the calculation procedure and other related documents now on the capacity development front more than 50 plus countries have already been trained on the indicator methodology so on this particular in this particular area whereby we not only conducted capacity development but we were undertaking advocacy as well for the indicator at various events and forums so we presented the indicator at African commission on agriculture statistics back in 2017 the indicator was presented at FAO committee on agriculture in 2018 then it got presented at Brussels briefing at European commission in 2019 and then at international conference on agriculture statistics in India 2019 we also conducted bilateral training in Bangladesh, Vietnam and Oman whereby we went to the country we sit with the national statistical office and the minister of agriculture staff we went through the methodology in a great detail and now most of these countries like say Vietnam is interested in further testing the methodology in its selected districts Oman is very much interested in further collaborating with us on implementing SDG 241 questionnaire in Oman and Bangladesh which was already a test country so they are also keen on adopting SDG 241 then we trained an African country in collaboration with United Nations Economic Commission on Africa and with the Ethiopian Minister of Agriculture I'm not going to go through the list of these countries but these were the 10 African countries that were trained on the indicator methodology then 17 countries from Asia and North Africa were trained in 2019 and likewise 18 countries from Asia and Pacific were trained on the indicator methodology we feel very glad to be with you to be with a group of countries from Latin America and Caribbean region because this is really the very first opportunity for us to engage with Latin America on 241 more formally previously most of your countries because Ecuador, Argentina, Mexico, Brazil, Chile have been collaborating with us on the methodological aspect when we were developing the indicator but this is really the very first instance whereby the national staff of these countries is getting trained on the indicator for the first time we are really pleased about that then in terms of advocacy and capacity development this year as I mentioned to you in my previous presentation we already conducted a three days virtual training for group one which included predominantly Asian countries from 8 to 10 September you were the second group of countries that got trained on the methodology and then on the third group this training will happen in October for the rest of the Middle Eastern and Asian countries and some African countries sorry African and Middle Eastern countries additional the activities that we have carried out up until so far the e-learning courses I mean you are already aware of that I mean we not only have the e-learning course for 241 but for many other STG indicators and beyond STGs on many other topics so I always will encourage you to go through that course and you know it's a very nice resource for you to learn more about not only STGs but other important areas that you work in we have translated the key documents into Arabic, Spanish and French there are many other documents that still need to get translated but hopefully that will be available soon we also you know always leveraged and capitalized you know on our in-house colleagues country missions to raise awareness about STG 241 and you know these missions also helped us confirm information on national focal points and assess national availability on STG 241 in 2021 next year we will continue to provide virtual trainings amid COVID-19 because of the travel restrictions we cannot engage in more bilateral in-person training so this is the only way for us to deliver training and provide technical assistance so we will continue to do that hopefully the situation will get better and maybe we will in-person come to your respective countries to help you and support you in implementation of 241 as I mentioned we will translate all the documents including the e-learnings into all official UN languages and we are also planning on developing digital lectures on STG 241 in 2021 whereby you know all the necessary steps in terms of how do you take data once it's collected how do you process it analyze it and then construct the sub indicators so these lectures will also be available in 2021 now in terms of data collection the FAO data collection questionnaire and reporting protocols have already been developed we have been showing you that Stefania presented as to what was the structure of this questionnaire yesterday the following activities regarding to the data collection have already been accomplished or completed with other planned in 2020 from December 2019 to April 2020 we tested 45 countries which I previously talked about you are going to have the presentation with you on the findings of the tests in August 2020 we sent out a comprehensive dispatch of the questionnaire to all member states so hopefully you know your national statistical offices and personnel related to STG 241 have received that questionnaire for them to fill it in and send it back to us by 30th of September post from September to November we will obviously continue to collect information and then we will start analyzing it filling the gaps and will carry out the quality assurance and quality control process in December 2020 we will draft analysis and finalize you know the report for United Nations statistical division now the reporting to United Nations statistical division or UNSD will be conditional on sufficient data being reported by countries to prepare story lines and construct global and regional regional aggregates and trends we will repeat the data collection cycle that is preparation of the off and dispatch to countries of the questionnaire we will repeat the same process of analysis gap filling quality assurance and quality control and then we will draft analysis and finalize it for reporting to UNSD now remember one thing we don't expect countries to be reporting every year on 241 the reason us being reaching out to countries every year is that maybe they currently they have information available on the subset of the sub indicators maybe 3 out of the 11 or maybe 1 out of the 11 and next year they have another indicator on you know already constructed and hence you know it will be it will be a process with the country so that we are engaged with them we understand as to what their problems are and then we you know provide support as we move along during this process now the first formal reporting to UNSD on this indicator will be in in 2022 for the entire globe now one additional point that I would like to highlight that there you know we we sent out this we carried out this pilot exercise for SCG 241 between December and April but you know we we received very low response rates and these were both expected and indicative showing the complexity of the indicator in the lake of data at the national level now as I mentioned you know in the previous slide what are the short term expectations as FAO is basically that we we expect that country will be reporting on the partial dashboard of 241 based on farm level data so we don't expect countries to be reporting on all the 11 sub indicators okay so even if you report on one or two even that is a very good starting point for the 11 sub indicators for which maybe methodology is not clear or for which maybe further capacity development assistance is required or maybe more data needs to be collected on those indicators so we can then prioritize indicators depending on what issues are you facing at the country level but at least you should start reporting something you know as for the 11 sub indicators are medium to long term we are going to develop the alternative data collection methods as a practical solution to enable and improve reporting on sg241 the current methodology is around farm survey now this is an alternative mechanism which we are going to develop okay you know from the Canada example it was very obvious that there will be different sources of information to report on sg241 but we want to have a formal guidelines and practical guidelines which are approved by the United Nations statistical division and the IAEG STG before we recommend it to countries because it's going to be an international standard on top of farm survey so it will be you know we will offer different solutions to country the countries who have a very strong agriculture survey system in place they can use that to report on 241 the others who don't have a very strong service they can use alternative data sources to report on sg241 or maybe a combination of these all in parallel we will we will continue our outreach and capacity development support to countries in close coordination with obviously with 50 by 2030 initiative to collect information on sg241 so this is the slide from the previous from the yesterday's presentation whereby I mentioned that basically many other sources of information can be used or leveraged to report on these indicators now how to use these different sources of information administrative data this is the approach which has already been developed now environmental monitoring systems GIS and remote sensing household surveys others how can we use these for countries to report on sg241 this though is indicated in the methodology but it is not developed fully and this is the stream of work that I was talking about in my previous slide now the use of alternative data sources to report on the selected indicator of sg241 may seem intuitive and may seem cost effective and may seem very appealing and attractive however both technically and operationally it is not as straightforward and involves several challenges to be addressed before its use so many countries have been saying no we want to use our existing sources of information but how can you use the existing sources of information then it becomes really very complicated and challenging now the actual problem is that these alternative the way the sg241 sub indicators are designed we are not only collecting data on the indicators but we also have you know basically develop these thresholds to assign sustainability statuses so the moment you shift away from form survey which through questions and then through combination of some criteria depending on the fulfillment of those criteria within assigned form sustainability status like say for example of the eight measures that we are dealing with so if it's complying with four it's green if it's complying with two it's yellow if it's complying with zero it's red now if the moment you go to GIS how do you then you know basically come up with these thresholds based on which we will be assigning you know red yellow and green statuses to the agriculture area of the country and hence it becomes difficult so and the problem using existing data sources sorry form survey and there is another country which is using alternative data sources how then you compare those results are those results consistent you know with each other will it tell a different story will it capture you know an entirely entirely different will it come up with an entirely different assessment so these are the issues and challenges that we are dealing with now now these may have different objectives scale of assessment scope and definition so not all the alternative data sources have the same you know not on not all are nationally representative or maybe their scale of assessment is different or maybe they are only covering crops or maybe this study is only for for livestock and maybe it's using definitions which are not internationally recognized plus or resolution and periodicity of the data set so if this is an ad hoc study which was conducted back back in 2010 and there is no repetition of that study then those dated estimates from the past unless those are updated are useless because we cannot use extrapolations and interpolations and coefficients or growth rates for us to you know basically come come up with the most recent estimates so this is an additional problem with alternative data sources sampling issues differences in design size under and and non coverage or you know so if if some country says that basically decent work wage rate in agriculture we can compile this information using labor force survey so then you know what is the coverage of that labor force survey that we are covering very well the agriculture sector is the agricultural sector well represented in that survey can can you know by taking information from the labor force survey can we can we generalize it for the entire country so that that's another question then different unit of measure so in case of farm survey because two for one talks about farm or farm holdings and then it talks about agriculture area because we are assigning sustainability statuses to the agriculture area of the country so if there is another survey for which the unit of observation and measurement is different how do you then you know basically relate or associate that information with farm with the agriculture area so that's another major challenge which needs to be taken into account so and then adjusting and harmonizing different baselines across different countries some countries may have a baseline of 2005 father country may have a baseline of 2015 how do you how do you adjust for that across different countries and across different alternative data sources and then integrating data from different data sources is also complicated it's complicated because there is a lack of an efficient mechanism for and coordination so let's say for example the production prices related data to agriculture is usually collected by the national statistical office or Ministry of Agriculture but the information related to environmental aspects maybe is with some other department right so so the moment you you steer away from one single data source which is farm survey which is easy because it's under the custodianship of the national statistical office and you are using a single tool periodically and you are going to the field and collecting data on all the elements of indicator by administering a set of questions but the moment you go to alternative data sources then we are talking about different institutions so you need to build that coordination mechanism and then we are talking about different institutions for for country to be able to report on on the 11 subindicators so that's that's another another major point that that needs to be taken into account so alternative data sources let me highlight this point once again maybe very appealing may may may may appear reasonable and cost effective and practical but there are numerous challenges because you know it's it's it's not a very good question yet again and and usage for sg2 for one reporting now as I mentioned earlier alternative data sources can be used though you know but then the following criteria needs to get fulfilled which I was which I explained in my previous presentation as well so the the first criteria is the alternative data sources should give the result of at least same quality So this is one, and there could be many instances whereby, like say for example, alternative data sources may be of a better quality than farm survey result, especially for the sub indicators in the environmental dimension. But then again, how do you make sure that you are capturing the same phenomena? Because like say for example, if you use GIS, the problem is already there. It will show you the extent of the problem. So it will give you an entirely different spectrum of yellow, green and red, then if you go by farm survey approach. So this was the case when we were discussing it with Belgium. So, so, so we, you know, based on our discussion with them. For the GIS, the results were shown entirely different for a given agriculture area than then as opposed to farm survey approach. So, you know, you need to be careful about that too. As I mentioned, it can be attributed to agriculture land area in the country, considering the different farm typologies and agriculture regions. So if you cannot relate the information collected through administrative records through land registers to the agriculture area, then you know that information is useless because you cannot say anything about the agriculture area as to whether it's sustainable or not. Then it can be associated with the country agriculture production systems, particularly crops and livestock are a mix of both which is the scope of this indicator. So if there is a study which is particularly focused on livestock but it's not covering crops, then then what I mean you are capturing one aspect but you are not going into another and hence the information will be collected, but it may not be sufficient for you to report on that particular sub indicator. And I explained this one capture the same aspect phenomenon as a proposed farm survey approach are representative of a situation at a national level with respect to agriculture land area. Okay, this is a very interesting, you could have maybe certification systems you could you can maybe have some kind of studies conducted for a certain, you know, region or a certain agro ecological zone of a country. So how do you, how do you then generalize the results of those surveys. So that that's another issue. So how do you make use of the information which is not national representative. And lastly, you know the alternative data sources before it use needs to be compliant, both with international, as well as national standards and classification system so that you know the estimates, once, once derived by constructing the indicator should be internationally comparable. Again, we are in SDG process we are in a universal process. So, for us to compare countries we need to all country needs to follow the same standards and classification system so that, you know, we can we can compare and contrast countries. So, as I, as I was mentioning, there, there was a large interest from countries that we still would like to use alternative data sources and though the methodological note of a C241 is providing some kind of, you know, indication for country to use it, but it doesn't go into the details on how to. Okay, so, so this is why we have started this program of work on alternative data sources. So from October to December we have already started working we have on boarded experts who are going to help us work on the further developing this approach to begin with we will start with remote sensing. So remote sensing or Earth observation, and then we will see as to how can we use, how can we make use of remote sensing GIS or Earth observation to report on some selected subindicator of 241. There are many subindicators which still for for those information will still come from farm survey, like say for example for land productivity for profitability for resilience for for maybe decent work in social dimension, because farm survey is better suited to collect that kind of information at a farm level but you would still need to use farm survey, but then again, for some of the sub indicator like say for example, water variation in water availability, fertilizer pollution risk or pesticide pesticide risk or, you know, biodiversity. So, can be, we have some loose ideas we are not yet sure as to whether we can use remote sensing to basically construct those indicator, but that's the plan that basically we will develop this approach. Then, our plan is to expand this effort, not only to, you know, in not only to focus only on the remote sensing, but explore other data sources which I just explained on the previous slide so apart from remote sensing. How can we use administrative records, how can we use livestock and, you know, agriculture senses how can we use make use of monitoring systems, how can we make use of household surveys on top of remote sensing for for for for it to be used as an option to report on 241. Of course, soon after we will develop the test protocols and then select test countries to compare the information, you know, collected collected to Earth observation with a be the farm survey approach, because we want to compare and construct the result of these two approaches. So once these are so we will then select test countries, and then we will triangulate the farm survey and earth observation and other sources of data to see as to whether it makes sense, right. And once these are tested, we will draft these guidelines on how earth observation other data sources can be used to report on as you do for one. And finally, these guidelines will be ready for dissemination to countries hopefully by December 2021. Now with this, I will, I will, I will take a pause if you have any question and then we then we go go to the open discussion around SD241. So thank you. Thank you. I don't see any question, but I don't know how are you going to translate those. Those discussions you're having. Yes, of course. I would like to know if there is anyone, let's say, a little interested in talking first. Okay. Okay. Then, I would suggest a Spaniard to answer the question from maybe Ricardo Salas from Costa Rica. What do you think? Yeah, no problem. Just to break the ice. The, the one which you sent me in my email, right? Yes, exactly. Okay. Do you want to quickly say the question and the answer or do you want me to read all? I'm gonna, I'm gonna do that. Yeah. Just give me a second. Okay. So the question. Okay. So the question was actually that. So this was from Mr. Ricardo, right? Yes. Okay. So the question was, I wanted to tell you in our country, Costa Rica, we have area and production data for at least 70% of the crops. However, we do not have it limited if it is a sustainable farm or a farm that does not use this type of tools. And of that we have data, it is because they are specialized institutions for many of them. For example, Corbana that analyzes the whole subject of banana. A great effort is being made to have registration system for all producers where they indicate the area produce but it does not analyze the production issue. And it is still in pilot testing. Now to complete the questionnaire that you have considered this type of situation in the countries. I have been left with this concern since many times we do not have the resources to be able to monitor all the farms, whether sustainable or not. We take data for example on irrigation agro chemicals, among other aspect that the indicator analyze in its matrix with the subject of sustainable farm. So look, this question is very interesting. Now there are two things. We showed you the methodology of SDG to for one, we showed you is conceptual basis. We showed you that the methodology is structured around or designed around farm survey. Now, for, for you to estimate sustainable agriculture or for you to estimate like say for example an aspect of sustainable agriculture. So one of the of the 11 we which we listed. You need to, you need to make sure that the key ingredients, okay, or the fundamental building blocks of that particular sub indicator aspect are integrated into your current agriculture statistical system, this is a must. But you cannot report because without a recipe you cannot, you know, maybe prepare a meal. So for you to have your recipe, you need to have your ingredients to you need to have those ingredients. We are telling you these are the ingredients and this is how this is the recipe on how to prepare you know as you do for one meal. So from this perspective, unless you have the ingredients, and unless you have the recipe, you cannot basically going to be able to report on SG 241. Now having said that. We need not to monitor and collect data from all farms for you to be able to estimate 241 at the national level. So we, we are not advising countries to do complete enumeration of all the agriculture holdings, and then collect data from the exhaustive list of whatever exists at a country level. So it's not a census approach. Okay. So this is in fact a standard survey approach that we recommend, and it's based on and said nationally representative sample. Okay. So, so again, let me corroborate complete enumeration and coverage of farm farms is not required, you need to have a rich enough sample, a sample which is representative or a subset of the entire universe of forms to be able to estimate the 11 sub indicator. And this is this is a cost effective approach, which is easy to implement. Now to elaborate further, unless you have incorporated the data items and variables needed to construct the 11 sub indicators, you won't be able to report on sustainability. So in the first step, you need to look into your current agriculture surveys map it against the requirement of SG 241 to see what is already covered and what is missing in there. Once the missing questions are included in the current agriculture survey, only then would you be able to construct the 11 sub indicator using the farm survey approach of SG 241. Now, if your current surveys are limited in scope, okay, are focused only on certain crops, but not others. Then you know this is this could very well be an opportunity for you, the SG 241 could very well be an opportunity for you to improve your entire agriculture system, because you still need this information to for you to make informed policies and decisions at the country level. Now the SG 241 data is not only for 241. It has many other usages as well. Like say for example the information that you collect for the productivity and the profitability indicators, which is on revenues and on cost of on cost of production. So the information is not only going to be used for 241, but it's going to be used for SDG indicator 231 and 232. So two other indicators, plus the same information is used by countries to, to prepare national accounts to prepare, you know, the gross value distribution or gross value added of agriculture in terms of its contribution to the GDP. So you still need those figures for you to estimate your gross domestic product. SG 241 is giving you an additional incentive for you to basically improve your agricultural statistical system. And mind you, I mean, so many aspects are covered by SG 241 in a single framework, which is, which is, which is going to give you an extra strength in terms of, you know, the national statistical office or the Ministry of Agriculture, Ministry of Environment, whichever institution you are representing to, to improve on, to improve on your policymaking. So I would say that basically, if there are scoping issues with your current surveys, the scoping needs to be improved if there are coverage issue in terms of if there is under coverage that needs to get improved. There is an issue whereby you don't collect information on certain aspects of the farm, like say for example agrochemicals, imports, prices, then that, that needs to get improved. So you can have a very, you know, fruitful discussion with your, with your high ups or with your, with your superiors that look by implementing 241 we are not going to only be reporting on sustainable agriculture. Okay, but, but also, you know, we are going to improve so many other processes. And mind you, it's not about reporting on the SDG indicator. That's not the, that's not the idea. This should be clear to all of you. The idea is to improve your national policymaking so that your agriculture becomes more resilient and more sustainable over time. Okay, thank you. I think you answered very precisely. We don't have any new questions. So I'm just asking Mr. Martinez, I think we have answered your question from yesterday about the complementary data. So I'm not going through your question, but in case you have any doubts, you can ask. I mean, we had one comment from Valeria Hamas, Brazil, I don't know if you want to touch base also on this question about getting out of their trainings or want to answer maybe later. Okay, so let me let me take this up. I mean, we would, we would like you to reach out to us more formally so please write to us, please write to us. Maybe we want to read the question so that everybody understand. Okay, please, please do that. So will it be possible to carry out other trainings of multiple, multiple multipliers like this, using this material and audio visual resources for researchers from the ODS and Panada network, for example, our network has 885 researchers who work in agricultural research. So yes, primarily let me put it this way, us as FAO as a UN agency, we have a mandate to produce global public goods. Okay, and by global public goods we mean to say methodology standards and classification systems that are in open source, which can be used by countries by country experts that you know from the National Statistical Office or policymaker from the Ministry of Agriculture, but as well for for for researchers for academia for for for many other experts belonging to different disciplines and walks of life. Now, our mandate is to engage with countries so we are bound by our by our charter to work closely with country representatives for us to improve their agriculture statistical systems so that they are able to make well informed policies and hence, in the process, it will help them reduce poverty, eliminate hunger and, you know, eliminate hunger and malnutrition. So from this perspective, we have a very defined mandate in terms of whom we can whom we can provide capacity development assistance to or are basically provide support support to both technically and monitoring terms. But having said that I would we would like you to reach out to us more formally via an email and then we discuss it internally here with our with our, you know, superiors. And once we discuss that then we will think about what means and ways on how can we better support better support your your network or your consortium of researchers. Okay, very good. We have one extra question from Mr Pablo Gallo Mendoza and then maybe we can leave the open discussion we start the open discussion. The representative sample is based on the sense of sampling frame. I don't know if the question is based on. That is what he said. So the representative sample is based on the sense of sampling frame. Yeah, yeah, so of course I mean senses, senses serve as a tool for you to derive your frame for sampling frame form from okay. So the most updated senses can be used if if it if it if it is a complete enumeration of all the agriculture holdings at the country level. And you can use that to derive the frame for your agriculture survey for you to have a nationally representative estimate so yes, a national senses can be used as a tool to derive frame for for for for your agriculture survey. Now, I mean the frame would already exist at a country level for you to agriculture surveys, all you need to do is you have to look at the let me just quickly show that I mean Stefania before I forget. This is very important. So I was, you know, yesterday I went through the. Okay, so this is the survey module that we have created for for for SDG 241, and it is created as both as an independent survey, as well as, you know, questions from here can be integrated you in your current agriculture survey. So in this, in this tool which has been translated into Spanish has all the required information that you need for you to be able to report on 241. So you will have a look at that, and you have a look at your current agriculture survey, and then you see as to where you know which questions are missing. So from here you just start integrating those questions into your agriculture survey for it to be SDG 241 ready. So as you can see here, we have a section one on introduction of the survey module and identification of the holder and the holding. We have this introduction introductory section, because in many countries agriculture survey doesn't exist, or if it exists those are purely production surveys, okay, they don't ask about the environmental aspects of the of the of the of the holding. So, you know, for those countries if they want to implement a separate survey for SDG 241, they can they can take this and implement it for other countries we strongly recommend to take questions from here and integrate it into their, their current agriculture survey. So all the information, you know about the identification of the holding, then the area of the holding which we spoke about land tenure land use, common land, etc. Then economic dimension of the holding so this section will help you collect information on the on the three indicators in the economic dimension. I remind you with this with this tool with this survey questionnaire. You have all the supporting material which I talked about numerator manual calculation procedure sampling guidance etc. So all this is linked to that. Then you have a section on environmental dimension of the holding so it has all the questions that will help you collect information on the on the five sub indicators for the for the environmental dimension. Similarly, you have the the section on the social dimension of the holding, and it has all the question that that that that will help you collect information on the three indicator. So let's say for example, the first sub indicator and the social dimension, all you need to have is two questions integrated into your, your current agriculture statistical survey. And mind you usually the information on on labor is already there, you only need to have maybe one additional question there. Okay. Similarly, for for land tenure this this this information is usually collected in an agricultural survey or senses, all you need to make sure is as to whether this kind of information is already provided there if not, you just take maybe a question and just from here and plug it in there integrated with your current agriculture statistical survey and and and then you are good to go so you will be able to report on one indicator. So all the groundwork all the basic work has been carried out. All you have to do is please, I would insist I would encourage I would appreciate if you go through all the material that we have shared with you. Have a look, you know, compare it and benchmark it with your current agriculture surveys, or other other sources of information that you have in your country, and see as to what's there and what's missing, and then reach out to us and ask us. Okay, fine these XYZ question is missing in my survey, how we can incorporate this where can we incorporate this and you know how we are going to go about administering this question within the context of our agriculture survey. So this is this is this is I wanted to show this I mean you already have you already have it, but we will happily share it with you once again. Okay, it's time to officially close the second round of virtual training on the SDG 241. I would like to thank officially Alda for her precious support at the time of the organization, and also during these three days, she has been really crucial for the smooth running of the training, especially during the so active sessions of question answers. Thanks a lot of the translators, Jasmine and Andrea, they were they have done a great job and translated everything very professionally and carefully. I'm fine finally I think I can thank us on behalf of the of all the participants. We have got so many messages that you have carried out a training in the perfect way. I'm just trying with passion to see how to see how to be ex exosciently to all questions. And the last but not least, thanks to all of you for having participated in this round of virtual training. I hope you enjoyed it and that we have helped you gain a clear understanding of the methodology of the 241 indicator. In the end, in this extraordinary circumstances with the pandemic allowed us to train more than 150 participants, which is for sure something that would have been very hard to achieve in a in a with an in person training. I leave the floor to a span yard for the last closures and then switch off switch on all the camera please so we take a photo all together. So thank you, Stefania. Thank you all. Thank you. The translators especially I mean they they are sitting even late today so thank you very much to the interpreters, and thank you to the esteemed and respected participants thank you for your patients it was a very complex very tiring, very intense course. So thank you for your patience, and for for making yourself available. The journey doesn't stop here, it has just begun. So basically we would like to carry forward this collaboration with the Latin American countries, Argentina, Peru, Chile, Brazil, Colombia, Costa Rica, Ecuador. Forgive me if I forgot any name, it's not on purpose it's not on intentionally, but thank you very much to all of you, and we would definitely like to work more with with your countries. Thank you so much for coming to us, and officially, so that we can engage with you and take this forward. One step, one step more, so that we are able to jointly basically defeat hunger and eliminate hunger and malnutrition everywhere, including your countries and you know from the entire globe. So thank you very much. Please smile so that I take several pictures because we are quite a lot. It's not easy. Okay, I took the first picture. Let me go to the second. In the meantime that I take the pictures of course, just to say again we will answer all the questions that were not answered during the training I have taken notes of everything so don't worry, you will be answered and we are always available for extra questions. A few seconds please. Okay, last question. Last photo. Okay, done. So thank you again. We will send a report and summary of this training and all the materials as we have promised. So you will receive everything probably tomorrow because here it's already 8pm. So it's time for us to rest and for you to of course have a nice day. Bye bye.