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Black soils, which play an important role in agricultural production and food security, are well known for their relatively high content of soil organic matter (SOM). SOM has a significant impact on the sustainability of farmland and provides nutrients for plants. Hyperspectral imaging (HSI) in the visible and near-infrared region has shown the potential to detect soil nutrient levels in the laboratory. However, using portable spectrometers directly in the field remains challenging due to variations in soil moisture (SM). The current study used spectral data captured by a handheld spectrometer outdoors to predict SOM, available nitrogen (AN), available phosphorus (AP) and available potassium (AK) with different SM levels. Partial least squares regression (PLSR) models were established to compare the predictive performance of air-dried soil samples with SMs around 20%, 30% and 40%. The results showed that the model established using dry sample data had the best performance (RMSE = 4.47 g/kg) for the prediction of SOM, followed by AN (RMSE = 20.92 mg/kg) and AK (RMSE = 22.67 mg/kg). The AP was better predicted by the model based on 30% SM (RMSE = 8.04 mg/kg). In general, model performance deteriorated with an increase in SM, except for the case of AP. Feature wavelengths for predicting four kinds of soil properties were recommended based on variable importance in the projection (VIP), which offered useful guidance for the development of portable hyperspectral sensors based on discrete wavebands to reduce cost and save time for on-site data collection.

Context: Intensification of arable farming in Northwest Europe has led to high yields. However, inadequate use of external inputs such as nutrients, irrigation water and crop protection products has contributed to several environmental problems, such as nitrate leaching and losses of crop protection products. There is a need to reduce environmental losses and contribute to a more circular and sustainable agriculture in Northwest Europe. Objective: Here, we take ware potato production in the Netherlands as an example cropping system to assess if there is scope to reduce input levels and environmental impact of nutrient, water and crop protection product use without compromising yield. Methods: We determined variability in use and use efficiency of nitrogen (N), phosphorus (P), potassium (K) and pesticides as well as water productivity (WP) and yields of 96 on-farm ware potato fields in the Netherlands, on both clay and sandy soils. In addition, we assessed if relatively high performance could be achieved on multiple environmental indicators simultaneously. Results and conclusions: Average N surplus was 265 kg N ha−1 on clay soils and 139 kg N ha−1 on sandy soils and varied among fields by a factor three. Phosphorus and K input exceeded P and K output on clay soils by 33 and 105 kg ha−1, respectively, while on sandy soils P and K balances were close to zero. Mean WP was 43 kg dry matter (DM) mm−1 ha−1 and ranged from 30 to 60 kg DM mm−1 ha−1 for both soil types. In terms of crop protection product use, lowest and highest use differed by a factor four. Unexpectedly, yields did not increase with higher input rates, suggesting that lower input rates are sufficient to obtain current yields. Consequently, input rates were the most important drivers to explain variability in resource use efficiency and environmental impacts. At the same time, a comparison across multiple indicators simultaneously showed that it was possible to achieve relatively high yields with relatively

Context: Yield gap analyses are useful to assess and benchmark the productivity of cropping systems. Often such analyses are performed at higher aggregation levels. As a result, these studies lack the detail to explain yield gaps at field level and hence make it difficult to translate findings into precise recommendations to farmers and extensionists. Objective: This study provides a detailed approach for yield gap assessments at field level through coupling frequent field monitoring in farmers’ fields with crop growth modelling. We used ware potato production in the Netherlands as a case to study yield gaps at field level, as average productivity is high whilst yields are still highly variable among fields, and as ware potato is an important cash crop for farmers. Methods: Over two growing seasons, 96 ware potato fields were monitored throughout the growing season on a biweekly basis, taking measurements on soil, crop growth and yield. The crop growth model SWAP-WOFOST was used to simulate potential and water-limited potential yields. Various statistical methods were used to quantify yield gap explaining factors. Results: The average yield gap ranged from 20 to 31% depending on the year and soil type. Among fields, the yield gap ranged from 0 to 51%. On clayey soils, the yield gap was attributed mostly to oxygen stress. On sandy soils, the yield gap was determined mostly by drought stress in 2020, a relatively dry year, and by reducing factors (pests, diseases and poor agronomic practices) in 2021, an average year in terms of precipitation. The type of reducing factors differed per field. Furthermore, we found that earlier planting and later harvesting can increase yields, as Yp is radiation-limited. Conclusions: Overall, there is limited scope to narrow the yield gap as current ware potato production is already close to 80% of the potential yield, which is assumed to be approximately the maximum farmers can attain. However, yield and resource use efficiency gains

Crop yields are determined by the biophysical environment and by farm management decisions, which in turn depend on socio-economic conditions of the farm(er). The interaction of these factors results in spatial and temporal yield variability. We assessed ware potato yield variability in the Netherlands across four agronomically relevant scales (among provinces, farms and fields and within fields) using five datasets with data on potato yield across space and time. Furthermore, we disseminated an online questionnaire among farmers to identify the perceived yield gap and the key yield gap explaining factors at farm level. Spatial yield variability was largest among fields, with a standard deviation of 8.5–11.1 t ha−1, and within fields, with a standard deviation of 7.7–8.7 t ha−1. Spatial yield variability decreased at higher aggregation levels, i.e., the standard deviation of among-farm yield variability was 4.0–6.1 t ha−1 and that of among-provinces 1.6–3.5 t ha−1. Mean yields of the datasets ranged from 46 to 52 t ha−1. Temporal yield variability explained 10–55 % of the total observed variation in crop yield and its magnitude was equal or larger than the spatial yield variability for almost all datasets. Farmers estimated the ware potato yield gap at 13–18 t ha−1, corresponding to 20–24 % of estimated yield potential, depending on the soil type and variety. Water deficit and water excess were considered the most important yield gap explaining biophysical factors. In addition, soil structure was an important biophysical factor on clay soils and diseases on sandy soils. Irrigation and fertilization were identified as the most important yield gap explaining management factors, whereas legislation and potato prices were identified as the key socio-economic factors influencing potato yields. However, the perceived yield gap explaining factors varied with soil type, variety and year. We conclude that reducing potato yield variability in the Netherlands can be achieved b

Deze notitie is gemaakt in opdracht van het Topsector AgriFood PPS-project ‘Precisielandbouw 4.0’: op naar data-gedreven landbouw voor rotatie management van de Topsector PPS AF-18101. Hiertoe is een aantal vragen geformuleerd en beantwoord omtrent de werkwijze en de gebruiksmogelijkheden van de Cool Farm Tool en BodemC. De keuze voor de Cool Farm Tool of BodemC heeft in grote mate te maken met het doel van het gebruik. Voor de evaluatie van de bodemvoorraad koolstof (huidige en toekomstige met scenario’s) is BodemC het meest geschikt. Is het doel meer omvattend en zijn emissies van broeikasgassen voor een teelt daar een onderdeel van, dan is de Cool Farm Tool het meest geschikt.

This report discusses the importance of precision agriculture in achieving sustainability goals and the need for a basis that considers different perspectives of a data space such as interoperability, scalability, security, transparency, and data ownership. The Towards Precision Agriculture 4.0 project aims to address these perspectives to provide better-informed management decisions for farmers and the ecosystem. The current study focuses on determining minimum interoperability mechanisms concerning the standardization of image data and deep learning algorithms for vision-based applications in weed management by robots. The study adopts a metadata-oriented approach to make data and algorithms semantically interoperable and reuses existing knowledge from the Reference Model Agro (rmAgro). The results indicate the need for a balance between established standardization and agile standardization for supporting semantic interoperability, and the interoperability of preferred standards like Robot Operating System (ROS) and Open Neural Network Exchange (ONNX) is insufficient. The study results are useful for professionals and academia who work in the design and development of software for the farming business.

Estimation of Dry Matter Yield (DMY) and Nitrogen Content (NC) in forage is a big concern for growers. In this study, an estimation model of DMY and NC using Visible and Near Infrared (V-NIR) spectroscopy was developed. An adequate number of grass samples (5078) of perennial ryegrass (Lolium perenne), collected from Dutch grassland in 2019 and 2020 were sensed with a hyperspectral sensor, while grass height was recorded in situ by an ultrasonic sensor mounted on a tractor. The samples were treated with Artificial Intelligence (AI) techniques. PCA based feature selection was applied first, revealing that visible green wavelength (around 500 nm) and red edge wavelength (around 700 nm) were enough to express the overall variability of the dataset. Then, Feature Importance analysis of Random Forest Regressor showed that NIR wavelengths (around 910, 960 and 990nm) were the most sensitive in DMY estimation, while red edge (around 710 nm) and visible orange wavelengths (around 610 nm) were the most related to NC estimation. Finally, SHAP (SHapley Additive exPlanations) analysis was applied to the Random Forest estimation models, resulting in the visualization of wavelength selection, thus assisting in the interpretation of the results and the intermediate processes. Overall, this method can lead to the reduction of the number of wavelengths to be measured in the field and thus, to the possible development of a low cost hyperspectral sensor for the above purposes.

DISAC is een cross-over samenwerking van de topsectoren AgriFood en Holland High Tech gericht op ontwikkeling van sleuteltechnologien voor en toepassingen van digitale landbouw. De focus in de R&D ligt op toepassingen in ketens van consumptieaardappelen (frites, chips en vers) en ruwvoer (gras) in de zuivel. Door toepassing van sensoren die zo veel mogelijk realtime, objectspecifieke data leveren, en dit in kombinatie met innovatieve data-infrastructuren en data-analyse, wordt een betere teelt- en ketensturing mogelijk. Dit is uitgevoerd in 3 deelprojecten/use cases, te weten: • N-sensing: Prototype-ontwikkeling en toetsen van een nieuwe sensoriek en agro-economische N-adviesmodules voor het Gras/Maïs-Signaal, inclusief een deel nitraatsensor; • E-pieper: Optimalisatie van kwaliteit in de keten door gebruik te maken van sensoren en data- infrastructuur; • Connectivity: Verbeteren decision support modules en interactie met machines. In het deelproject N-sensing is de webapplicatie GrasSignaal ontwikkeld voor melkveehouders, om te voorspellen hoeveel gras waar staat en wat de kwaliteit hiervan is. Het geeft inzicht in hoeveel gras erbij gaat groeien en hoe de voederwaarde zich gaat ontwikkelen, binnen de weersverwachtingstermijn. Het ruw eiwitgehalte is daarbij een steeds belangrijker gegeven om het gewenste oogstmoment te bepalen en de mestbenutting te optimaliseren. In N-sensing is verder gewerkt aan de ontwikkeling en validatie van sensoren die nitraat in water kunnen meten. Daarbij gaat het om metingen in oppervlaktewater en bodemvocht. De data van de meting zijn dan bruikbaar voor adviesmodellen (decision support) voor bemesting van gewassen. Een werkend prototype is opgeleverd. Het E-Pieper deelproject heeft inzicht en technologie opgeleverd hoe data via een data-platform bij elkaar gebracht kan worden, gevisualiseerd kan worden voor gebruikers, en slim toegepast kan worden door koppeling met modellen bij de productie van aardappelen. Tijdens validatie op twee

Stalk lodging in maize causes yield and quality losses worldwide. This could potentially be prevented through breeding and improved crop management. Breeding efforts and management optimization are however, hampered by the lack of an internode growth model and an indicator for stalk lodging resistance. With this study, we aim to contribute to a solution for this problem. We report on the results of a two-year field study in which we measured and analyzed plant traits assumed to be related to stalk lodging resistance, in five cultivars. These traits include plant and basal internode morphology, dry matter constituents accumulation, and mechanical strength of basal internode. Results from a logistic regression analysis indicate that, the stalk lodging incidence was significantly affected by the development process of the basal internode. The rapid accumulation duration of lignin, internode plumpness and cellulose were found to be the most important contributors to mechanical strength of basal internode. The correlation between Rind penetration strength (PS) and stalk lodging rate was found to be higher than the correlation between bending strength (BS) and the stalk lodging rate. In addition, PS was found to be more stable than BS over development stages and years. Dry matter constituents accumulation in the basal internode, especially lignin accumulation, were found to be the dominant process determining the mechanical strength of the basal internode. Breeding and crop management strategies aiming to prolong the duration of rapid lignin and dry matter accumulation in the basal internode may thus significantly contribute to improved lodging resistance in future maize cultivars.

Background: The European Commission (EC) has launched the European Green Deal communication, setting out the path for a fundamental transformation of Europe. Key element in this policy is a fully sustainable food system outlined in the farm-to-fork strategy. Such strategy requires a systems approach in which all aspects related to the production and consumption of sufficient and healthy food are considered, including economic, environmental (climate, ecosystems) and social aspects. Scope and approach: Here, we present the systems approach concept for food production, following the farm-to-fork principle as embraced by the EC, and elaborate on how digitalisation and Artificial Intelligence (AI) can solve the challenges that a sustainable food system imposes. Key findings and conclusions: We present a number of research and innovation challenges and illustrate these by some specific examples. It is concluded that AI and digitalisation show great potential to support the transition towards a sustainable food system. This development will impact the roles and interactions of the actors in the entire value chain from farmers to consumers. Policy recommendations are made for a successful future implementation of AI in sustainable food production.

Door middel van een vergelijkingsproef op twee praktijkpercelen in Dronten en Wageningen zijn een tiental systemen die bodemvocht bepalen met elkaar vergeleken. De vergelijking richtte zich enerzijds op de nauwkeurigheid waarmee bodemvochtgehaltes door de verschillende systemen konden worden bepaald. Anderzijds werd gekeken naar een groot aantal factoren die het gebruik beïnvloeden, zowel het gemak als de mogelijkheden. De verschillen tussen de systemen zijn zo nu en dan behoorlijk groot, met name op het gebied van gebruiksgemak en mogelijkheden. Het bepalen van een absoluut niveau van de bodemvochttoestand blijkt zelfs met ringmonsters lastig, vochtgehalte en trends worden over het algemeen goed gevolgd door de verschillende sensoren. In vervolgonderzoek zou meer nadruk op deze trends moeten liggen, alsook op de reproduceerbaarheid van de gemeten waarden door meerdere sensoren per type te plaatsen.

Op het snijvlak tussen luchtvaart- en landbouwregelgeving bevindt zich de ontwikkeling en inzet van spuitdrones. Nieuwe regelgeving op het gebied van gewasbescherming verwacht veel van drones als innovatieve manier om middelen toe te dienen. Echter, er zijn nog de nodige barrières voor het invoeren van spuitdrones. Naast regelgeving zijn dit ook de beschikbaarheid van hiervoor goedgekeurde middelen, opleidingen en licenties van drone-operators, technische standaarden voor spuitinstallaties en dienstenmodellen voor de markt. De studie constateert een positief toekomstbeeld voor spuitdrones, maar dat wetenschappelijke en technische ontwikkeling nodig is voor het wegnemen van risico’s en onzekerheden. Deze studie geeft handvatten voor verdere onderzoeksinitiatieven en doorontwikkeling in de markt.

The demand for biostimulants has been growing at an annual rate of 10 and 12.4% in Europe and Northern America, respectively. The beneficial effects of humic substances (HS) as biostimulants of plant growth have been well-known since the 1980s, and they can be supportive to a circular economy if they are extracted from different renewable resources of organic matter including harvest residues, wastewater, sewage sludge, and manure. This paper presents an overview of the scientific outputs on application methods of HS in different conditions. Firstly, the functionality of HS in the primary and secondary metabolism under stressed and non-stressed cropping conditions is discussed along with crop protection against pathogens. Secondly, the advantages and limitations of five different types of HS application under open-fields and greenhouse conditions are described. Key factors, such as the chemical structure of HS, application method, optimal rate, and field circumstances, play a crucial role in enhancing plant growth by HS treatment as a biostimulant. If we can get a better grip on these factors, HS has the potential to become a part of circular agriculture.

Potato is the fourth most important staple crop in China. To meet the increased demand and environmental objectives, potato production should be enhanced by sustainable practices that aim to maximize yield and resource use efficiencies and minimize environmental impacts. Most experiments so far have taken place on experimental stations, while on-farm experimentation is needed to evaluate, demonstrate and scale more sustainable practices. On-farm field experiments were conducted in two years (2017, 2018) in northern China to investigate and demonstrate the effects of different nitrogen (N) fertiliser and irrigation input levels on potato yield, quality, resource use efficiency and environmental impacts. The 2017 experimental results on one farmer’s field showed that under irrigated conditions, adding N fertiliser (from 0 to 267 kg ha−1) did not increase yield due to the high soil N supply, rather it reduced tuber quality. The 2018 experimental results, in which four additional farmers were involved, indicated that, under irrigated conditions, reducing N fertiliser from the current rates (189–252 kg ha−1) to lower levels (109–181 kg ha−1) did not affect yield nor quality; while further reducing N fertiliser inputs (to 9–117 kg ha−1) resulted in a yield reduction (18% on average) in some fields. In both years, irrigation improved tuber yield and quality compared to that under rainfed conditions. The nitrogen use efficiency was improved and N surplus was reduced by applying irrigation and reducing N fertiliser input. Farmers expressed they were willing to reduce N fertiliser input by 10–20%, and indicated that a widespread adaptation of drip irrigation is hindered by the high costs and labor requirements. Site-specific recommendations on optimum N fertiliser and irrigation management must be provided, which should preferably be based on regular quantitative monitoring of soil N supply and soil moisture content.

De PPS PL4.0 onderzoekt in fase 1 de haalbaarheid van een veilige ruimte voor het delen van data voor open-teeltenbedrijven, waardoor zij een volwaardige positie krijgen in data-gedreven AgriFood waardeketens. Het doel van de PPS is een collectieve, publiek-private R&D inspanning te leveren om te komen tot een basis voor grootschalig, slim, veilig, transparant en ‘in control’ gebruik van data in open teelten (inclusief teelt van voedergewassen) en AgriFood-ketens in Nederland. In dit rapport worden (1) de huidige situatie van data gebruik op akkerbouw-, ruwvoerproductie- en loonwerkbedrijven beschreven, (2) technische, organisatorische, ethische en juridische aspecten van data-gebruik en (3) een knelpuntenanalyse van data-gebruik op deze open-teelten bedrijven. De kern van de uitkomsten van de analyse is dat boeren moeten werken met een lappendeken van ICT-tools die onderling slecht verbonden zijn waardoor het schier onmogelijk is om op hun bedrijven gegenereerde data overzichtelijk bij elkaar te brengen in een gebruiksvriendelijk data-platform van waaruit ze alle zaken met hun data willen kunnen doen waarin meerwaarde zit (monitoring, benchmarking, verantwoording, teelt-, bedrijf- en ketenoptimalisatie, etc.). Kernwoorden zijn Data-soevereiniteit (zeggenschap over data) en Interoperabiliteit (kunnen koppelen van data en systemen). Om de knelpunten op te lossen doen we een achttal aanbevelingen, waarvan de belangrijkste is het maken van publiek-private afspraken over architectuurprincipes van technische en organisatorische aard. Die afspraken zijn de basis voor realisatie van de gewenste data-ruimte van de boer waardoor hij een volwaardige partner wordt in AgriFood ketens. En als die gewenste data-ruimte er is, ontstaan er nieuwe mogelijkheden op gebied van bedrijfs- en ketenoptimalisatie, nieuwe services en monitoring van maatschappelijke doelen waaronder die van EU GLB. De aanbevelingen kunnen uitgewerkt worden in fase 2 van PPS PL4.0, waarin de PPS met meer partn

How can blockchain help to achieve a sustainable agrifood sector? Blockchain offers many opportunities for improving transparency, efficiency, competitiveness of agrifood and the position of farmers in the data value chain. The playing field of blockchain spans the domains of automation, data science, and data economy. To realise a good use case requires close collaboration of people from all three sub-domains. For this report we studied more than 30 blockchain use cases and platforms in and outside of the Netherlands. Within the programme ‘Blockchain for Agrifood’, software applications have been built for three use cases: FarmDataWallet, Flori-Chain and AGF-Chain. Experiences with these use cases have been used to identify the challenges and best practices., Hoe kan blockchain bijdragen aan het realiseren van een duurzame agrifood? Blockchain biedt veel kansen om de transparantie, efficiëntie en concurrentieposities van agrifood en de positie van boeren in de agrifoodketens te verbeteren. Het speelveld van een blockchaintoepassing omvat automatisering, data science en data-economie. Om een geslaagde blockchaintoepassing of een usecase te organiseren is nauwe samenwerking nodig tussen partijen vanuit deze drie werelden. Ten behoeve van dit rapport zijn ruim 30 blockchain-usecases en blockchainplatformen binnen en buiten Nederland onderzocht. Voor drie usecases (FarmDataWallet, Flori-Chain en AGF-Chain) binnen het programma ‘Blockchain voor Agrifood’ wordt er ook prototype software gebouwd en getest. De bevindingen van de best practices en uitdagingen zijn mede gebaseerd op de ervaringen hiermee.

De publiek private samenwerking (PPS) ‘Op naar precisielandbouw 2.0’ (PL2.0) is een R&D project van de topsector AgriFood. Het project is gestart in 2015 met doorlooptijd van 4 jaar. Voor u ligt het eindrapport. In deze PPS werkten ruim 20 private bedrijven en organisaties, publieke kennisinstellingen en overheden samen aan strategische onderwerpen binnen precisielandbouw. Het project omvatte 13 deelprojecten verdeeld over vijf specifieke R&D thema’s, te weten slim satellietbeeldengebruik, sensorontwikkeling (ziektedetectie), slimme integratie van technologieën in toepassingen, perceelkarakteristieken voor schatten van opbrengstpotentie en ondersteunende ICT, en een generiek thema communicatie en kennisverspreiding.Met betrekking tot het thema satellietbeeldengebruik is uitgezocht hoe optische satellietbeelden in combinatie met radarbeelden of beelden verkregen via drone-camera’s beter gebruikt kunnen worden om de variatie en status van de bovengrondse hoeveelheid biomassa van gewassen in kaart te brengen en opbrengsten te voorspellen. Op het gebied van ziektedetectie is door middel van sensor fusion en artificial intelligence de detectie van virus- en bacterieziekten in aardappelplanten verbeterd. En werd een prototype sensorsysteem voor veldonderzoek ontwikkeld. Door slimme integratie van data, adviesmodellen en mechanisatie zijn er enkele variabel-doseertoepassingen ontwikkeld en gevalideerd. Het gaat hier om variabel doseren van Stikstof en herbiciden binnen teelten d.m.v. taakkaarten. In het verlengde hiervan is ook een ontwerp geleverd en als prototype gevalideerd voor een innovatieve beddenspuit in bloembollenteelt. Op grond van perceelkarakteristieken en ondersteunende ICT zijn inzichten en tools voor het inschatten van opbrengst(potentie) geleverd en wordt een doorkijk gegeven naar software voor verbeterde rijpadenplanning en perceelinformatie. De inzet op communicatie en kennisdeling heeft ca. 100 publicaties en presentaties in 4 jaar tijd opgeleverd. Voo

The Agricultural Counsellor of the Netherlands Embassy in Delhi initiated a BOCI project ‘Overview of the potato chain in India’ in early 2011. In September 2012 this initiative has been adopted by the Dutch and Indian stakeholders and the Pubic Private Partnership (PPS) was established to facilitate the intensification of collaboration between Dutch and Indian stakeholders of the potato chain. A team of Wageningen UR researchers was commissioned to carry out this project. In 2011, the team collected information from reports, personal files, internet and some Dutch companies and reported the information in “An overview of the potato sector in India and prospects of Indo & Dutch cooperation”. The team also participated in the Netherlands Trade mission to India (5 & 11 June 2011) and visited the Central Potato Research Institute at Shimla. Furthermore jointly with the Agricultural Counsellor we organized a potato seminar to present our findings on 5 October 2011 in Delhi. Major potato stakeholders both from India and from the Netherlands attended the seminar; total number of participants was about 60 persons. In 2012, 2013, 2014, 2015 and 2016 the team carried out different tasks such as presenting information on various subjects of the Dutch and Indian potato chain to exchange knowledge. In addition, several identified subjects were investigated. All actions and activities aimed to facilitate collaboration between Dutch and Indian stakeholders. Visits to different locations of India accompanied by Dutch stakeholders, meetings with experts of the Indian potato production chain both stakeholders and researchers, and topics such as skin curing and chemical haulm killing, reduce storage losses and the establishment of the Centres of Excellence (CoE) in Punjab (Jalandhar) and Uttar Pradesh, and the Centre of Potato Expertise (COPE) at Ludhiana (Punjab) were successfully accomplished.

For farmers, the application of Precision Agriculture (PA) technology is expected to lead to an increase in profitability. For society, PA is expected to lead to increased sustainability.The objective of this paper is to determine for a number of common PA practices how much they increase profitability and sustainability. For potato production in The Netherlands, we considered variable rate application (VRA) of soil herbicide, fungicide for late blight control, sidedress N, and haulm killing herbicide. For olive production in Greece, we considered spatially variable application of P and K fertilizer and lime. For each of the above scenarios, we quantified the value of outputs, the cost of inputs, and the environmental costs. This allowed us to calculate profit as well as social profit, where the latter is defined as revenues minus conventional costs minus the external costs of production. Social profit can be considered an overall measure of sustainability. Our calculations show that PA in potatoes increases profit by 21% (420 € ha-1) and social profit by 26%. In olives, VRA application of P, K, and lime leads to a strong reduction in nutrient use and although this leads to an increase in sustainability, it has only a small effect on profit and on social profit. In conclusion, PA increases sustainability in olives and both profitability and sustainability in potatoes.