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Novel approaches and algorithms to estimate crop physiological processes from Earth Observation (EO) data are essential to develop more sustainable management practices in agricultural systems. Within this context, this paper presents the results of different research activities carried out within the ESA-MOST Dragon 4 programme. The paper encompasses two research avenues: (a) the retrieval of biophysical variables of crops and yield prediction; and (b) food security related to different crop management strategies. Concerning the retrieval of variables, results show that LAI, derived by radiative transfer model (RTM) inversion, when assimilated into a crop growth model (i.e., SAFY) provides a way to assess yields with a higher accuracy with respect to open loop model runs: 1.14 t·ha−1 vs 4.42 t·ha−1 RMSE for assimilation and open loop, respectively. Concerning food security, results show that different pathogens could be detected by remote sensing satellite data. A k coefficient higher than 0.84 was achieved for yellow rust, thus assuring a monitoring accuracy, and for the diseased samples k was higher than 0.87. Concerning permanent crops, neural network (NN) algorithms allow classification of the Pseudomonas syringae pathogen on kiwi orchards with an overall accuracy higher than 91%. [ABSTRACT FROM AUTHOR]

Novel technologies for estimating crop water needs include mainly remote sensing evapotranspiration estimates and decision support systems (DSS) for irrigation scheduling. This work provides several examples of these approaches, that have been adjusted and modified over the years to provide a better representation of the soil–plant–atmosphere continuum and overcome their limitations. Dynamic crop simulation models synthetize in a formal way the relevant knowledge on the causal relationships between agroecosystem components. Among these, plant–water–soil relationships, water stress and its effects on crop growth and development. Crop models can be categorized into (i) water-driven and (ii) radiation-driven, depending on the main variable governing crop growth. Water stress is calculated starting from (i) soil water content or (ii) transpiration deficit. The stress affects relevant features of plant growth and development in a similar way in most models: leaf expansion is the most sensitive process and is usually not considered when planning irrigation, even though prolonged water stress during canopy development can consistently reduce light interception by leaves; stomatal closure reduces transpiration, directly affecting dry matter accumulation and therefore being of paramount importance for irrigation scheduling; senescence rate can also be increased by severe water stress. The mechanistic concepts of crop models can be used to improve existing simpler methods currently integrated in irrigation management DSS, provide continuous simulations of crop and water dynamics over time and set predictions of future plant–water interactions. Crop models can also be used as a platform for integrating information from various sources (e.g., with data assimilation) into process-based simulations. [ABSTRACT FROM AUTHOR]

The present work reports the global sensitivity analysis of the Aquacrop Open Source (AOS) model, which is the open-source version of the original Aquacrop model developed by the Food and Agriculture Organization (FAO). Analysis for identifying the most influential parameters was based on different strategies of global SA, density-based and variance-based, for the wheat crop in two different geographical locations and climates. The main objectives were to distinguish the model's influential and non-influential parameters and to examine the yield output sensitivity. We compared two different methods of global sensitivity analysis: the most commonly used variance-based method, EFAST, and the moment independent density-based PAWN method developed in recent years. We have also identified non-influential parameters using Morris screening method, so to provide an idea of the use of non-influential parameters with a dummy parameter approach. For both the study areas (located in Italy and in China) and climates, a similar set of influential parameters was found, although with varying sensitivity. When compared with different probability distribution functions, the probability distribution function of yield was found to be best approximated by a Generalized Extreme Values distribution with Kolmogorov–Smirnov statistic of 0.030 and lowest Anderson–Darling statistic of 0.164, as compared to normal distribution function with Kolmogorov–Smirnov statistic of 0.122 and Anderson–Darling statistic of 4.099. This indicates that yield output is not normally distributed but has a rather skewed distribution function. In this case, a variance-based approach was not the best choice, and the density-based method performed better. The dummy parameter approach avoids to use a threshold as it is a subjective question; it advances the approach to setting up a threshold and gives an optimal way to set up a threshold and use it to distinguish between influential and non-influential parameters. The highly sensitive parameters to crop yield were specifically canopy and phenological development parameters, parameters that govern biomass/yield production and temperature stress parameters rather than root development and water stress parameters. [ABSTRACT FROM AUTHOR]

Red chicory (radicchio) plants produce leafy heads that are of great commercial interest and they require a proper irrigation technique to achieve satisfactory productivity. The use of mini-sprinklers with high-frequency irrigation schedules may increase radicchio productivity, provide better growing conditions due to timely intervention, and save water, but so far little research has been carried out on this topic. This experiment aims at evaluating the effect of two mini-sprinkler irrigation schedules (high- and low-frequency) on radicchio yield and growing conditions over a 5-year cultivation period. Marketable radicchio head production was on average 12% greater with the high-frequency schedule (26.5 t ha−1) than with the low-frequency schedule (23.6 t ha−1), mainly due to greater head weight. The number of underweight, pre-flowering, rotten, and missing plants was significantly different between the two schedules when these variables were considered separately, but the overall number of marketable plants was greater in the high-frequency schedule during certain years. In general, the high-frequency schedule permitted to increase both radicchio yield and to reduce irrigation water use on average by 14% (−24 mm in volume), improving the irrigation water productivity by 19% (from 0.18 t mm−1 of the low-frequency schedule to 0.22 t mm−1 of the high-frequency schedule). Reducing the irrigation interval permits a timely adaptation to the weather course and improves radicchio growing conditions, presenting itself as a valid strategy that could be adopted by the farmers, upon appropriate consideration of energy and management costs. [ABSTRACT FROM AUTHOR]

Surface flow constructed wetlands (SFCWs) can be effectively used to treat agricultural drainage waters, reducing N and P surface water pollution. In the Venice Lagoon drainage basin (northeastern Italy), an SFCW was monitored during 2007–2013 to assess its performance in reducing water, N, and P loads more than 10 years after its creation. Nitrogen concentrations showed peaks during winter due to intense leaching from surrounding fields. Phosphorus concentrations were higher after prolonged periods with no discharge, likely due to mobilization of P of the decomposing litter inside the basin. Over the entire period, N removal efficiency was 83% for NO3–N and 79% for total N; P removal efficiency was 48% for PO4–P and 67% for total P. Values were higher than in several other studies, likely due to the fluctuating hydroperiod that produced discontinuous and reduced outflows. Nitrogen outlet concentrations were reduced by the SFCW, and N removal ratios decreased with increasing hydraulic loading, while no strong correlations were found in the case of P. The SFCW was shown to be an effective long-term strategy to increase water storage and reduce N and P loads in the Venice Lagoon drainage basin. [ABSTRACT FROM AUTHOR]