Piero Battista

Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy.

Evaluation and adaptation of TOMGRO model to Italian tomato protected crops

Abstract A simplified version of TOMGRO, a well-known model for tomato growth simulation, was delivered by its authors in 1999, with the aim to adapt the program to operational exigencies. This model version was chosen to integrate the functions of a decision support tool, oriented to support Italian tomato growers in soilless crop fertigation management. During the preliminary evaluation phase, its application on data collected in three greenhouse experiments conducted on tomato cv. Jama in Pisa (central Italy) in 2004 and 2005, showed an insufficient accuracy in the Leaf Area Index (LAI) estimation of tomato crops. Consequently, node number and LAI computational algorithms were modified. This paper discusses model modifications, analysing their effects on tomato growth simulation. In comparison with the observed data, the modified model showed a good enhancement of estimation accuracy of node and LAI, with significantly positive effects also on plant and fruit biomass estimation.

Integration of spatial analysis and fuzzy classification for the estimation of forest parameters in Mediterranean areas

Satellite images are often insufficient to provide reliable estimates of forest parameters in complex Mediterranean areas, where the spectral response of vegetation is influenced by several interacting factors. In the current work spatial analysis and Geostatistics are used to produce additional information which can supplement that derived from remotely sensed data. In particular, an approach based on kriging was applied in a study area in Tuscany (Central Italy) to estimate forest composition and structure, and the same was done with a fuzzy classification procedure using bitemporal Landsat‐TM images. Since the two methods produced per‐pixel estimates of error variance, their outputs could be integrated by means of an optimal merging methodology. The results of the experiments, evaluated by statistical comparison to independent ground references, showed that both methods provided good estimates of forest composition and structure at stand level. Furthermore, the information derived from the two sources was partly nonredundant and could be efficiently merged to improve the estimation accuracy for both forest parameters.

Improved simulation of soil water content by the combination of ground and remote sensing data

Abstract The simulation of site water balance requires the assessment of actual evapotranspiration (ETA), which is highly variable both in space and in time depending on several factors (climate, soil, vegetation). In a recent work we proposed a new method based on remotely sensed NDVI data which can estimate daily ETA operationally over large areas. The current paper utilizes these ETA estimates to drive two crop coefficient models, WinEtro and FAO56, in the prediction of soil water content (SWC). The outputs of the simulations are evaluated versus daily measurements of SWC taken in a Tuscany forest site (Barbialla) during four years. The results obtained indicate the efficiency of the proposed data combination, which improves the SWC simulations of both models examined. Recommendations are finally expressed for the possible extension and enhancement of the method described.

Combination of ground and satellite data for the operational estimation of daily evapotranspiration

Abstract A recent paper of our research group has proposed a simplified “water balance” model which predicts actual evapotranspiration (ETA) based on ground and remotely sensed data. The model combines estimates of potential evapotranspiration (ET0) and of fractional vegetation cover derived from NDVI in order to separately simulate transpirative and evaporative processes. The new method, named NDVI-Cws, was validated against latent heat measurements taken by the eddy covariance technique over various vegetation types in Central Italy. The current paper extends this validation to three other test sites in Tuscany for which reference data are obtained from different sources. In the first two sites (non-irrigated winter wheat and irrigated maize fields) seasonal reference ETA data series are obtained by the WinEtro model. In situ transpiration measurements are instead used as reference data for a deciduous oak forest stand. The ETA and transpiration estimates of the NDVI-Cws method are very similar to the reference data in terms of both annual totals and seasonal evolutions. Examples are finally provided of the model application for operationally monitoring ETA in Tuscany.

Integration of Ground and Multi-Resolution Satellite Data for Predicting the Water Balance of a Mediterranean Two-Layer Agro-Ecosystem

The estimation of site water budget is important in Mediterranean areas, where it represents a crucial factor affecting the quantity and quality of traditional crop production. This is particularly the case for spatially fragmented, multi-layer agricultural ecosystems such as olive groves, which are traditional cultivations of the Mediterranean basin. The current paper aims at demonstrating the effectiveness of spatialized meteorological data and remote sensing techniques to estimate the actual evapotranspiration (ETA) and the soil water content (SWC) of an olive orchard in Central Italy. The relatively small size of this orchard (about 0.1 ha) and its two-layer structure (i.e., olive trees and grasses) require the integration of remotely sensed data with different spatial and temporal resolutions (Terra-MODIS, Landsat 8-OLI and Ikonos). These data are used to drive a recently proposed water balance method (NDVI-Cws) and predict ETA and then site SWC, which are assessed through comparison with sap flow and soil wetness measurements taken in 2013. The results obtained indicate the importance of integrating satellite imageries having different spatio-temporal properties in order to properly characterize the examined olive orchard. More generally, the experimental evidences support the possibility of using widely available remotely sensed and ancillary datasets for the operational estimation of ETA and SWC in olive tree cultivation systems.

Modelling Evapotranspiration of Container Crops for Irrigation Scheduling

Irrigation is now recognized as an important component in the agriculture economy of Mediterranean regions. As practiced by many growers, it is often based on traditional application methods that fail to measure the supply of water needed to satisfy the variable requirements of different crops. In order to achieve more profitable and sustainable cropping systems, it is essential to modernize existing irrigation systems and improve irrigation water use efficiency (WUE). Up-to-date methods of irrigation should likewise be based on sound principles and techniques for attaining greater control over the soil-cropwater regime and for optimizing irrigation in relation to all other essential agricultural inputs and operations. Accurate predictions of crop water requirements are necessary for an efficient use of irrigation water in container crops cultivated both outdoors and in greenhouse. Irrigation scheduling (IS) has conventionally aimed to achieve an optimum water supply for productivity, with soil or container water content being maintained close to field capacity. Different approaches to IS have been developed, each having both advantages and disadvantages but despite the number of available systems and apparatus, not entirely satisfactory solutions have been found to rationalize IS, assuring optimal plant growth with minimal water use (Jones, 2004). Many growers, especially in the Mediterranean regions, use simple timers for automated irrigation control of containerized crops and scheduling is based on their own experience. Evapotranspiration (ET) is the primary process affecting crop water requirements and, therefore, its knowledge is essential for efficient irrigation management. ET is the combined process of evaporation from soil or substrate and leaf transpiration. Evapotranspiration requires two essential components: a source of energy and a vapour transport mechanism. Energy is needed for phase change from liquid to vapour in sub-stomatal cavities whereas the leaf-to-air vapour pressure gradient ensures that water vapour crosses leaf stomata. In container-grown plants, ET is affected by many factors, both environmental (e.g. air temperature, radiation, humidity, wind speed) and plant related characteristics (e.g. growth