Improving vineyard water use efficiency and yield with variable rate irrigation in California

Sánchez, Luis A.; Sams, B.; Alsina, María Mar; Hinds, Nigel; Klein, Levente J.; Dokoozlian, Nick

doi:10.1017/s2040470017000772

Cited by 38 publications

(27 citation statements)

References 4 publications

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“…Considering both sectors, a water saving of 18% was achieved. This result is slightly higher than that achieved, for instance, in [19], where with a much more complex irrigation system a maximum saving of 17% was obtained. Since the 2018 season was rather rainy, it is not unlikely that in drier years the total volume saved could be even greater.…”

contrasting

confidence: 55%

“…A VRI system should, ideally, be able to follow as much as possible the spatial variability detected in the field, in order to ensure a distribution of water well in accordance with the identified crop irrigation needs [22]. This need to have a high level of spatial differentiation in the irrigation supply collides with the complexity and the cost of the technical solution to be implemented: the more field zones there are to be managed, the more irrigation sectors with different characteristics and operating independently of each other there must be [19]. To pursue an economically viable solution, it is however necessary to reach a compromise between the spatial variability detected in the field and the number of homogeneous zones that can be managed.…”

Section: Irrigation System Design Preliminary Irrigation Scheduling mentioning

confidence: 99%

“…As a matter of fact, it is not rare that heterogeneity in soil characteristics could lead to 10-fold differences in yield between one area and another in the same vineyard, or to a differential maturation of grapes which would require selective harvesting; similar spatial variability patterns are observed in the development of canopy and, therefore, in transpiration and irrigation requirements [9]. These works usually present analyses of the within-field variability conducted through proximal or remote sensing techniques based on spectral indices, such as NDVI (Normalized Difference Vegetation Index) [19,20], CWSI (Crop Water Stress Index) [5,17], SAVI (Soil-Adjusted Vegetation Index) [21], or sometimes on canopy cover [22]. Even soil characteristics are widely used to identify patterns of variability in vineyard, in particular mapping the soil Electrical Conductivity (EC) which is well related to soil variables such as soil texture, water content and water retention capacity [23].…”

Section: Introductionmentioning

confidence: 99%

“…However, very few works deal with the subsequent implementation of irrigation VR systems to manage such heterogeneity, and these studies are usually carried out in experimental fields for research aims [20,24]. For instance, technological solutions presented so far for drip VRI in vineyards are economically unsustainable [19,22].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Effectiveness of Variable-Rate Drip Irrigation on Water Use Efficiency in a Vineyard in Northern Italy

Ortuani

Facchi

Mayer

et al. 2019

Water

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Although many studies in the literature illustrate the numerous devices and methodologies nowadays existing for assessing the spatial variability within agricultural fields, and indicate the potential for variable-rate irrigation (VRI) in vineyards, only very few works deal with the implementation of VRI systems to manage such heterogeneity, and these studies are usually conducted in experimental fields for research aims. In this study, a VR drip irrigation system was designed for a 1-ha productive vineyard in Northern Italy and managed during the agricultural season 2018, to demonstrate feasibility and effectiveness of a water supply differentiated according to the spatial variability detected in field. Electrical resistivity maps obtained by means of an electro-magnetic induction sensor were used to detect four homogeneous zones with similar soil properties. In each zone, a soil profile was opened, and soil samples were taken and analyzed in laboratory. Two irrigation management zones (MZs) were identified by grouping homogeneous zones on the basis of their hydrological properties, and an irrigation prescription map was built consistently with the total available water (TAW) content in the root zone of the two MZs. The designed drip irrigation system consisted of three independent sectors: the first two supplied water to the two MZs, while the third sector (reference sector) was managed following the farmer’s habits. During the season, irrigation in the first two sectors was fine-tuned using information provided by soil moisture probes installed in each sector. Results showed a reduction of water use by 18% compared to the ‘reference’ sector without losses in yield and product quality, and a grape’s maturation more homogeneous in time.

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contrasting

confidence: 55%

Section: Irrigation System Design Preliminary Irrigation Scheduling mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing the Effectiveness of Variable-Rate Drip Irrigation on Water Use Efficiency in a Vineyard in Northern Italy

Ortuani

Facchi

Mayer

et al. 2019

Water

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“…The entire vineyard is characterized by sandy loam and a 0-1 percent slope. The vineyard is equipped with a variable rate drip irrigation (VRDI) system (black grid; Figure 1) capable of applying specific amounts of irrigation on a 30 × 30 m gridded basis [42]. This grid was designed to have a symmetrical arrangement from the middle North-South line of the field so that each multi-tube drip irrigation bundle would span six pixels either from the west or from the east edges, where the valve boxes were located.…”

Section: Study Domainmentioning

confidence: 99%

Using High-Spatiotemporal Thermal Satellite ET Retrievals for Operational Water Use and Stress Monitoring in a California Vineyard

et al. 2019

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In viticulture, deficit irrigation strategies are often implemented to control vine canopy growth and to impose stress at critical stages of vine growth to improve wine grape quality. To support deficit irrigation scheduling, remote sensing technologies can be employed in the mapping of evapotranspiration (ET) at the field to sub-field scales, quantifying time-varying vineyard water requirements and actual water use. In the current study, we investigate the utility of ET maps derived from thermal infrared satellite imagery over a vineyard in the Central Valley of California equipped with a variable rate drip irrigation (VRDI) system which enables differential water applications at the 30 × 30 m scale. To support irrigation management at that scale, we utilized a thermal-based multi-sensor data fusion approach to generate weekly total actual ET (ETa) estimates at 30 m spatial resolution, coinciding with the resolution of the Landsat reflectance bands. Crop water requirements (ETc) were defined with a vegetative index (VI)-based approach. To test capacity to capture stress signals, the vineyard was sub-divided into four blocks with different irrigation management strategies and goals, inducing varying degrees of stress during the growing season. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. The thermal-based method was also able to capture the spatial heterogeneity in ET over the vineyard due to a water stress event imposed on two of the four vineyard blocks. This transient stress event was not reflected in the VI-based ETc estimate, highlighting the value of thermal band imaging. While the data fusion system provided valuable information, latency in current satellite data availability, particularly from Landsat, impacts operational applications over the course of a growing season.

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ARD‐VO: Agricultural robot data set of vineyards and olive groves

Crocetti

Bellocchio

Dionigi

et al. 2023

Journal of Field Robotics

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The availability of real-world data in agricultural applications is of paramount importance to develop robust and effective robotic-based solutions for farming operations. In this application context, however, very few data sets are available to the community and for some important crops, such as grapes and olives, they are almost absent. Therefore, the aim of this paper is to introduce and release ARD-VO, a data set for agricultural robotics applications focused on vineyards and olive cultivations. Its main purpose is to provide the researchers with a real-world extensive set of data to support the development of solutions and algorithms for precision farming technologies in the aforementioned crops.ARD-VO has been collected with an unmanned ground vehicle (UGV) equipped with different heterogeneous sensors that capture information essential for robot localization and plant monitoring tasks. It is composed of sequences gathered in 11 experimental sessions between August and October 2021, navigating the UGV for several kilometers in four cultivation fields in Umbria, a central region of Italy. In addition, to highlight the utility of ARD-VO, two application case studies are presented. In the first one, the data set is used to compare the performance of simultaneous localization and mapping and odometry estimation methods using vision systems, light detection and ranging, and inertial measurement unit sensors. The second one shows how the multispectral images included in ARD-VO can be used to compute Normalized Difference Vegetation Index maps, which are crucial to monitor the crops and build prescription maps.

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Improving vineyard water use efficiency and yield with variable rate irrigation in California

Cited by 38 publications

References 4 publications

Assessing the Effectiveness of Variable-Rate Drip Irrigation on Water Use Efficiency in a Vineyard in Northern Italy

Assessing the Effectiveness of Variable-Rate Drip Irrigation on Water Use Efficiency in a Vineyard in Northern Italy

Using High-Spatiotemporal Thermal Satellite ET Retrievals for Operational Water Use and Stress Monitoring in a California Vineyard

ARD‐VO: Agricultural robot data set of vineyards and olive groves

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