An integrated method for irrigation scheduling of potted plants

Bacci, L.; Battista, Piero; Rapi, B.

doi:10.1016/j.scienta.2007.11.005

Cited by 38 publications

(24 citation statements)

References 19 publications

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“…However, aside from implementing precision irrigation strategies for producing containerized crops, there are other benefits when using these systems in commercial applications. Automated sensor-based irrigation is not only used to restrict irrigation for controlling height [6] but also to improve water use [24], plant growth uniformity [27], biomass [28], flower number [29], plant stress symptoms, and disease pressure [30] and can increase profitability of commercial producers compared to visual inspection-or timer-based irrigation scheduling [31].…”

Section: Discussionmentioning

confidence: 99%

Substrate Volumetric Water Content Controls Growth and Development of Containerized Culinary Herbs

et al. 2019

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There are no chemical plant growth retardants that may be used on containerized culinary herbs intended for consumption. Our objective was to quantify the effect of substrate moisture content on the growth of four commonly produced culinary annual herbs grown in containers in the greenhouse. Seedlings of basil (Ocimum basilicum L.), dill (Anethum graveolens L.), parsley (Petroselinum crispum (Mill.) Fuss), and sage (Salvia officinalis L.) were transplanted into 11.4 cm diameter containers filled with commercial soilless substrate comprising (by vol.) 75% sphagnum peat moss and 25% coarse perlite and amended with 3.0 kg·m −3 of controlled-release fertilizer. After the containers were thoroughly irrigated to container capacity, plants were placed into a sensor-controlled irrigation system, which maintained substrate volumetric water content (VWC) at 0.15, 0.28, 0.30, 0.38, or 0.45 m 3 ·m −3 . Chlorophyll fluorescence, photosynthesis, stomatal conductance, and transpiration were measured 27 d after initiating treatments, and the results showed that chlorophyll fluorescence of parsley and photosynthesis of basil increased as substrate VWC increased from 0.15 to 0.45 m 3 ·m −3 ; the remaining parameters for basil, parsley, and sage were unaffected. Additionally, height, width, leaf area, and shoot dry mass of basil, dill, parsley, and sage increased as substrate volumetric water content increased from 0.15 to 0.45 m 3 ·m −3 . Our results show that growth of basil, dill, parsley, and sage can be promoted or inhibited by providing or withholding water, respectively, with no signs of stress or visual damage resulting from reduced substrate volumetric water content. Therefore, restricting irrigation and substrate volumetric water content is an effective nonchemical growth control method for containerized culinary herbs grown in peat-based substrate.Agronomy 2019, 9, 667 2 of 12 basil supplied with 200 mg·L −1 N from a complete, balanced water-soluble fertilizer are 33% larger than plants supplied with 50 mg·L −1 N from the same fertilizer [4]. Additionally, restricting P to 5 mg·L −1 produced basil, dill, parsley, and sage shorter than plants provided with 40 mg·L −1 [5]. While cultivar selection and nutrient management are useful forms of nonchemical growth control, it may be necessary to use multiple nonchemical methods of controlling growth to achieve the degree of control required in the absence of PGRs.Reducing irrigation or substrate volumetric water content (VWC), commonly referred to as "deficit irrigation", is another effective method of controlling containerized plant growth [6][7][8]. The water available for plant uptake increases and growth is promoted as substrate VWC increases and, as such, restricting irrigation and reducing the substrate VWC can diminish turgor pressure and subsequent stem extension and growth [9]. For example, containerized angelonia (Angelonia angustifolia Benth.) and petunia (Petunia × hybrid Vilm.) bedding plant growth is promoted by substrate VWC and, by reducing VWC, compact plants o...

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Section: Discussionmentioning

confidence: 99%

Substrate Volumetric Water Content Controls Growth and Development of Containerized Culinary Herbs

et al. 2019

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“…Currently, many greenhouse and nursery growers base their irrigation scheduling decisions on intuition or experience (Bacci et al, 2008;Jones, 2008;Lea-Cox et al, 2009). Oftentimes the most basic decision is -"do I need to irrigate today?"…”

Section: Intensive Production System Irrigation Schedulingmentioning

confidence: 99%

“…Previous studies with a variety of crop, ornamental and turf species have reported that the use of appropriate scheduling methods and precision irrigation technologies can save a significant amount of water, while maintaining or increasing yield and product quality (Bacci et al, 2008;Beeson & Brooks, 2008;Blonquist et al, 2006;. Many of these empirical approaches have successfully incorporated environmental variables into various models, to further increase the precision of irrigation scheduling (e.g.…”

Section: Hybridizing Sensing and Modeling Techniques For Precision Irmentioning

confidence: 99%

Using Wireless Sensor Networks for Precision Irrigation Scheduling

Lea‐Cox¹

2012

Problems, Perspectives and Challenges of Agricultural Water Management

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“…However, irrigation management can take into account more variables, including the hydro-physical properties of certain soils, the parameters related to other crops, their stages of development, water quality [25,26], and factors related to productivity, fruit quality, and the implementation of deficit irrigation strategies [27], which prevent the proper functioning of irrigation thresholds.…”

Section: Introductionmentioning

confidence: 99%

A Decision Support System for Irrigation Management: Analysis and Implementation of Different Learning Techniques

Torres-Sánchez

Navarro-Hellín²,

Guillamón

et al. 2020

Water

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Automatic irrigation scheduling systems are highly demanded in the agricultural sector due to their ability to both save water and manage deficit irrigation strategies. Elaborating a functional and efficient automatic irrigation system is a very complex task due to the high number of factors that the technician considers when managing irrigation in an optimal way. Automatic learning systems propose an alternative to traditional irrigation management by means of the automatic elaboration of predictions based on the learning of an agronomist (DSS). The aim of this paper is the study of several learning techniques in order to determine the goodness and error relative to expert decision. Nine orchards were tested during 2018 using linear regression (LR), random forest regression (RFR), and support vector regression (SVR) methods as engines of the irrigation decision support system (IDSS) proposed. The results obtained by the learning methods in three of these orchards have been compared with the decisions made by the agronomist over an entire year. The prediction model errors determined the best fitting regression model. The results obtained lead to the conclusion that these methods are valid engines to develop automatic irrigation scheduling systems.

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An integrated method for irrigation scheduling of potted plants

Cited by 38 publications

References 19 publications

Substrate Volumetric Water Content Controls Growth and Development of Containerized Culinary Herbs

Substrate Volumetric Water Content Controls Growth and Development of Containerized Culinary Herbs

Using Wireless Sensor Networks for Precision Irrigation Scheduling

A Decision Support System for Irrigation Management: Analysis and Implementation of Different Learning Techniques

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