Differing precision irrigation thresholds for kale (Brassica oleracea L. var. acephala) induces changes in physiological performance, metabolites, and yield
Introduction
Increasing irrigation costs and worldwide development of water fluctuations and scarcity are major problems facing vegetable producers. Implementing water conservation practices to significantly reduce irrigation use, while still maintaining yields and quality, is important for food security. Improving water use efficiencies (WUE) and physiological performance in intense production systems are gaining further importance. A vegetable production and plant physiological systems approach will be needed to sustainably reduce irrigation needs while maintaining high yields and vegetable quality. The approach will have to entail using drip irrigation technologies and integrative irrigation management techniques, coupled with precision irrigation systems that utilize soil moisture sensors (Kumar and Sahu, 2013). To achieve these goals, the precise irrigation timing of optimal amounts of water is critical. It is especially important in vegetable crops where timely irrigation is beneficial to yield and quality. However, information is lacking for Brassica species where literature on the effects of irrigation scheduling and WUE are scarce, especially in kale (Brassica oleracea L. var. acephala).
Plants in irrigated agricultural production systems, including greenhouse and high tunnel production, are often exposed to fluctuating soil water availability, characterized by repeated soil drying and rewetting cycles. These drying and re-wetting cycles affect both plant water and nutrient uptake (Dodd et al., 2015), gas exchange and photosynthesis (Singh and Reddy, 2011), and other metabolic processes such as gene expression, hormone levels, amino acids, and sugars (Seki et al., 2007). In a recent study, Pavlović et al. (2018) determined that kale was more tolerant to drought conditions, compared to other Brassica species that had increased levels of phytohormones such as abscisic acid (ABA) and auxin. In the same study, there were also increased levels of salicylic acid (SA) and jasmonates (JA). However, there was no decrease in quantum yields (Fv/Fm).
Crop adaptation to irrigated conditions can be improved by increasing WUE or by increasing water supply to the plant through improved plant root architecture (Hall, 2004). Intrinsic WUE estimated as a ratio of A/gs has been recognized as a measure of carbon gain per unit of water loss and found to be inversely proportional to the ratio of intercellular and ambient CO2 concentrations (Ci/Ca) (Martin and Ruiz-Torres, 1996; Brodribb, 1996). Large variability in WUE has been reported in several Brassica species (Hall et al., 2005). Because higher rates of leaf photosynthesis are often associated with faster crop growth rates, a combination of higher photosynthesis and improved WUE may play a vital role for yield enhancement of crops under drought stress conditions (Condon et al., 2002; Parry et al., 2005). Although studies have demonstrated that the photosynthetic performance in Brassica species’ can recover once drought stress is relieved, transient photoinhibition or residual impairment of photosystems at very low gs can lead to an overall reduction in metabolism and biomass accumulation (Franks, 2011; Edwards et al., 2016). To mitigate drought stress and improve WUE, soil moisture sensing technologies have a promising future because real-time data can be used to irrigate crops only when needed.
Irrigation scheduling has a wide array of methods, including arbitrary techniques such as the soil “feel test” and farmer experience to more advanced techniques such as soil water balance calculations, crops specific growth simulation models with evapotranspiration, and soil moisture sensing methods. One important method still used is the crop water stress index that determines the irrigation needs of a crop by evapotranspiration. Erdem et al. (2010) determined that crop water stress index, a means of irrigation scheduling dependent on canopy temperatures and weather conditions, is directly correlated to predicting irrigation timing and yields of broccoli (Brassica oleracea L. var. Italica). Even though different methods are used today, the use of soil moisture sensing devices coupled with data loggers and software are gaining acceptance due to their accuracy, precision, and reliability.
Soil moisture sensing technologies such as tensiometers, granular matrix, and capacitance-based (e.g., time-domain reflectometry (TDR) and time-domain transmission) devices have been gaining a good reputation over the last decade. These soil moisture devices are relatively inexpensive and have low maintenance cost once installed. Capacitance-based soil moisture sensors are the most promising, accurate, and least likely to need calibration (Dukes et al., 2010). Thus, there is great potential for these sensors to help vegetable producers use real-time data to more accurately and precisely irrigate their crops. For example, soil moisture sensor irrigation control increased zucchini squash (Cucurbita pepo L.) WUE by 274 % when compared to vegetable producer practices of single daily time irrigation (Zotarelli et al., 2008). Additional research from Zotarelli et al. (2009) reported an irrigation savings of 40 to 65 % compared to a typical grower based timed irrigation schedule while increasing tomato (Solanum lycopersicum L.) yields by 11 to 45 %. In another study, data revealed that TDR soil moisture sensor-based irrigation treatments used 11 % and 33 % less water compared to evapotranspiration-based irrigation in cabbage (Brassica oleracea L. var. capitata) plasticulture production (Barrett et al., 2018).
There is limited research on the implementation of soil moisture sensing technologies in kale or other Brassica spp. production systems. Thus, the purpose of the current study was to determine how TDR soil moisture sensors affect kale yields, photosynthetic processes (A, Ci, gn, E, and WUE), and primary and secondary metabolites (amino acids, sugars, carotenoids, and glucosinolates).
Section snippets
Plant material and growth conditions
The study was started in November 2018 and completed in January 2019. Kale ‘Winterbor’ was transplanted into 11.36 L polybags and grown in a greenhouse at the North Mississippi Research and Extension Center, Verona, MS. Bags were filled with Pro-Mix BX soilless medium (Premier Tech Horticulture, Quebec, Canada) and a 15N-3.9P-9.9 K controlled-release fertilizer (Osmacote plus; ScottsMircale Gro, Maryville, OH) was incorporated at a rate of 5.93 kg·m-3. Once tranplanted, kale plants were thinned
Gas exchange, fresh and dry mass, and intrinsic water use efficiency
Drought stress imposed significant impacts on gas exchanges parameters (Fig. 1, Table 1). Kale plant E increased significantly from 0.15 to 0.35 m3 m3 VWC, by 18.1%. On average, at 0.15, 0.25, and 0.35 VWC were 21.83, 22.05, and 23.49 μmol CO2 m2·s-1, respectively. The Ci and gs were also significantly increased when VWC increased from 0.15 to 0.35 m3 m3. The Ci of kale plants rose by 7.7%, and the gs increased by 27.1% when comparing 0.15 to 0.35 m3 m3 VWC. However, there were no differences
Discussion
Producing high quality nutritious food with fewer inputs is at the forefront of sustainable agriculture. A part of sustainability is the increase in agricultural technologies, such as soil moisture sensors systems that allow producers to identify when and how much to irrigate a vegetable crop. In the current study, there were not differences in kale yield when comparing the 0.25 and 0.35 VWC treatments representing a savings in the production process. The savings in the production process
Funding
The funding for the experiments is based on work that is supported by the USDA-NIFA Hatch Project under accession number 149210.
CRediT authorship contribution statement
T. Casey Barickman: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Kang-Mo Ku: Methodology, Formal analysis, Investigation, Resources, Writing - original draft, Writing - review & editing, Visualization, Validation. Carl E. Sams: Validation, Investigation, Resources, Writing - review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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These authors contributed equally.