Surface irrigation management for guayule rubber production in the US desert Southwest

Hunsaker, Douglas J.; El-Shikha, Diaa M

doi:10.1016/j.agwat.2017.01.015

Cited by 29 publications

(19 citation statements)

References 21 publications

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“…Likewise, the rubber content of plants grown under stressed conditions ranged from 1.16 to 9.68% with an average of 3.94%, while under non-stressed conditions, the rubber content ranged from 0.61 to 5.84% with an average of 2.83%. The observation of higher rubber content under dry conditions coincided with previous studies [20, 32].…”

Section: Resultssupporting

confidence: 92%

“…Finally, a total of 315 guayule samples were harvested from water-stressed (147) and non-stressed (168) field plots at Maricopa, Arizona, USA. Trials were irrigated differentially to reach suitable stress levels following the soil water depletion model described by Hunsaker and Elshikha [20]. Two homogenous plants from each plot were harvested in spring of 2018.…”

Section: Methodsmentioning

confidence: 99%

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A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

2019

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BackgroundGuayule (Parthenium argentatum A. Gray), a plant native to semi-arid regions of northern Mexico and southern Texas in the United States, is an alternative source for natural rubber (NR). Rapid screening tools are needed to replace the current labor-intensive and cost-inefficient method for quantifying rubber and resin contents. Near-infrared (NIR) spectroscopy is a promising technique that simplifies and speeds up the quantification procedure without losing precision. In this study, two spectral instruments were used to rapidly quantify resin and rubber contents in 315 ground samples harvested from a guayule germplasm collection grown under different irrigation conditions at Maricopa, AZ. The effects of eight different pretreatment approaches on improving prediction models using partial least squares regression (PLSR) were investigated and compared. Important characteristic wavelengths that contribute to prominent absorbance peaks were identified.ResultsUsing two different NIR devices, ASD FieldSpec®3 performed better than Polychromix Phazir™ in improving R2 and residual predicative deviation (RPD) values of PLSR models. Compared to the models based on full-range spectra (750–2500 nm), using a subset of wavelengths (1100–2400 nm) with high sensitivity to guayule rubber and resin contents could lead to better prediction accuracy. The prediction power of the models for quantifying resin content was better than rubber content.ConclusionsIn summary, the calibrated PLSR models for resin and rubber contents were successfully developed for a diverse guayule germplasm collection and were applied to roughly screen samples in a low-cost and efficient way. This improved efficiency could enable breeders to rapidly screen large guayule populations to identify cultivars that are high in rubber and resin contents.

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Section: Resultssupporting

confidence: 92%

Section: Methodsmentioning

confidence: 99%

A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

2019

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“…In central Arizona, research at the Maricopa Agricultural Center (MAC) has developed FAO-56 approaches for irrigation management in alfalfa (Medicago sativa (L.) Lew; Hunsaker et al, 2002), camelina (Camelina sativa (L.) Crantz; Hunsaker et al, 2013), upland cotton (Gossypium hirsutum L.; Hunsaker et al, 2005aHunsaker et al, , 2015, guayule (Parthenium argentatum (A.) Gray; Hunsaker and Elshikha, 2017), and wheat (Triticum aestivium L.; Hunsaker et al, 2005bHunsaker et al, , 2007aHunsaker et al, , 2007b. These efforts resulted in the development of an FAO-56 irrigation scheduling spreadsheet that is now well-tested for a variety of crops at MAC and used routinely to manage irrigation for many field research activities at the station.…”

mentioning

confidence: 99%

Cotton Irrigation Scheduling Using a Crop Growth Model and FAO-56 Methods: Field and Simulation Studies

Thorp¹,

Hunsaker²,

Bronson³

et al. 2017

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“…The required SDI replacement fraction of ET (i.e., a range of 25% to 125% of ET) was evaluated for guayule production on sandy loam and sandy clay loam soils in Arizona (Hunsaker et al, 2019). The researchers found a linear response to total applied water, and the greatest yield was for SDI replacing 125% of ET, which was twice the guayule yield reported for the same treatment in a companion SGI study (Hunsaker and Elshikha, 2017).…”

Section: 4mentioning

confidence: 98%

A 2020 Vision of Subsurface Drip Irrigation in the U.S.

Lamm¹,

Colaizzi²,

Sorensen³

et al. 2021

Transactions of the ASABE

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HighlightsSubsurface drip irrigation (SDI) has continued to expand in irrigation area within the U.S. during the last 15 years.Research with SDI continues for multiple crop types (fiber, grain and oilseed, horticultural, forage, and turf).SDI usage on many crops has matured through research and development of appropriate strategies and technologiesDespite some persistent challenges to successful use of SDI, important opportunities exist for further adoption.Abstract. Subsurface drip irrigation (SDI) offers several advantages over alternative irrigation systems when it is designed and installed correctly and when best management practices are adopted. These advantages include the ability to apply water and nutrients directly and efficiently within the crop root zone. Disadvantages of SDI in commercial agriculture relative to alternative irrigation systems include greater capital cost per unit land area (except for small land parcels), unfamiliar management and maintenance protocols that can exacerbate the potential for emitter clogging, the visibility of system attributes (components and design characteristics) and performance, and the susceptibility to damage (i.e., rodents and tillage) of the subsurface driplines. Despite these disadvantages, SDI continues to be adopted in commercial agriculture in the U.S., and research efforts to evaluate and develop SDI systems continue as well. This article summarizes recent progress in research (2010 to 2020) and the status of commercial adoption of SDI, along with a discussion of current challenges and future opportunities. Keywords: Drip Irrigation, Irrigation, Irrigation systems, Microirrigation, SDI, Water management.

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Surface irrigation management for guayule rubber production in the US desert Southwest

Cited by 29 publications

References 21 publications

A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

Cotton Irrigation Scheduling Using a Crop Growth Model and FAO-56 Methods: Field and Simulation Studies

A 2020 Vision of Subsurface Drip Irrigation in the U.S.

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