scholarly journals Post-transplant Irrigation Scheduling for Two Native Deciduous Shrub Taxa

HortScience ◽  
2010 ◽  
Vol 45 (11) ◽  
pp. 1620-1625
Author(s):  
Abby B. Griffin ◽  
Amy N. Wright ◽  
Kenneth M. Tilt ◽  
D. Joseph Eakes
Keyword(s):  
Shoot Growth ◽  
Sandy Loam ◽  
Irrigation Scheduling ◽  
Soil Matric Potential ◽  
Stem Water Potential ◽  
Irrigation Frequency ◽  
Matric Potential ◽  
Post Transplant ◽  
Backfill Soil ◽  
Surrounding Soil

The effect of five irrigation scheduling treatments on shoot growth [growth index (GI)] and stem water potential (SWP) of Itea virginica L. ‘Henry's Garnet’ (‘Henry's Garnet’ sweetspire) and Rhododendron austrinum Rehd. (Florida flame azalea) were studied. Plants were transplanted on 13 Mar. 2008 at soil grade level under shade structures in field plots of sandy loam soil on the Auburn University campus in Auburn, AL. Matric potential was continuously measured 7.6 cm from the stem in the root ball and 20.3 cm from the stem in the soil backfill for three plants per treatment per taxa. Irrigation scheduling treatments included (in order of decreasing irrigation frequency): root ball and surrounding soil matric potential maintained at or above –25 kPa [well-watered (WW)]; root ball and surrounding soil rewatered when root ball matric potential dropped to either –50 kPa (50RB) or –75 kPa (75RB); and root ball and surrounding soil rewatered when surrounding soil matric potential dropped to either –25 kPa (25S) or –50 kPa (50S). In both taxa, GI increased linearly over time in all five irrigation treatments. For I. virginica ‘Henry's Garnet’, GI increased most in WW and 25S treatments followed by 50S, 50RB, and 75RB. Shoot growth of R. austrinum was similar among treatments. Both I. virginica ‘Henry's Garnet’ and R. austrinum had a larger increase in GI during the first growing season (2008). For I. virginica ‘Henry's Garnet’, SWP was higher in 50S and 75RB treatments than in 50RB, WW, and 25S. For R. austrinum, SWP was not different among treatments. Results indicate that although plant growth might be diminished slightly, irrigation frequency can be reduced without compromising plant visual quality or survival if root ball and soil matric potential is monitored. Additionally, until roots grow into the backfill soil, monitoring both backfill soil and root ball matric potential is important for scheduling and reducing post-transplant irrigation applications.

scholarly journals 355 REDUCING MECHANICAL IMPEDANCE OF ROOTS IN COMPACTED SOILS INCREASES ROOT AND SHOOT GROWTH

HortScience ◽  
1994 ◽  
Vol 29 (5) ◽  
pp. 481e-481
Author(s):  
Susan D. Day ◽  
Nina L. Bassuk
Keyword(s):  
Root Growth ◽  
Shoot Growth ◽  
Sandy Loam ◽  
Mechanical Impedance ◽  
Compacted Soils ◽  
Vertical Drains ◽  
Pyrus Calleryana ◽  
Vertical Drainage ◽  
Root And Shoot Growth ◽  
Surrounding Soil

Four techniques for compaction amelioration were studied: 1) Vertical drainage panels; 2) vertical gravel-filled sump drains; 3) soil trenches filled with sandy loam; and 4) peat amended back fill. The control was backfilled with existing soil on the site. Vertical drainage mats and vertical gravel-filled sump drains were shown to increase O2% in surrounding soil; however, all O2 levels regardless of treatment were above what is considered limiting. Shoot and root growth of Pyrus calleryana `Redspire' was greatest for treatments that alleviated mechanical impedance (soil trenches and amended back fill) and least for treatments that did not (controls and vertical drains). Vertical drainage mats which alleviated mechanical impedance to a lesser degree showed intermediate growth.

Evaluation of Two Recurrent Neural Network Methods for Prediction of Irrigation Rate and Timing

2020 ◽  
Vol 63 (5) ◽  
pp. 1327-1348
Author(s):  
Andrés F. Jiménez ◽  
Brenda V. Ortiz ◽  
Luca Bondesan ◽  
Guilherme Morata ◽  
Damianos Damianidis
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Recurrent Neural Network ◽  
Recurrent Neural Networks ◽  
Irrigation Scheduling ◽  
Soil Types ◽  
List Type ◽  
Soil Matric Potential ◽  
Matric Potential ◽  
Network Methods

HighlightsNARX and LSTM recurrent neural networks were evaluated for prediction of irrigation prescriptions.LSTM neural networks presented the best performance for irrigation scheduling using soil matric potential sensors.NARX neural networks had the best performance for predicting irrigation prescriptions using weather data.High performance for several time-ahead predictions using both recurrent neural networks, with R2 > 0.94.The results can be adopted as a decision-support tool in irrigation scheduling for fields with different types of soils.Abstract. The implementation of adequate irrigation strategies could be done through real-time monitoring of soil water status at several soil depths; however, this could also represent a complex nonlinear problem due to the plant-soil-weather relationships. In this study, two recurrent neural network (RNN) models were evaluated to estimate irrigation prescriptions. Data for this study were collected from an on-farm corn irrigation study conducted between 2017 and 2019 in Samson, Alabama. The study used hourly data of weather and soil matric potential (SMP) monitored at three soil depths from 13 sensor probes installed on a loamy fine sand soil and a sandy clay loam soil. Two neural network methods, i.e., a nonlinear autoregressive with exogenous (NARX) input system and long short-term memory (LSTM), were trained, validated, and tested with a maximum dataset of 20,052 records and a maximum of eight categorical attributes to estimate one-step irrigation prescriptions. The performance of both methods was evaluated by varying the model development parameters (neurons or blocks, dropout, and epochs) and determining their impact on the final model prediction. Results showed that both RNN models demonstrated good capability in the prediction of irrigation prescriptions for the soil types studied, with a coefficient of determination (R2) > 0.94 and root mean square error (RMSE) < 1.2 mm. The results of this study indicate that after training the RNNs using the dataset collected in the field, models using only SMP sensors at three soil depths obtained the best performance, followed by models that used only data of solar radiation, temperature, and relative humidity in the prediction of irrigation prescriptions. For future applicability, the RNN models can be extended using datasets from other places for training, which would allow the adoption of a unique data-driven soil moisture model for irrigation scheduling useful in a wide range of soil types. Keywords: Corn, Irrigation scheduling, Machine learning, Modeling, Soil matric potential sensor.

Measurement of soil matric potential under 'Williams' Bon Cretien' pear comparing regulated deficit with normal irrigation

1992 ◽  
Vol 32 (4) ◽  
pp. 487
Author(s):  
I Goodwin ◽  
PD Mitchell ◽  
PH Jerie
Keyword(s):  
Shoot Growth ◽  
Small Volume ◽  
Initial Period ◽  
Central Position ◽  
Soil Matric Potential ◽  
Tree Line ◽  
Grid Pattern ◽  
Matric Potential ◽  
Regulated Deficit Irrigation ◽  
Pyrus Communis L

Soil matric potential (SMP) was measured under close planted 'William Bon Cretian' pear (Pyrus communis L.) after a period of withholding irrigation and during a period of regulated deficit irrigation (RDI). Trees were trickle irrigated with 20% replacement of pan evaporation over the planting square (Eps) after an initial period without irrigation, and compared with trees constantly irrigated at 80% Eps. Midway between 2 pairs of trees in each treatment (henceforth the 20% and 80% trees), gypsum blocks were installed in a grid pattern at depths of 10, 25, and 40 cm in the tree line and at 30 and 60 cm on the west and east sides of the tree line, to measure soil matric potential (SMP). The blocks were measured prior to, and 12 h, after irrigation. Consistent with previous results under RDI, shoot growth decreased and yields increased on the 20% relative to the 80% trees. Measured SMPs thus represent suitable levels for RDI. After withholding irrigation, SMPs at the 10 and 25 cm depths ranged between -1.25 and -2.61 MPa in the central position, but were less negative away from the tree line (-0.4 to -2.08) and at the 40 cm depth (-0.35 to -0.91). When averaged over all measurement dates during RDI, pre- and post-irrigation SMPs were more negative at all sites under the 20% compared with the 80% treatments. The pattern of wetting under the 20% treatment was restricted to the central tree line, with some skewing towards the east. Within this soil volume SMP fluctuated between irrigations, and prior to irrigation ranged between -0.3 and -0.7 MPa. As it was likely that only a small fraction of the available subsoil moisture was utilised, available water under the 20% treatment probably was confined to this small volume of soil.

Influence of soil matric potential on 14C exudation from fungal propagules

1987 ◽  
Vol 65 (10) ◽  
pp. 2084-2089 ◽  
Author(s):  
A. B. Filonow ◽  
D. K. Arora
Keyword(s):  
Water Content ◽  
Sandy Loam ◽  
Macrophomina Phaseolina ◽  
Sandy Loam Soil ◽  
Soil Matric Potential ◽  
Clay Loam ◽  
Clay Loam Soil ◽  
Matric Potential ◽  
Fungal Propagules ◽  
Loam Soil

The influence of soil matric potential (ψm) on 14C exudation from labeled fungal propagules incubated in two soils over 5 days was determined, using tensiometers set at 0, −50, −100, and −200 mbar ψm (1 bar = 100 kPa). In general, 14C exudation to soil (as a percent of initial label) tended to be greatest at 0 mbar and decreasing ψm. In a sandy loam soil, the range of 14C exudation from conidia of Bipolaris victoriae or sclerotia of Macrophomina phaseolina was 18.4–20.9 or 4.4–5.5% at 0 mbar. At −200 mbar, it was 5.5–6.0 or 1.2–1.7%, respectively. In a clay loam soil at 0 mbar, conidia of B. victoriae or B. sorokiniana lost 17.6–19.9 or 7.3–9.2%, respectively, of total 14C label as exudate. At −200 mbar 14.6 or 5.9–7.2% was lost, respectively. Sclerotia of M. phaseolina lost 5.1–5.7% 14C-labeled exudate to the clay loam soil at 0 mbar and 4.3–4.6% at −200 mbar. 14C exudation at ψm less than saturation was about 2–3 times greater in the clay loam soil than in the sandy loam soil. Calculated ratios of evolved 14CO2/total 14C-labeled exudate were lowest at 0 mbar and increased as ψm decreased, suggesting that oxygen availability and soil water content as regulated by ψm were related to soil respiratory utilization of exudate.

Soil matric potential-based irrigation scheduling to rice (Oryza sativa)

2005 ◽  
Vol 23 (4) ◽  
pp. 153-159 ◽  
Author(s):  
S. S. Kukal ◽  
G. S. Hira ◽  
A. S. Sidhu
Keyword(s):  
Oryza Sativa ◽  
Irrigation Scheduling ◽  
Soil Matric Potential ◽  
Matric Potential
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