Irrigation scheduling strategies based on soil matric potential on yield and fruit quality of mulched-drip irrigated chili pepper in Northwest China

2012 ◽  
Vol 115 ◽  
pp. 232-241 ◽  
Author(s):  
Haijun Liu ◽  
Huiying Yang ◽  
Jianhua Zheng ◽  
Dongdong Jia ◽  
Jun Wang ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Northwest China ◽  
Irrigation Scheduling ◽  
Chili Pepper ◽  
Soil Matric Potential ◽  
Matric Potential ◽  
Scheduling Strategies

scholarly journals Effects of Drip Irrigation Configuration and Rate on Yield and Fruit Quality of Young Highbush Blueberry Plants

HortScience ◽  
2012 ◽  
Vol 47 (3) ◽  
pp. 414-421 ◽  
Author(s):  
David L. Ehret ◽  
Brenda Frey ◽  
Tom Forge ◽  
Tom Helmer ◽  
David R. Bryla
Keyword(s):  
Fruit Quality ◽  
Drip Irrigation ◽  
Vaccinium Corymbosum ◽  
Highbush Blueberry ◽  
Anthocyanin Content ◽  
Soil Matric Potential ◽  
Matric Potential ◽  
Total Anthocyanin ◽  
Irrigation Volume

A 4-year study was conducted to establish the effects of drip irrigation configuration and rate on fruit yield and quality of young highbush blueberry plants (Vaccinium corymbosum L. ‘Duke’). Plants were grown in a silt loam soil on raised beds and were non-irrigated or irrigated using either one or two lines of suspended drip tape. Each line configuration had in-line emitters spaced every 0.3 or 0.45 m for a total of four drip configurations. Water was applied by each drip configuration at two rates, a moderate rate of 5 L/plant per irrigation event, and a heavy rate of 10 L/plant. The frequency of irrigation was guided by measurements of soil matric potential. Irrigation was applied each year, and plants were cropped beginning the second year after planting. Rainfall was above normal in the first 2 years of the study, and differences in soil moisture were most evident in the last 2 years, in which soil matric potential increased with irrigation volume. Neither the number of irrigation lines nor emitter spacing had an effect on yield or fruit quality. Yield was unaffected by irrigation rate until the fourth year after planting and was only higher when 5 L/plant was applied. The yield increase was the result of differences in fruit weight during the second of two harvests and was associated with delays in fruit maturation. Irrigation affected plant mineral concentrations but leaves and berries responded differently; affected minerals tended to decrease in leaves but increase in the fruit. Many irrigation-induced changes in fruit quality were evident 1 or 2 years before changes in yield. Higher irrigation volume increased fruit size and water content but reduced fruit firmness and soluble solids. Irrigation reduced fruit water loss during storage and thereby promoted longer shelf life. Irrigation also resulted in a change in anthocyanin composition in the fruit but did not affect antioxidants or total anthocyanin content.

scholarly journals INFLUENCE OF IRRIGATION SCHEDULING ON FRUIT QUALITY OF YOUNG POTTED 'MANZANILLA DE SEVILLA' OLIVE TREES

2011 ◽  
pp. 177-182 ◽  
Author(s):  
A. Morales-Sillero ◽  
J.E. Fernández ◽  
J.M. Torres-Ruiz ◽  
A. Montero
Keyword(s):  
Fruit Quality ◽  
Irrigation Scheduling ◽  
Olive Trees

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.

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.

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

scholarly journals Effects of Deficit Irrigation Scheduling on Water Use, Gas Exchange, Yield, and Fruit Quality of Date Palm

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2256
Author(s):  
Maged Mohammed ◽  
Abdelkader Sallam ◽  
Muhammad Munir ◽  
Hassan Ali-Dinar
Keyword(s):  
Gas Exchange ◽  
Water Use ◽  
Fruit Quality ◽  
Deficit Irrigation ◽  
Date Palm ◽  
Irrigation Scheduling ◽  
Irrigation Systems ◽  
Irrigation Treatments ◽  
And Control

Water scarcity is very common in the arid region due to the low yearly rainfall. The cost of water for agricultural usage is extremely high in dry locations. Date palm is a high water-demanding tree throughout the year in arid regions. Therefore, the application of deficit irrigation strategies for date palm cultivation may significantly contribute to conserving irrigation water. The present study aimed to assess the effects of controlled deficit irrigation using two modern micro-irrigation systems on water use efficiency (WUE), gas exchange, fruit yield, and quality of date palm (Khalas cv.). The irrigation systems included drip irrigation (DI) and subsurface irrigation (SI) systems. The study was conducted during the 2020 and 2021 seasons at the Date Palm Research Center of Excellence, King Faisal University, Saudi Arabia. The meteorological variables of the study area were real-time monitored using cloud-based IoT (Internet of Things) to calculate the evapotranspiration reference (ETo) and control the irrigation scheduling. Three irrigation treatments (50, 75, and 100% ETc) were applied using DI and SI systems compared with the traditional surface bubbler irrigation (Control). The actual applied water at the deficit irrigation treatments of 50, 75, and 100% ETc were 27.28 ± 0.06, 44.14 ± 1.07, and 55.55 ± 0.37 m3 palm−1, respectively. At all deficit irrigation treatments, the leaf chlorophyll and gas exchange were significantly higher in the SI compared to the DI system. The yield of date palms did not differ significantly between the control and SI systems at both the level of 100 and 75% ETc. The WUE under the SI (1.09 kg m−3) was significantly higher than the DI system (0.52 kg m−3) at the 50% level. There was no significant difference regarding the fruit quality parameters between SI at 50% ETc and control at 100% ETc. Therefore, adopting deficit irrigation strategies using the SI system at 50% ETc level throughout the year could be suggested for date palm irrigation to save water, improve WUE, and maintain fruit quality.

scholarly journals Improving Yield and Quality of Processing Tomato (Lycopersicon esculentum Miller) Using Alternate Partial Root-Zone Drip Irrigation in Arid Northwest China

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1503 ◽  
Author(s):  
Di Zhao ◽  
Zhenhua Wang ◽  
Jinzhu Zhang ◽  
Wenhao Li ◽  
Bo Zhou
Keyword(s):  
Fruit Quality ◽  
Irrigation Water ◽  
Drip Irrigation ◽  
Root Zone ◽  
Northwest China ◽  
Yield Reduction ◽  
Processing Tomato ◽  
Irrigation Water Use ◽  
Arid Northwest China

Processing tomato is one of the most important economic crops in Xinjiang, China, which was constrained with severe water shortage and extreme arid climate. Alternate partial root-zone irrigation (APRI) may provide an effective way to increase irrigation water use efficiency (iWUE) without yield reduction. However, limited studies concerned about applying APRI in processing tomato plantation have been done, especially combined with drip irrigation to further control the irrigation and improve iWUE. Therefore, the two-year pot experiments were conducted to study the effects of different irrigation treatments, including three APRI treatments (irrigation quota of 67.5, 51.6, and 43.7 mm, respectively), fixed partial root-zoon drip irrigation (FPRI, 67.5 mm) and conventional drip irrigation (CDI, 67.5 mm). The results indicated that APRI was an appropriate irrigation method in processing tomato plantation in arid desert area such as Xinjiang, as high irrigation quota of APRI (APRIH) significantly improved its yield without fruit quality reduction in comparison with those of CDI. However, the yield without fruit quality of FPRI significantly decreased. Even if the irrigation quota of APRI decreased to the medium level (APRIM, 51.6 mm), iWUE by increased 31.8–32.7% on the contrary, as irrigation water was saved by 23.6%; while keeping the yield and fruit quality. Therefore, APRIM is recommended for processing tomato plantation in arid northwest China, to increase plant growth, fruit quality, yield, and iWUE synergistically.

scholarly journals YIELD AND QUALITY OF ‘PERA’ SWEET ORANGE GRAFTED ON DIFFERENT ROOTSTOCKS UNDER RAINFED CONDITIONS

2016 ◽  
Vol 38 (3) ◽  
Author(s):  
ANTONIO HÉLDER RODRIGUES SAMPAIO ◽  
MAURÍCIO ANTONIO COELHO FILHO ◽  
LAERCIO DUARTE SOUZA ◽  
RALPH BRUNO FRANÇA BRITO ◽  
ROBERVAL OLIVEIRA DA SILVA
Keyword(s):  
Fruit Quality ◽  
Sweet Orange ◽  
Fruit Production ◽  
Matric Potential ◽  
Rangpur Lime ◽  
Production Parameters ◽  
Yield And Quality ◽  
Volkamer Lemon ◽  
Cleopatra Mandarin

ABSTRACT This study aimed to evaluate, under field conditions, different combinations between ‘Pera’ sweet orange and eight rootstocks: ‘Rangpur’ lime (RL), ‘Volkamer’ lemon (VL), ‘Cleopatra’ mandarin (CM), ‘Sunki Maravilha’ mandarin (SMM), ‘Indio’ and ‘Riverside’ citrandarins, and VL x RL (‘Rangpur’ lime)-010 and TH-051 hybrids. The soil water matric potential (?m) was characterized for all scion-rootstock combinations at distance of 1.0m from the trunk at the plant row direction and depths of 0.25 m, 0.50 m 0.90 m in the dry and wet seasons. For two years, fruit production parameters and fruit quality were assessed. Differences of Ym among scion-rootstock combinations were observed during the dry season (p=0.05). The lowest Ym values for RL and the highest for TH-051 indicate the existence of different intrinsic mechanisms affecting the water extraction of each scion-rootstock combination. Rootstocks have influenced fruit yield and quality (p=0.05). The best combinations for fruit quality and production were sweet orange grafted on ‘Riverside’, ‘Indio’ and TH-051 rootstocks.

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