Crop Evapotranspiration Estimations of Red
Pepper Using Field Level Remote Sensing Data
and Energy Balance

Köksal, Eyüp Seli̇m; Artık, Cengiz; Taşan, Mehmet

doi:10.15244/pjoes/85351

Cited by 8 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the bean trial, with adequate rainfall for the majority of the season, T c values for the different treatments did not differ from each other as there was not much difference in the irrigation applied and NDVI values for the two treatments. As the fPAR and NDVI started diverging from each other as a result of irrigation applied, lower T c values relate to greater NDVI values (Köksal et al., 2019). In general, T c varied from ∼6 during the early part of the season to ∼21 during the late‐season.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Site‐specific estimation of spatiotemporal crop evapotranspiration through field‐level sensing data

El-Naggar

Hedley

2023

Agronomy Journal

View full text Add to dashboard Cite

This study integrated field‐level sensor data into the FAO‐56 Penman–Monteith algorithm to provide a site‐specific estimate of crop evapotranspiration. This was carried out at two contrasting sites for pea and bean (Manawatū) and barley (Hawke's Bay) crops managed within two irrigation management zones, at each site, under variable‐rate irrigation systems in New Zealand. Daily crop evapotranspiration estimates were calculated using data from a weather station situated at the field site combined with in‐field crop sensing data (spectral reflectance, canopy temperature, and canopy height). In addition, calibrated soil moisture data were used with a soil water balance model to compare estimations of daily crop evapotranspiration with those estimated using the crop sensing method. The results indicated that variable crop responses to different irrigation strategies and soil types provided a good opportunity to quantify different levels of spectral reflectance, canopy temperature, and consequently the estimation of crop water use. The statistical comparisons revealed that the modified FAO‐56 Penman–Monteith using crop sensor data compared well with the more conventional soil water balance approach using soil moisture data (R2 = 0.70, 0.83, 0.91 for barley, pea, and bean, respectively). Overall, the results from this study indicated that crop sensing approaches combined with the FAO‐56 Penman–Monteith model have potential to provide a more easily determined site‐specific field estimation of crop evapotranspiration than other methods, and it can take into consideration the spatiotemporal variability of crop growth in a field.

show abstract

Section: Resultsmentioning

confidence: 99%

“…(2020) and Köksal et al. (2019) is based on measurement of rainfall, irrigation water, and SWC in the rooting zone.

\begin{equation} {\mathit{ET}}_{\mathrm{ci}}={P}_{\mathrm{i}}+{I}_{\mathrm{i}}\pm \mathrm{\Delta}{\mathrm{SMC}}_{\mathrm{i}}+{D}_{\mathrm{i}} \end{equation}

…”

Section: Methodsmentioning

confidence: 99%

Site‐specific estimation of spatiotemporal crop evapotranspiration through field‐level sensing data

El-Naggar

Hedley

2023

Agronomy Journal

View full text Add to dashboard Cite

show abstract

“…Net radiation measurements are integral to understanding the energy balance of a system, and net radiometers are used in natural ecosystems, broad acre cropping, and PC agriculture ( Koksal et al., 2018 ; Rebmann et al., 2018 ; Saadon et al., 2021 ). Introducing film technology to a glasshouse that reflects and absorbs SW light will impact the energy balance of the crop and the requirements to maintain optimal crop temperatures.…”

Section: Discussionmentioning

confidence: 99%

Light blocking film in a glasshouse impacts Capsicum annuum L. yield differentially across planting season

Maier,

Chavan,

Klause

et al. 2023

Front. Plant Sci.

View full text Add to dashboard Cite

High energy costs are a barrier to producing high-quality produce at protected cropping facilities. A potential solution to mitigate high energy costs is film technology, which blocks heat-producing radiation; however, the alteration of the light environment by these films may impact crop yield and quality. Previous studies have assessed the impact of ULR 80 [i.e., light-blocking film (LBF)] on crop yield and photosynthetically active radiation (PAR); however, an assessment of the spectral environment over different seasons is important to understand potential crop impacts through different developmental phases. In this study, two varieties (red and orange) of Capsicum annuum were grown across two crop cycles: one cycle with primary crop growth in the autumn (i.e., autumn experiment [AE]) and the other with primary crop growth in the summer (i.e., summer experiment [SE]). LBF reduced PAR (roof level: 26%–30%, plant canopy level: 8%–25%) and net radiation (36%–66%). LBF also reduced total diffuse PAR (AE: 8%, SE: 15%), but the diffuse fraction of PAR increased by 7% and 9% for AE and SE, respectively, potentially resulting in differential light penetration throughout the canopy across treatments. LBF reduced near-infrared radiation (700 nm–2,500 nm), including far-red (700 nm–780 nm) at mid- and lower-canopy levels. LBF significantly altered light quantity and quality, which determined the amount of time that the crop grew under light-limited (<12 mol m−2 d−1) versus sufficient light conditions. In AE, crops were established and grown under light-limited conditions for 57% of the growing season, whereas in SE, crops were established and grown under sufficient light conditions for 66% of the growing season. Overall, LBF significantly reduced the yield in SE for both varieties (red: 29%; orange: 16%), but not in AE. The light changes in different seasons in response to LBF suggest that planting time is crucial for maximizing fruit yield when grown under a film that reduces light quantity. LBF may be unsuitable for year-round production of capsicum, and additional development of LBF is required for the film to be beneficial for saving energy during production and sustaining good crop yields in protected cropping.

show abstract

“…Especially for water shortage areas, the uneven spatiotemporal distribution of water resources aggravates the challenge of agricultural production. Therefore, quantifying agriculture water consumption for different crops over large area is important for agricultural water management in arid and semi-arid areas [5].…”

Section: Introductionmentioning

confidence: 99%

“…Fortunately, the application of remote sensing (RS) technology in earth observation provides an alternative approach for mapping ET at regional and even global scales [5,8,23,24]. Accordingly, various RS-based ET models based on surface energy balance equation have been developed to adapt to different underlying surface characteristics [25], such as the Surface Energy Balance Algorithm for Land (SEBAL) [26], the Two-Source Energy Balance Model (TSEB) [27], and the Hybrid dual-source scheme and Trapezoid framework based ET Model (HTEM) [28].…”

Section: Introductionmentioning

confidence: 99%

Estimating Growing Season Evapotranspiration and Transpiration of Major Crops over a Large Irrigation District from HJ-1A/1B Data Using a Remote Sensing-Based Dual Source Evapotranspiration Model

Shang

2020

Remote Sensing

View full text Add to dashboard Cite

Crop evapotranspiration (ET) is the largest water consumer of agriculture water in an irrigation district. Remote sensing (RS) technique has provided an effective way to map regional ET using various RS-based ET models over the past several decades. To map growing season ET of different crops and partition ET into evaporation (E) and transpiration (T) at regional scale, appropriate ET models should be further integrated with crop distribution maps in different years and crop growing seasons determined for each crop pixel. In this study, a hybrid dual-source scheme and trapezoid framework-based ET Model (HTEM) fed with HJ-1A/1B data was applied in Hetao Irrigation District (HID) of China from 2009 to 2015 to map crop growing season ET and T at 30 m resolution. The HTEM model with HJ-1A/1B data performed well in estimating ET in HID, and the finer spatial resolution of model input data can improve the estimation accuracy of ET. Combined with the annual crop planting map identified in previous study, and crop growing seasons determined from fitted Normalized Difference Vegetation Index (NDVI) curves for crop pixels, the spatial and temporal variations of growing season ET and T of major crops (maize and sunflower) were examined. The results indicate that ET and T of maize and sunflower reach their minimum values in the southwest HID with smaller crop planting density, and reach their maximum values in northwest HID with higher crop planting density. Over the study period with a decreasing trend of available irrigation water, ET and T in maize and sunflower growing seasons show decreasing trends, while ratios of T/ET show increasing trends, which implies that the adverse effect of decreased irrigation water diversion on crop growth is diminished due to the favorable portioning of E and T in cropland of HID. In addition, the calculation results of crop coefficients show that there is water stress to crop growth in the study area. The present results are helpful to better understand the spatial pattern of crop water consumption and water stress of different crops during crop growing season, and provide the basis for optimizing the spatial distribution of crop planting with less water consumption and more crop yield.

show abstract

Crop Evapotranspiration Estimations of Red Pepper Using Field Level Remote Sensing Data and Energy Balance

Cited by 8 publications

References 30 publications

Site‐specific estimation of spatiotemporal crop evapotranspiration through field‐level sensing data

Site‐specific estimation of spatiotemporal crop evapotranspiration through field‐level sensing data

Light blocking film in a glasshouse impacts Capsicum annuum L. yield differentially across planting season

Estimating Growing Season Evapotranspiration and Transpiration of Major Crops over a Large Irrigation District from HJ-1A/1B Data Using a Remote Sensing-Based Dual Source Evapotranspiration Model

Contact Info

Product

Resources

About