Deficiência hídrica simulada nos diferentes estádios de desenvolvimento de um cultivar precoce de soja

Nogueira, Sandra Dos Santos Sevá; Nagai, Violeta

doi:10.1590/s0006-87051988000100002

Cited by 6 publications

(3 citation statements)

References 6 publications

(3 reference statements)

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“…However, among plants submitted to drought stress at the reproductive stage, grain yield was significantly lower than was the case of plants under water deficit induced at the vegetative stage under either natural conditions or irrigation. Thus, water withholding at the reproductive stage was more harmful to soybean production, as has also been reported by several authors in studies evaluating soybean plants submitted to different water availability levels (Nogueira and Nagai 1988;de Paiva Rolla et al 2014;Carvalho et al 2015;Crusiol et al 2017).…”

Section: Canopy Temperature and Nrctsupporting

confidence: 73%

UAV-based thermal imaging in the assessment of water status of soybean plants

Crusiol

Nanni

Furlanetto

et al. 2019

International Journal of Remote Sensing

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Soybean production both in Brazil and globally has regularly been threatened by drought periods. The use of infrared thermography to evaluate the canopy's temperature and its relationship with plant water status constitutes an important tool for agricultural monitoring. However, studies regarding the water status of soybean plants through unmanned aerial vehicle (UAV)-based thermal imaging are yet to be reported. Thus, the present study aimed to evaluate the water status of soybean plants submitted to different water conditions via thermal images obtained through an UAV thermal infrared camera. The field experiment was undertaken at the National Soybean Research Centre (Embrapa Soja, a branch of the Brazilian Agricultural Research Corporation) in a randomized complete block design, with four replicates. The following water conditions were evaluated: irrigated (IRR, receiving rainfall and irrigation when necessary, and with a soil water matric potential between −0.03 MPa and −0.05 MPa), non-irrigated (NIRR, receiving only rainfall), and water deficit (or drought stress) induced at the vegetative (DSV) and reproductive (DSR) stages. Water deficit was induced using rainout shelters. Soil moisture and weather data were monitored daily. Thermal images were obtained on twelve dates, half in 2016-2017 and half during the 2017-2018 crop seasons, through a thermal infrared camera (DIY-Thermocam) sensitive to temperatures ranging from -40°C to 200°C, with 0.5 °C accuracy and 14-bit radiometric resolution. Images in RAW format (160 pixels x120 pixels) were obtained at 125 m above ground level. They were then processed and calibrated by acquiring a correction factor resulting from the effect of atmospheric attenuation. The canopy temperature was evaluated in relation to that of air temperature and through the Normalized Relative Canopy Temperature (NRCT). Atmospheric attenuation was positively correlated to flight altitude, so that image correction eliminated such an effect. The thermal behaviour of soybean plants was directly correlated to soil water availability and atmospheric vapour pressure deficit, with differences ranging from 0.2 °C to 7.2°C. Plants grown at lower soil moisture conditions had higher temperatures, which were

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Section: Canopy Temperature and Nrctsupporting

confidence: 73%

UAV-based thermal imaging in the assessment of water status of soybean plants

Crusiol

Nanni

Furlanetto

et al. 2019

International Journal of Remote Sensing

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“…This result may be related to a trait inherited from one of their parents. Nogueira et al (2015), working with cultivar Packham's Triumph, detected 12 anthers per flower. Cultivars Seleta and Tenra showed a small number of pollen grains per anther and per flower.…”

Section: Number Of Anthers Per Flower and Pollen Grains Per Anther Anmentioning

confidence: 99%

Determination of Potential Pollinizer Grafted Pear Hybrids (Pyrus communis × Pyrus pyrifolia) for Subtropical Regions in Brazil

Bisi¹,

Pio²,

Locatelli³

et al. 2019

JAS

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The pear tree is originally a temperate-climate fruit tree. The cross Pyrus communis × Pyrus pyrifolia generated hybrid cultivars adapted to subtropical regions. However, the low effective fruiting is a limiting factor for the expansion of pear tree crops in subtropical regions and no pollinizer plants have been identified for these cultivars in subtropical regions. This work aimed to identify possible pollinizer pear tree cultivars in subtropical regions by evaluating the stigmatic receptivity, the germination percentage, and the number of pollen grains. Seven hybrid pear cultivars were used. Flowers of each cultivar at each floral stage were collected (E, E2, F, F2, and G). The stigmatic receptivity was evaluated by immersing the material in 3% hydrogen peroxide. Flowers were collected for the quantification of anthers, pollen grains per anther and per flower, and pollen grain germination. Stigmas were 100% receptive for all cultivars at the F2 and G stages. Cultivar Cascatense showed a large number of anthers and pollen grains per anther and per flower. The highest pollen grain germination percentage was detected for Cascatense (72.75%). Cultivars Seleta and Triunfo have high stigmatic receptivity for a longer period during the flowering stage, proven to be a potential female parent. Cascatense has a higher germination percentage and a larger number of anthers per flower, pollen grains per anther, and pollen grains per flower. Cascatense has a high potential to be used as a pollinizer, both in pear tree breeding programs and commercial orchards.

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“…In turn, soybean plants subjected to water deficit during the vegetative stages presented grain yield similar to plants under natural rainfall (NIRR treatment), demonstrating that the water deprivation during reproductive stages is more harmful to soybean crop. Several authors have reported similar values of soybean yield on plants under water deficit during the vegetative stages (and rain watered during reproductive stages) compared to plants under good conditions of water availability [49][50][51][52].…”

Section: Effect Of Experimental Treatments On Climatic Water Balance Soil Moisture Grain Yield and Leaf Reflectancementioning

confidence: 89%

Yield Prediction in Soybean Crop Grown under Different Levels of Water Availability Using Reflectance Spectroscopy and Partial Least Squares Regression

et al. 2021

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Soybean grain yield has regularly been impaired by drought periods, and the future climatic scenarios for soybean production might drastically impact yields worldwide. In this context, the knowledge of soybean yield is extremely important to subsidize government and corporative decisions over technical issues. This paper aimed to predict grain yield in soybean crop grown under different levels of water availability using reflectance spectroscopy and partial least square regression (PLSR). Field experiments were undertaken at Embrapa Soja (Brazilian Agricultural Research Corporation) in the 2016/2017, 2017/2018 and 2018/2019 cropping seasons. The data collected were analyzed following a split plot model in a randomized complete block design, with four blocks. The following water conditions were distributed in the field plots: irrigated (IRR), non-irrigated (NIRR) and water deficit induced at the vegetative (WDV) and reproductive stages (WDR) using rainout shelters. Soybean genotypes with different responses to water deficit were distributed in the subplots. Soil moisture and weather data were monitored daily. A total of 7216 leaf reflectance (from 400 to 2500 nm, measured by the FieldSpec 3 Jr spectroradiometer) was collected at 24 days in the three cropping seasons. The PLSR (p ≤ 0.05) was performed to predict soybean grain yield by its leaf-based reflectance spectroscopy. The results demonstrated the highest accuracy in soybean grain yield prediction at the R5 phenological stage, corresponding to the period when grains are being formed (R2 ranging from 0.731 to 0.924 and the RMSE from 334 to 403 kg ha−1—7.77 to 11.33%). Analyzing the three cropping seasons into a single PLSR model at R5 stage, R2 equal to 0.775, 0.730 and 0.688 were obtained at the calibration, cross-validation and external validation stages, with RMSE lower than 634 kg ha−1 (13.34%). The PLSR demonstrated higher accuracy in plants submitted to water deficit both at the vegetative and reproductive periods in comparison to plants under natural rainfall or irrigation.

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Deficiência hídrica simulada nos diferentes estádios de desenvolvimento de um cultivar precoce de soja

Cited by 6 publications

References 6 publications

UAV-based thermal imaging in the assessment of water status of soybean plants

UAV-based thermal imaging in the assessment of water status of soybean plants

Determination of Potential Pollinizer Grafted Pear Hybrids (Pyrus communis × Pyrus pyrifolia) for Subtropical Regions in Brazil

Yield Prediction in Soybean Crop Grown under Different Levels of Water Availability Using Reflectance Spectroscopy and Partial Least Squares Regression

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