Publications by authors named "Hugh Earl"

Drought limits the growth and development of L. (known as common bean). Common bean plants contain various phenylpropanoids, but it is not known whether the levels of these metabolites are altered by drought.

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Article Synopsis
  • The study introduces a cost-effective, passive irrigation system for studying drought tolerance in crops, specifically soybean, by controlling soil water content through a wicking bed with a float valve.
  • This method allows for easy measurement of single-plant water usage over time, enabling researchers to differentiate between various levels of drought stress and observe distinct differences in plant growth traits.
  • The findings highlight the system's applicability for high-throughput phenotyping, promising to enhance research efforts on plant responses to drought conditions.
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Article Synopsis
  • Hyperspectral data collected remotely is being used to track crop growth and development, particularly during key stages in the growing season.
  • A time series analysis of reflectance measurements during the grain filling period offers valuable insights into plant physiological responses and is available in a public database.
  • The dataset includes raw and processed hyperspectral data from 2017 and 2018, provided in spreadsheet formats along with documentation about the data collection and plant characteristics.
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Typical small-pot culture systems are not ideal for controlled environment phenotyping for drought tolerance, especially for root-related traits. We grew soybean plants in a greenhouse in 1-m rooting columns filled with amended field soil to test the effects of drought stress on water use, root growth, shoot growth, and yield components. There were three watering treatments, beginning at first flower: watered daily to 100% of the maximum soil water holding capacity (control), 75% (mild drought stress), or 50% (drought stress).

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Recent substantial advances in high-throughput field phenotyping have provided plant breeders with affordable and efficient tools for evaluating a large number of genotypes for important agronomic traits at early growth stages. Nevertheless, the implementation of large datasets generated by high-throughput phenotyping tools such as hyperspectral reflectance in cultivar development programs is still challenging due to the essential need for intensive knowledge in computational and statistical analyses. In this study, the robustness of three common machine learning (ML) algorithms, multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF), were evaluated for predicting soybean () seed yield using hyperspectral reflectance.

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In the past, there have been drought events in different parts of the world, which have negatively influenced the productivity and production of various crops including wheat ( L.), one of the world's three important cereal crops. Breeding new high yielding drought-tolerant wheat varieties is a research priority specifically in regions where climate change is predicted to result in more drought conditions.

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The pattern of soil water availability in frequently watered small pots is different from field environments. In small pots, volumetric soil water content (VSWC) is relatively high throughout the rooting zone due to a lack of suction to remove water from large and midsize capillaries. This necessitates the use of growing media with large pore space to avoid anaerobic conditions and so prohibits the use of field soil (FS) in small pots.

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The impact of grain yield on post-silking N uptake (PostN) in maize has been a major focus of previous studies, although results are mixed as to the direction and magnitude of the relationship between these two variables. The objective of this study was to understand how grain yield and other plant traits interact with exogenous N and water availability to regulate PostN in maize. In a greenhouse experiment, maize was subjected to high or low levels of N and water supply pre-silking during vegetative growth, which created large variations in source and sink components such as ear size and leaf area.

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During vegetative growth maize can accumulate luxury nitrogen (N) in excess of what is required for biomass accumulation. When post-silking N uptake is restricted, this luxury N may mitigate N stress by acting as an N reserve that buffers grain yield and maintains plant function. The objective of this study was to determine if and how luxury accumulation of N prior to silking can buffer yield against post-silking N and/or water stress in maize.

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Background: Cold temperatures and their alleviation affect many plant traits including the abundance of protein coding gene transcripts. Transcript level changes that occur in response to cold temperatures and their alleviation are shared or vary across genotypes. In this study we identify individual transcripts and groups of functionally related transcripts that consistently respond to cold and its alleviation.

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Drought is known to limit carbon assimilation in plants. However, it has been debated whether photosynthesis is primarily inhibited by stomatal or non-stomatal factors. This research assessed the underlying limitations to photosynthesis in peanuts (Arachis hypogaea L.

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Estimates of thylakoid electron transport rates (J(e)) from chlorophyll fluorometry are often used in combination with leaf gas exchange measurements to provide detailed information about photosynthetic activity of leaves in situ. Estimating J(e) requires accurate determination of the quantum efficiency of Photosystem II (Phi(P)), which in turn requires momentary light saturation of the Photosystem II light harvesting complex to induce the maximum fluorescence signal (F(M)'). In practice, full saturation is often difficult to achieve, especially when incident photosynthetic photon flux density (Q) is high and energy is effectively dissipated by non-photochemical quenching.

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