Hyperspectral imaging of spinach canopy under combined water and nitrogen stress to estimate biomass, water, and nitrogen content

Corti, M.; Gallina, P. Marino; Cavalli, Daniele; Cabassi, Giovanni

doi:10.1016/j.biosystemseng.2017.03.006

Cited by 65 publications

(36 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Hyperspectral imaging, another nondestructive technique, is widely used in agriculture (Lowe et al 2017). It could measure the reflectivity of light at different wavelengths and thus be used to calculate the water content, cell structure, pigment content, and nitrogen content in plant leaves (Corti et al 2017, Sytar et al 2017. Compared to traditional detection methods, infrared thermal imaging and hyperspectral imaging technologies are quicker, more efficient, and more accurate (Lowe et al 2017, Biju et al 2018.…”

Section: Introductionmentioning

confidence: 99%

Differential response of growth and photosynthesis in diverse cotton genotypes under hypoxia stress

Pan¹,

Jiang²,

Wang³

et al. 2019

Photosynt.

View full text Add to dashboard Cite

The objectives of the present study were to compare the dynamic of the growth and photosynthetic characteristics of cotton varieties contrasting in waterlogging (WL) tolerance when subjected to hypoxia stress. The growth of the WL-sensitive genotypes was notably inhibited by WL, mainly as a result of a significant reduction in the net photosynthesis (PN) after two days of hypoxia treatment; in the tolerant varieties, no significant changes in PN were observed until 8 d after hypoxia onset. The intercellular CO2 concentration and maximal photochemical efficiency of PSII significantly declined, and the nonphotochemical quenching increased in the sensitive varieties. Infrared thermography showed that a low stomatal conductance resulted in an increased leaf temperature under hypoxia stress. Spectral image analysis suggested that the pigment content and water content rapidly decreased in the leaves of the sensitive varieties. It is concluded that maintaining stomatal opening through the interaction of ethylene and abscisic acid may be an important strategy to improve waterlogging tolerance in cotton.Additional key words: chlorophyll fluorescence; Gossypium hirsutum; hyperspectral image; infrared thermal image. Abbreviations: Ci -intercellular CO2 concentration; E -transpiration rate; Fv/Fm -optimal/maximal quantum yield of PSII; gs -stomatal conductance; NDWI -normalized difference water index; NPQ -nonphotochemical quenching coefficient; PN -net photosynthetic rate; PSSRa -pigment ratio index a; qp -photochemical quenching coefficient. Acknowledgement: We appreciate the contribution of C. Li and Y.W. Nong on experimental execution. We thank to The National Natural Science Fund (No. 31471496) for financial support.

show abstract

Section: Introductionmentioning

confidence: 99%

Differential response of growth and photosynthesis in diverse cotton genotypes under hypoxia stress

Pan¹,

Jiang²,

Wang³

et al. 2019

Photosynt.

View full text Add to dashboard Cite

show abstract

“…In recent years, this technique has been effectively employed for various crops to estimate biophysical parameters, such as leaf area index [13,14], leaf and fruit pigment content [15][16][17][18], biomass [19] as well as detection of diseases and fungal infections [20][21][22][23]. Several studies have been reported on the spectral changes related to leaf water content [24,25], chlorophyll content [26] and macronutrient content, e.g., nitrogen [27,28] and potassium [29].…”

Section: Introductionmentioning

confidence: 99%

Identification of Plant Leaf Phosphorus Content at Different Growth Stages Based on Hyperspectral Reflectance

Siedliska¹,

Baranowski²,

Pastuszka-Woźniak³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Modern agriculture strives to sustainably manage fertilizer for both economic and environmental reasons. The monitoring of any nutritional (phosphorus, nitrogen, potassium) deficiency in growing plants is a challenge for precision farming technology. A study was carried out on three species of popular crops, celery (Apium graveolens L., cv. Neon), sugar beet (Beta vulgaris L., cv. Tapir) and strawberry (Fragaria × ananassa Duchesne, cv. Honeoye), fertilized with four different doses of phosphorus (P) to deliver data for non-invasive detection of P content. Results: Data obtained via biochemical analysis of the chlorophyll and carotenoid contents in plant material showed that the strongest effect of P availability for plants was in the diverse total chlorophyll content in sugar beet and celery compared to that in strawberry, in which P affects a variety of carotenoid contents in leaves. The measurements performed using hyperspectral imaging, obtained in several different stages of plant development, were applied in a supervised classification experiment. A machine learning algorithm (Backpropagation Neural Network, Random Forest, Naive Bayes and Support Vector Machine) was developed to classify plants from four variants of P fertilization. The lowest prediction accuracy was obtained for the earliest measured stage of plant development. Statistical analyses showed correlations between leaf biochemical constituents, phosphorus fertilization and the mass of the leaf/roots of the plants. Conclusions: Obtained results demonstrate that hyperspectral imaging combined with artificial intelligence methods has potential for non-invasive detection of non-homogenous phosphorus fertilization on crop levels.

show abstract

“…For this scope, hyperspectral cameras are powerful PRSs performing at high resolution (i.e., 1-5 nm) and measuring hundreds of bands in the spectral range between 350 and 2500 nm [14,23]. In the SIR regions, biotic and abiotic stress can be detected more specifically, thereby performing cause-effect analysis at a high-precision level [42]. The use of digital (multispectral and hyperspectral) cameras allows performing 3D imaging as previously described; however, being passive PRSs, digital camera acquisition requires continuous adjustments depending on the radiation source [14,23].…”

Section: Radiation Reflectance Absorbance and Transmittancementioning

confidence: 99%

“…The interaction between radiation and plant leaves-in terms of spectral reflectance, absorbance, and transmittance-can be defined as a passive process in which incoming electromagnetic radiation is affected by the relative quantity, but not in the wavelength form (as occurs, for example, in the fluorescence phenomenon). Reflectance, absorbance, and transmittance measurements can be related to plant structural and chemical characteristics [31,[41][42][43], thereby allowing the assessment of plant water and nutrient status [31,43,44] and photosynthetic activity, the detection of biotic and abiotic stress [25,27], and the evaluation of different plant physiological statuses [26,27,45]. In fact, reflectance, absorbance, and transmittance of electromagnetic radiation are influenced by plant tissue morphology and elemental and molecular composition [15].…”

Section: Radiation Reflectance Absorbance and Transmittancementioning

confidence: 99%

“…The hyperspectral images analysis system represented a clear advantage compared to the spectrophotometric methods that analyze a small area of leaf sample, since it allowed for the identification of leaf regions with different states of degradation and the establishment of decision rules about the overall quality. Another employment in spinach has regarded the use of NIR to estimate crop variables in the greenhouse under combined water and nitrogen stress [42].…”

Section: Hyperspectral Sensing Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Sensing Technologies for Precision Phenotyping in Vegetable Crops: Current Status and Future Challenges

Tripodi¹,

Massa²,

Venezia³

et al. 2018

Agronomy

View full text Add to dashboard Cite

Abstract:Increasing the ability to investigate plant functions and structure through non-invasive methods with high accuracy has become a major target in plant breeding and precision agriculture. Emerging approaches in plant phenotyping play a key role in unraveling quantitative traits responsible for growth, production, quality, and resistance to various stresses. Beyond fully automatic phenotyping systems, several promising technologies can help accurately characterize a wide range of plant traits at affordable costs and with high-throughput. In this review, we revisit the principles of proximal and remote sensing, describing the application of non-invasive devices for precision phenotyping applied to the protected horticulture. Potentiality and constraints of big data management and integration with "omics" disciplines will also be discussed.

show abstract

Hyperspectral imaging of spinach canopy under combined water and nitrogen stress to estimate biomass, water, and nitrogen content

Cited by 65 publications

References 45 publications

Differential response of growth and photosynthesis in diverse cotton genotypes under hypoxia stress

Differential response of growth and photosynthesis in diverse cotton genotypes under hypoxia stress

Identification of Plant Leaf Phosphorus Content at Different Growth Stages Based on Hyperspectral Reflectance

Sensing Technologies for Precision Phenotyping in Vegetable Crops: Current Status and Future Challenges

Contact Info

Product

Resources

About