Leaf Hyperspectral Reflectance Research Articles

Non-destructive estimation of potato leaf chlorophyll and protein contents from hyperspectral measurements using the PROSPECT radiative transfer model

Optimizing nitrogen (N) fertilization in potato (Solanum tuberosum L.) production by in-season measurements of potato N status may improve fertilizer N-use efficiency. Hyperspectral leaf reflectance and transmittance measurements can be used to assess potato N status by estimating leaf chlorophyll or N contents. This study evaluated the ability of the inverted PROSPECT radiative transfer model to predict leaf chlorophyll and N (as protein) contents. Trials were conducted with Russet Burbank and Shepody potato cultivars under different N fertility rates (0 to 300 kg N ha-1) in 2001 and 2002. Leaf reflectance and transmittance, leaf chlorophyll content, and leaf protein content were measured. Leaf chlorophyll and protein content correlated significantly (r = 0.16*, n = 584), but the relationship was strongly dependent on sampling date (r = 0.55* to 0.92*). Chlorophyll content was predicted with reasonable accuracy by the model, particularly in 2002. The low estimation accuracy in 2001 was probably related to sample variability induced by prolonged drought conditions. Protein content could not be predicted with any degree of accuracy by the model. The relative success of the PROSPECT model to predict chlorophyll content, and the good correlation between leaf chlorophyll and leaf N, suggests that it might be used as a component of a more complex leaf-canopy reflectance model to estimate chlorophyll content from reflectance spectra at the canopy level. Key words: Leaf reflectance, PROSPECT radiative transfer model, Solanum tuberosum

Selection of Optimum Reflectance Ratios for Estimating Leaf Nitrogen and Chlorophyll Concentrations of Field‐Grown Cotton

Leaf N and chlorophyll (Chl) concentrations of cotton (Gossypium hirsutum L.) are important indicators of plant N status. Laboratory determinations of plant tissue N are time consuming and costly. Measurements of leaf reflectance may provide a rapid and accurate means of estimating leaf N and Chl. Studies were conducted to determine the relationships between leaf hyperspectral reflectance (400–2500 nm) and Chl or N concentration in field‐grown cotton. One study consisted of four N rates of 0, 56, 112, and 168 kg N ha−1, and another study consisted of four mepiquat chloride (MC) rates of 0, 0.59, 1.17, and 2.34 L MC ha−1. Chlorophyll and N concentrations and reflectance of uppermost, fully expanded mainstem leaves were measured throughout the growing seasons. Reflectance at 556 and 710 nm increased significantly as N fertilizer rate decreased. Averaged across years and sampling dates, the percentage increase in reflectance at these two wavelengths was 8, 10, and 19% greater in the 112, 56, and 0 kg N ha−1 treatments, respectively, compared with the 168 kg N ha−1 treatment. The effect of MC on leaf reflectance was more complex than the N effect. In both the N and MC studies, a linear relationship was found between leaf N and a simple ratio of leaf reflectance at 517 and 413 nm (R517/R413) (r2 = 0.65–0.78***). Leaf Chl concentration was associated closely with reflectance ratios of either R708/R915 or R551/R915 (r2 = 0.67–0.76***). Our results suggest leaf reflectance can be used for real‐time monitoring of cotton plant N status and N fertilizer management in the field.

Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum

An experiment was conducted under outdoor pot-culture conditions to determine effects of nitrogen (N) deficiency on sorghum growth, physiology, and leaf hyperspectral reflectance properties. Sorghum (cv. DK 44C) was seeded in 360 twelve-litre pots filled with fine sand. All pots were irrigated with half-strength Hoagland's nutrient solution from emergence to 25 days after sowing (DAS). Thereafter, pots were separated into three identical groups and the following treatments were initiated: (1) the control (100% N) continued receiving the half-strength nutrient solution; (2) reduced N to 20% of the control (20% N); and (3) withheld N from the solution (0% N). Photosynthetic rate (Pn), chlorophyll (Chl) and N concentrations, and hyperspectral reflectance of the uppermost, fully expanded leaves were determined at 3- to 4-day-interval from 21 to 58 DAS during the N treatments. Plants were harvested 58 DAS to determine effects of N deficiency on leaf area (LA), biomass accumulation, and partitioning. Nitrogen deficiency significantly reduced LA, leaf Chl content and Pn, resulting in lower biomass production. Decreased leaf Pn due to N deficiency was mainly associated with lower stomatal conductance rather than carboxylation capacity of leaf chemistry. Among plant components of dry weights, leaf dry weight had the greatest and root dry weight had the smallest decrease under N deficiency. Nitrogen-deficit stress mainly increased leaf reflectance at 555 ( R 555) and 715 nm ( R 715) and caused a red-edge shift to shorter wavelength. Leaf N and Chl concentrations were linearly correlated with not only the reflectance ratios of R 405/ R 715 ( r 2 = 0.68 ***) and R 1075/ R 735 ( r 2 = 0.64 ***), respectively, but also the first derivatives of the reflectance (d R/d λ) in red edge centered 730 or 740 nm ( r 2 = 0.73–0.82 ***). These specific reflectance ratios or d R/d λ may be used for rapid and non-destructive estimation of sorghum leaf Chl and plant N status.

Senescence and hyperspectral reflectance of cotton leaves exposed to ultraviolet-B radiation and carbon dioxide.

The objectives of this study were to determine the effects of UV-B radiation and atmospheric carbon dioxide concentrations ([CO(2)]) on leaf senescence of cotton by measuring leaf photosynthesis and chlorophyll content and to identify changes in leaf hyperspectral reflectance occurring due to senescence and UV-B radiation. Plants were grown in controlled-environment growth chambers at two [CO(2)] (360 and 720 micro mol mol(-1)) and three levels of UV-B radiation (0, 7.7 and 15.1 kJ m(-2) day(-1)). Photosynthesis, chlorophyll, carotenoids and phenolic compounds along with leaf hyperspectral reflectance were measured on three leaves aged 12, 21 and 30 days in each of the treatments. No interaction was detected between [CO(2)] and UV-B for any of the measured parameters. Significant interactions were observed between UV-B and leaf age for photosynthesis and stomatal conductance. Elevated [CO(2)] enhanced leaf photosynthesis by 32%. On exposure to 0, 7.7 and 15.1 kJ of UV-B, the photosynthetic rates of 30-day-old leaves compared with 12-day-old leaves were reduced by 52, 76 and 86%, respectively. Chlorophyll pigments were not affected by leaf age at UV-B radiation of 0 and 7.7 kJ, but UV-B of 15.1 kJ reduced the chlorophylls by 20, 60 and 80% in 12, 21 and 30-day-old leaves, respectively. The hyperspectral reflectance between 726 and 1142 nm showed interaction for UV-B radiation and leaf age. In cotton, leaf photosynthesis can be used as an indicator of leaf senescence, as it is more sensitive than photosynthetic pigments on exposure to UV-B radiation. This study revealed that, cotton leaves senesced early on exposure to UV-B radiation as indicated by leaf photosynthesis, and leaf hyperspectral reflectance can be used to detect changes caused by UV-B and leaf ageing.

Interactive Effects of Ultraviolet‐B Radiation and Temperature on Cotton Physiology, Growth, Development and Hyperspectral Reflectance¶

ABSTRACTCurrent conditions of 2–11 kJ m−2 day−1 of UV‐B radiation and temperatures of >30°C during flowering in cotton cultivated regions are projected to increase in the future. A controlled environment study was conducted in sunlit growth chambers to determent the effects of UV‐B radiation and temperature on physiology, growth, development and leaf hyperspectral reflectance of cotton. Plants were grown in the growth chambers at three day/night temperatures (24/16° C, 30/22° C and 36/28° C) and three levels of UV‐B radiation (0, 7 and 14 kJ m−2 day−1) at each temperature from emergence to 79 days under optimum nutrient and water conditions. Increases in main stem node number and the node of first fruiting branch and decrease in duration to first flower bud (square) and flower were recorded with increase in temperature. Main effects of temperature and UV‐B radiation were significant for net photosynthetic rates, stomatal conductance, total chlorophyll and carotenoid concentrations of uppermost, fully expanded leaves during squaring and flowering. A significant interaction between temperature and UV‐B radiation was detected for total biomass and its components. The UV‐B radiation of 7 kJ m−2 day−1 reduced boll yield by 68% and 97% at 30/22°C and 36/28° C, respectively, compared with yield at 0 kJ m−2 day−1 and 30/22° C. No bolls were produced in the three temperature treatments under 14 kJ m−2 day−1 UV‐B radiation. The first‐order interactions between temperature, UV‐B radiation and leaf age were significant for leaf reflectance. This study suggests a growth‐ and process‐related temperature dependence of sensitivity to UV‐B radiation.

Interactive effects of ultraviolet-B radiation and temperature on cotton physiology, growth, development and hyperspectral reflectance.

Current conditions of 2-11 kJ m(-2) day(-1) of UV-B radiation and temperatures of >30 degrees C during flowering in cotton cultivated regions are projected to increase in the future. A controlled environment study was conducted in sunlit growth chambers to determine the effects of UV-B radiation and temperature on physiology, growth, development and leaf hyperspectral reflectance of cotton. Plants were grown in the growth chambers at three day/night temperatures (24/16 degrees C, 30/22 degrees C and 36/28 degrees C) and three levels of UV-B radiation (0, 7 and 14 kJ m(-2) day(-1)) at each temperature from emergence to 79 days under optimum nutrient and water conditions. Increases in main stem node number and the node of first fruiting branch and decrease in duration to first flower bud (square) and flower were recorded with increase in temperature. Main effects of temperature and UV-B radiation were significant for net photosynthetic rates, stomatal conductance, total chlorophyll and carotenoid concentrations of uppermost, fully expanded leaves during squaring and flowering. A significant interaction between temperature and UV-B radiation was detected for total biomass and its components. The UV-B radiation of 7 kJ m(-2) day(-1) reduced boll yield by 68% and 97% at 30/22 degrees C and 36/28 degrees C, respectively, compared with yield at 0 kJ m(-2) day(-1) and 30/22 degrees C. No bolls were produced in the three temperature treatments under 14 kJ m(-2) day(-1) UV-B radiation. The first-order interactions between temperature, UV-B radiation and leaf age were significant for leaf reflectance. This study suggests a growth- and process-related temperature dependence of sensitivity to UV-B radiation.

Corn (Zea mays L.) growth, leaf pigment concentration, photosynthesis and leaf hyperspectral reflectance properties as affected by nitrogen supply

Plant nitrogen (N) deficiency often limits crop productivity. Early detection of plant N deficiency is important for improving fertilizer N-use efficiency and crop yield. An experiment was conducted in sunlit, controlled environment chambers in the 2001 growing season to determine responses of corn (Zea mays L. cv. 33A14) growth and leaf hyperspectral reflectance properties to varying N supply. Four N treatments were: (1) half-strength Hoagland’s nutrient solution applied throughout the experiment (control); (2) 20% of control N starting 15 days after emergence (DAE); (3) 0% N starting 15 DAE; and (4) 0% N starting 23 DAE (0% NL). Plant height, the number of leaves, and leaf lengths were examined for nine plants per treatment every 3–4 days. Leaf hyperspectral reflectance, concentrations of chlorophylla, chlorophyllb, and carotenoids, leaf and canopy photosynthesis, leaf area, and leaf N concentration were also determined during the experiment. The various N treatments led to a wide range of N concentrations (11 – 48 g kg −1 DW) in uppermost fully expanded leaves. Nitrogen deficiency suppressed plant growth rate and leaf photosynthesis. At final harvest (42 DAE), plant height, leaf area and shoot biomass were 64–66% of control values for the 20% N treatment, and 46-56% of control values for the 0% N treatment. Nitrogen deficit treatments of 20% N and 0% N (Treatment 3) could be distinguished by changes in leaf spectral reflectance in wavelengths of 552 and 710 nm 7 days after treatment. Leaf reflectance at these two wavebands was negatively correlated with either leaf N (r = –0.72 and –0.75 ∗∗ ) or chlorophyll (r = –0.60 and –0.72 ∗∗ ) concentrations. In addition, higher correlations were found between leaf N concentration and reflectance ratios. The identified Nspecific spectral algorithms may be used for image interpretation and diagnosis of corn N status for site-specific N management.

Simulation of hyperspectral and directional radiance images using coupled biophysical and atmospheric radiative transfer models

Future remote sensing satellite missions exploring the earth will feature advanced hyperspectral and directional optical imaging instruments. Given the complex nature of the data to be expected from these missions, a thorough preparation for them is essential and this can be accomplished by realistic simulation of the imagery data, years before the actual launch. Based on given spectral and directional capabilities of the instrument, and in combination with biophysical land surface properties obtained from existing imagery, the spectral and directional responses of several types of vegetation and bare soil have been simulated pixel by pixel using the radiative transfer models PROSPECT (for hyperspectral leaf reflectance and transmittance), GeoSAIL (for two-layer canopy bidirectional spectral reflectance), and MODTRAN4 (for atmospheric hyperspectral and directional effects). In this way, one obtains realistically simulated hyperspectral and directional top-of-atmosphere spectral radiance images, with all major effects included, such as heterogeneity of the landscape, non-Lambertian reflectance of the land surface, the atmospheric adjacency effect, and the limited spatial resolution of the instrument. The output of the image simulations can be used to demonstrate the capabilities of future earth observation missions. In addition, instrument specifications and image acquisition strategies might be optimized on the basis of simulated image analysis results, and new advanced data assimilation procedures could be validated with realistic inputs under controlled circumstances. This paper describes the applied methodology, the study area with the input images, the set-up of the actual image simulations, and discusses the final results obtained.

Remote Detection of Rhizomania in Sugar Beets

ABSTRACT As a prelude to remote sensing of rhizomania, hyper-spectral leaf reflectance and multi-spectral canopy reflectance were used to study the physiological differences between healthy sugar beets and beets infested with Beet necrotic yellow vein virus. This study was conducted over time in the presence of declining nitrogen levels. Total leaf nitrogen was significantly lower in symptomatic beets than in healthy beets. Chlorophyll and carotenoid levels were reduced in symptomatic beets. Vegetative indices calculated from leaf spectra showed reductions in chlorophyll and carotenoids in symptomatic beets. Betacyanin levels estimated from leaf spectra were decreased at the end of the 2000 season and not in 2001. The ratio of betacyanins to chlorophyll, estimated from canopy spectra, was increased in symptomatic beets at four of seven sampling dates. Differences in betacyanin and carotenoid levels appeared to be related to disease and not nitrogen content. Vegetative indices calculated from multi-spectral canopy spectra supported results from leaf spectra. Logistic regression models that incorporate vegetative indices and reflectance correctly predicted 88.8% of the observations from leaf spectra and 87.9% of the observations for canopy reflectance into healthy or symptomatic classes. Classification was best in August with a gradual decrease in accuracy until harvest. These results indicate that remote sensing technologies can facilitate detection of rhizomania.