Non-Destructive Estimation of Aboveground Biomass in Sawgrass Communities of the Florida Everglades

Rice is an important economic and staple crop in several developing countries. Indica rice cultivars, ‘KDML105’ and ‘RD6’ are clear favourites, popular throughout world for their cooking quality, aroma, flavour, long grain, and soft texture, thus consequently dominate major plantation area in Northeastern region of Thailand. The objective of present study was to validate UAV (unmanned aerial vehicle)-derived information of rice crop traits with ground truthing non-destructive measurements in these rice varieties throughout whole life span under field environment. Plant height of cv. ‘KDML105’ was more than cv. ‘RD6’ for each respective stage. Whereas, number of tillers per clump in ‘KDML105’ exhibited stability at each developmental stage, which was in contrast to ‘RD6’ (increased continuously). Moreover, 1,000 grain weight, total grain weight and aboveground biomass were higher in ‘KDML105’ than in ‘RD6’ by 1.20, 1.82 and 3.82 folds. Four vegetative indices, ExG, EVI2, NDVI and NDRE derived from UAV platform proved out to be excellent parameters to compare KDML105 and RD6, especially in the late vegetative and reproductive developmental stages. Positive relationships between NDVI and NDRE, NDRE and total yield traits, as well as NDVI and aboveground biomass were demonstrated. In contrast, total chlorophyll pigment in cv. ‘RD6’ was higher than in cv. ‘KDML105’ leading to negative correlation with NDVI. ‘KDML105’ reflected rapid adaptation to Northeastern environments, leading to maintenance of plant height and yield components. Vegetation indices derived from UAV platform and ground truth non-destructive data exhibited high correlation. ‘KDML105’ was rapidly adapted to NE environments when compared with ‘RD6’, leading to maintenance of physiological parameters (detecting by UAV), the overall growth performances and yield traits (measuring by ground truth method). This study advocates harnessing and adopting the approach of UAV platform along with ground truthing non-destructive measurements of assessing a species/cultivars performance at broad land-use scale.

Download Full-text

Assessment of long-term protection on the aboveground biomass and organic carbon content using two non-destructive techniques: case of the Sidi Toui National Park in southern Tunisia

African Journal of Range and Forage Science ◽

10.2989/10220119.2021.1928752 ◽

2021 ◽

pp. 1-11

Author(s):

Roukaya Chibani ◽

Abderrazak Tlili ◽

Farah Ben Salem ◽

Mounir Louhaichi ◽

Azaiez Ouled Belgacem ◽

...

Keyword(s):

Organic Carbon ◽

Carbon Content ◽

Aboveground Biomass ◽

National Park ◽

Organic Carbon Content ◽

Southern Tunisia ◽

Non Destructive ◽

Non Destructive Techniques

Download Full-text

A rapid, non-destructive method for estimating aboveground biomass of salt marsh grasses

Wetlands ◽

10.1672/0277-5212(2002)022[0626:arndmf]2.0.co;2 ◽

2002 ◽

Vol 22 (3) ◽

pp. 626-630 ◽

Cited By ~ 30

Author(s):

Glen B. Thursby ◽

Marnita M. Chintala ◽

Denise Stetson ◽

Cathleen Wigand ◽

Denise M. Champlin

Keyword(s):

Salt Marsh ◽

Aboveground Biomass ◽

Non Destructive

Download Full-text

Non-destructive aboveground biomass estimation of coniferous trees using terrestrial LiDAR

Remote Sensing of Environment ◽

10.1016/j.rse.2017.08.013 ◽

2017 ◽

Vol 200 ◽

pp. 31-42 ◽

Cited By ~ 44

Author(s):

Atticus E.L. Stovall ◽

Anthony G. Vorster ◽

Ryan S. Anderson ◽

Paul H. Evangelista ◽

Herman H. Shugart

Keyword(s):

Aboveground Biomass ◽

Biomass Estimation ◽

Terrestrial Lidar ◽

Coniferous Trees ◽

Non Destructive

Download Full-text

Non-destructive aboveground biomass estimation of Leymus chinensis individual across large scale

Ecological Indicators ◽

10.1016/j.ecolind.2021.108212 ◽

2021 ◽

Vol 131 ◽

pp. 108212

Author(s):

Zhenyu Yao ◽

Hua Qing ◽

Liu Yang ◽

Liqing Zhao

Keyword(s):

Aboveground Biomass ◽

Large Scale ◽

Leymus Chinensis ◽

Biomass Estimation ◽

Non Destructive

Download Full-text

Wheat Quality Estimation Using Vision-Based Digital Image Analysis

10.21203/rs.3.rs-266773/v1 ◽

2021 ◽

Author(s):

Edina Csákvári ◽

Melinda Halassy ◽

Attila Enyedi ◽

Ferenc Gyulai ◽

József Berke

Keyword(s):

Image Analysis ◽

Real Time ◽

Digital Image ◽

Aboveground Biomass ◽

Digital Image Analysis ◽

Grain Quality ◽

Quality Parameters ◽

Wheat Quality ◽

Study Laboratory ◽

Non Destructive

Abstract BackgroundEinkorn wheat (Triticum monococcum L. subs. monococcum) plays an increasingly important role in agriculture, promoted by organic farming. Although the number of comparative studies about modern and ancient types of wheats are increasing, there are still some knowledge gaps. The aim of the present study was to compare ancient, traditional and modern wheats using novel methods, including field study, laboratory stress experiment and vision-based digital image analysis. The yield and grain quality parameters based on the field experiment were measured with a near-infrared optical laboratory analyser. In order to predict the aboveground biomass production under nutrient deficiency and drought stress, a controlled experiment was set up in a growth chamber. Processing was performed by image segmentation using the Adobe Photoshop CC 20.04.4 Camera RAW 11.2 plug-in. Digital image parameters were determined with the open source software ImageJ and expressed in pixels of projected area, perimeter, bounding rectangle and Feret’s diameter.ResultsWe presented a fast, real-time, non-destructive and low-cost method for estimation of wheat quality. Based on the results, digital area is suitable to estimate aboveground biomass. Digital area outperformed other digital variables in biomass prediction in relation to stress, but height and Feret’s diameter better correlated with yield and grain quality parameters. The developed technique is easy to use to assess the growth and health status of plants. An RGB digital camera is easy to operate and image acquisition can be done at will, meanwhile conventional laboratory instruments are relatively expensive, very expert-intensive and time consuming.ConclusionOur study showed that digital image analysis could be a viable alternate means for the real-time estimation of aboveground biomass and for predicting yield and grain quality parameters. We suggest that the combination of various vision-based methods could improve the estimation of wheat performance in a non-destructive and real-time way. The results also demonstrated that modern wheats had better yield production and grain quality compared to einkorn wheats, but the latter were not far behind, thus the cultivation of various species could provide a diverse and sustainable agriculture.

Download Full-text

A novel protocol for assessment of aboveground biomass in rangeland environments

The Rangeland Journal ◽

10.1071/rj14072 ◽

2015 ◽

Vol 37 (2) ◽

pp. 157 ◽

Cited By ~ 3

Author(s):

Charity Mundava ◽

Antonius G. T. Schut ◽

Petra Helmholz ◽

Richard Stovold ◽

Graham Donald ◽

...

Keyword(s):

Aboveground Biomass ◽

Vegetation Index ◽

Growth Models ◽

Vegetation Type ◽

Perennial Grasses ◽

Heterogeneous Environments ◽

Growing Seasons ◽

Normalised Difference Vegetation Index ◽

Bunch Grass ◽

Non Destructive

Current methods to measure aboveground biomass (AGB) do not deliver adequate results in relation to the extent and spatial variability that characterise rangelands. An optimised protocol for the assessment of AGB is presented that enables calibration and validation of remote-sensing imagery or plant growth models at suitable scales. The protocol combines a limited number of destructive samples with non-destructive measurements including normalised difference vegetation index (NDVI), canopy height and visual scores of AGB. A total of 19 sites were sampled four times during two growing seasons. Fresh and dry matter weights of dead and green components of AGB were recorded. Similarity of responses allowed grouping into Open plains sites dominated by annual grasses, Bunch grass sites dominated by perennial grasses and Spinifex (Triodia spp.) sites. Relationships between non-destructive measurements and AGB were evaluated with a simple linear regression per vegetation type. Multiple regression models were first used to identify outliers and then cross-validated using a ‘Leave-One-Out’ and ‘Leave-Site-Out’ (LSO) approach on datasets including and excluding the identified outliers. Combining all non-destructive measurements into one single regression model per vegetation type provided strong relationships for all seasons for total and green AGB (adjusted R2 values of 0.65–0.90) for datasets excluding outliers. The model provided accurate assessments of total AGB in heterogeneous environments for Bunch grass and Spinifex sites (LSO-Q2 values of 0.70–0.88), whereas assessment of green AGB was accurate for all vegetation types (LSO-Q2 values of 0.62–0.84). The protocol described can be applied at a range of scales while considerably reducing sampling time.

Download Full-text

A simple non-destructive method for estimating aboveground biomass of emergent aquatic macrophytes

Acta Limnologica Brasiliensia ◽

10.1590/s2179-975x6416 ◽

2017 ◽

Vol 29 (0) ◽

Cited By ~ 2

Author(s):

Laís Samira Correia Nunes ◽

◽

Antonio Fernando Monteiro Camargo ◽

Keyword(s):

Aboveground Biomass ◽

Aquatic Macrophytes ◽

Experimental Studies ◽

River Estuary ◽

Dry Mass ◽

Biomass Estimation ◽

Morphological Variables ◽

The Individual ◽

The Relationship ◽

Non Destructive

Abstract: Aim Non-destructive methods for estimating aquatic macrophytes biomass may be employed by using indirect measurements, especially in experimental studies, thus enabling the conservation of plant samples. It is possible to estimate macrophyte biomass by developing mathematical equations that relate the plants’ dry mass to their morphological variables. The aim of this study was to evaluate the relationship between different morphological variables and biomass in order to determine which variable is easier to be obtained for the emergent aquatic macrophytes Crinum americanum and Spartina alterniflora. Methods We obtained the aboveground area and height of individuals of both species, with different sizes and distinct developmental stages. The samples were collected in the Itanhaém River Estuary (SP, Brazil). The plants were dried in a laboratory oven and weighed so as to obtain their dry mass. Simple linear regression analyses were applied to the morphological variables and the individual dry mass to obtain equations. Results For the both species, the relationship between area and biomass, and the relationship between individual height and biomass presented significant coefficients of determination (p < 0.0001). For the elaboration of models involving the individual height, we used only one morphological measure for each individual, whereas for models involving the individual area it was necessary to obtain more than one hundred morphological measurements per individual. Conclusions The morphological variables chosen are good attributes for estimating the aboveground biomass of C. americanum and S. alterniflora. Considering the models’ adjustment and the consumed time to obtain the measurements, we conclude that the individual height measurement is better for biomass estimation for both species.

Download Full-text