Dr Nataša Ljubičić (F) Research associate, received the Ph.D. degrees from the Faculty of Agriculture, University of Novi Sad, in Serbia in the field of Genetics and Plant Breeding. She holds her Master thesis with the name: ”Multivariate analysis of wheat genotypes grown on meliorated Solonjec soil”, where she investigated different plant responses through genotype/environment interaction caused by different types of soil melioration. In Doctoral dissertation, namely "Genetic inheritance in wheat crossing", it was estimated variability, gene effect and inheritance of yield components, while non-allelic interactions, epistatic gene effect, were estimated in the inheritance of yield components using the additive-dominance model. Dr Nataša Ljubičić is a Research associate at BioSense Institute, University of Novi Sad, Serbia. Her research interests include using and implementing innovative and smart technology in agricultural and environmental investigations, following genotype/environment interaction, plant response within different mineral nutrition, nutrition, plant stress, phenotypic variability of the plant traits of the agricultural crops. Her investigation involved research from plant scale to large-scale evaluation with the main aim to improve agricultural production. She is the author and co-author of more than 50 journal and conference papers on international and national levels and Technical solutions. Address: Novi Sad Serbia
The aim of this paper is to analyze the factors leading to low adoption rate of precision farming... more The aim of this paper is to analyze the factors leading to low adoption rate of precision farming in Serbia and to describe steps being taken by BioSense institute to increase it. The majority of the arable land in Serbia is grown by small family owned and operated farms most of which are in the range of 2 to 5 ha making them highly unsustainable. Only 16% of the arable land is managed by agricultural companies and cooperatives. We believe that the adoption of advanced technologies with the currently available precision farming solutions is low among the small farmers due to the small size of the agricultural fields and their inability to invest in technologies. Therefore BioSense institute aims to develop low cost, easy to use precision farming solutions that can be applied anywhere regardless of size, the type and age of agricultural machinery used by the farmers and make IT an important tool to drive small farms towards sustainability. With the new applications developed by BioSense all farmers, even small, can benefit from the diffusion of IT into agriculture making precision farming widely accepted in the years to come. In the framework of the “Digital Agriculture of Serbia” program, several technologies are being developed in the areas of nano and microelectronic in-situ sensors, robotic platforms, genotyping/phenotypic, remote sensing (UAS, satellites), internet of things (IoT), and big data analytics as a means to create new information and extract new knowledge that is not otherwise available. A web-based and android-based digital platform named “AgroSense” was recently released for public use and got widely accepted with a large number of large, medium and small farmers registering to the system. The platform brings the benefits of IT to the end users providing free and paid tools (for advanced users) for better decision making. It is also an excellent tool for big data collection that will create new agronomic knowledge. We foresee a great potential for advancing and modernizing farming in Serbia leading towards a more sustainable and environmentally friendly agriculture.
Aflatoxin, a naturally occurring toxin produced by the fungus Aspergillus flavus, is the most eco... more Aflatoxin, a naturally occurring toxin produced by the fungus Aspergillus flavus, is the most economically important mycotoxin in the world, with harmful effects on human and animal health. Preventive measures such as irrigation and planting dates can minimize aflatoxin contamination most years. However, no control strategy is completely effective when environmental conditions are extremely favorable for growth of the fungus. The most effective control method is growing maize hybrids with genetic resistance to aflatoxin contamination. The aim of this research was to evaluate the sensitivity of different maize hybrids to A. flavus infection and aflatoxin accumulation. Twenty commercial maize hybrids were evaluated in field trials with artificial inoculations using the colonized toothpicks method. The mycotoxin production potential of A. flavus isolates was confirmed by cluster amplification patterns (CAPs) analysis. The results of this research indicated the existence of significant ...
Alfalfa is the most important forage legume in our agroecological conditions for feeding cattle. ... more Alfalfa is the most important forage legume in our agroecological conditions for feeding cattle. In the area of Jablanica district, alfalfa occupies a considerable place in the total plant production. The restrictive factor in the establishment and short durability of alfalfa stand is the low pH of arable agricultural soil. Within the three-year field trial on Vertisol soil type (pH in KCl 4.9), from 2016 to 2018, alfalfa plot yield has been analyzed with different fertilization variants. The research results indicate that alfalfa provides a significantly higher yield on the plot where amelioration measures were applied, through the application of limestone and manure, with the addition of mineral fertilizer. A barely lower yield was achieved on the calcified and manured plot, while the lowest yield was on the control plot, where a generous amount of mineral fertilizer was added, which is a common practice of agricultural producers in the area of Jablanica district.
Evaluating maize genotypes under different conditions is important for identifying which genotype... more Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes grown in field trials; one control trial without nitrogen, and three applying different levels of nitrogen (0, 70, 140, and 210 kg ha−1, respectively). Across two growing seasons, both the phenotypic variability and GEI for yield traits over four maize genotypes (P0725, P9889, P9757 and P9074) grown in four different fertilization treatments were studied. The additive main effects and multiplicative interaction (AMMI) models were used to estimate the GEI. The results revealed that genotype and environmental effects, such as the GEI effect, significantly influenced yield, as well as revealing that maize genotypes responded differently to different conditions and fertilization measures. An...
INTRODUCTION: The less productive soils present one of the major problems in wheat production ove... more INTRODUCTION: The less productive soils present one of the major problems in wheat production over the world. Considering the importance of wheat production, it is necessary to better utilize the less productive soils and to select wheat varieties that can be successfully grown on such soils. Since that the grain yield of wheat is complex and variable trait that depends on numerous yield components and environmental factors, individual characteristics of the plant, such as the number of grains per spike, grain weight per spike, plant height and harvest index, are important in the formation of grain yield, especially in the stressful conditions of wheat cultivation. The investigation of variability and assessment the interrelationship of yield components could improve cultivar creation, selection and ability of a wheat cultivar to produce high and stable yield over a wide range of environments. OBJECTIVES: The objective of this study was to estimate the mean values the yield componen...
Grain yield of wheat is a complex trait made up of the interaction between different yield compon... more Grain yield of wheat is a complex trait made up of the interaction between different yield components and environmental effects. Due to the importance of yield traits, breeders need efficient and precise methods to measure differences among genotypes. Since that spectral proximal sensing is promising for high-throughput non-destructivephenotyping, recent findings suggest that multispectral proximal sensors can be used in place of labour intensive methods to estimate specific plant traits. The objective of this study was to evaluate the impact of different spectral reflectance indices (SRIs) in assessing stem height and spike length in 4 winter wheat genotypes grown in different conditions of seed priming. Seeds of each winter wheat genotypes were primed with different concentrations of zinc oxide nanoparticles (ZnO NPs) and after sown in soil pots. Spectral reflectance from the plants at different growth stages during vegetation was measured using an active multispectral, optical se...
With an increasing interest of the agricultural community in precision agriculture, this paper ai... more With an increasing interest of the agricultural community in precision agriculture, this paper aims to compare two novel sensing approaches for crop monitoring. The recently developed multispectral proximal sensor named Plant-O-Meter and Sentinel-2 satellite, which carries a multispectral optical instrument, are two sensors suitable for agricultural applications. Each of them has pros and cons regarding spatial, spectral and temporal resolutions and their complementary use will surely bring added value compared to information retrieved by a single sensor. In order to correctly address the problem of data fusion, compatibility studies between the two sensors are necessary. In this study, a maize field was sensed on several dates in 2018 growing season using both sensors. Numerous vegetation indices based on different spectral channel combinations were calculated and the results were compared using linear regression analysis. First results showed good positive correlations between the...
The challenges of the global food supply and environment conservation require ongoing scientific ... more The challenges of the global food supply and environment conservation require ongoing scientific observations of soil-to-plant and plant-to-environment interactions with the aim of improving agriculture resource management. This study included observations of winter wheat yield and biomass of four varieties over three consecutive growing seasons and four site-year cases to assess the effects of nitrogen (N) fertilization rate and time of application on grain yield and biomass. For different wheat varieties, the full factorial design was performed, where factorial combinations of year, location, fall and spring N applications were laid out in a randomized complete block design. The N rate significantly influenced grain yield and biomass production efficiency. The time of N application had a highly significant effect on grain yield, biomass and NUE traits. The N rate of 120 kg ha−1 was recognized as a breakpoint over which the grain yield and biomass showed a downtrend. N application ...
Active proximal sensing has been increasingly used to provide information about canopy properties... more Active proximal sensing has been increasingly used to provide information about canopy properties in a large range of crops. In this study a low cost, active multispectral optical device named Plant-OMeter (POM) was tested in real conditions at two experimental fields comparing it with the GreenSeeker handheld device. Treatments included five nitrogen (N) fertilisation rates applied during sowing. Maize was scanned between V5 to V8 growth stages. The results showed that measuring with the POM sensor within this growth stage window can provide good estimation of end-of-season yield, comparable to the GreenSeeker. This indicates that Plant-O-Meter exhibits strong potential for accurate plant canopy measurements and for real time variable rate fertilisation applications in maize
The aim of this paper is to analyze the factors leading to low adoption rate of precision farming... more The aim of this paper is to analyze the factors leading to low adoption rate of precision farming in Serbia and to describe steps being taken by BioSense institute to increase it. The majority of the arable land in Serbia is grown by small family owned and operated farms most of which are in the range of 2 to 5 ha making them highly unsustainable. Only 16% of the arable land is managed by agricultural companies and cooperatives. We believe that the adoption of advanced technologies with the currently available precision farming solutions is low among the small farmers due to the small size of the agricultural fields and their inability to invest in technologies. Therefore BioSense institute aims to develop low cost, easy to use precision farming solutions that can be applied anywhere regardless of size, the type and age of agricultural machinery used by the farmers and make IT an important tool to drive small farms towards sustainability. With the new applications developed by BioSense all farmers, even small, can benefit from the diffusion of IT into agriculture making precision farming widely accepted in the years to come. In the framework of the “Digital Agriculture of Serbia” program, several technologies are being developed in the areas of nano and microelectronic in-situ sensors, robotic platforms, genotyping/phenotypic, remote sensing (UAS, satellites), internet of things (IoT), and big data analytics as a means to create new information and extract new knowledge that is not otherwise available. A web-based and android-based digital platform named “AgroSense” was recently released for public use and got widely accepted with a large number of large, medium and small farmers registering to the system. The platform brings the benefits of IT to the end users providing free and paid tools (for advanced users) for better decision making. It is also an excellent tool for big data collection that will create new agronomic knowledge. We foresee a great potential for advancing and modernizing farming in Serbia leading towards a more sustainable and environmentally friendly agriculture.
Aflatoxin, a naturally occurring toxin produced by the fungus Aspergillus flavus, is the most eco... more Aflatoxin, a naturally occurring toxin produced by the fungus Aspergillus flavus, is the most economically important mycotoxin in the world, with harmful effects on human and animal health. Preventive measures such as irrigation and planting dates can minimize aflatoxin contamination most years. However, no control strategy is completely effective when environmental conditions are extremely favorable for growth of the fungus. The most effective control method is growing maize hybrids with genetic resistance to aflatoxin contamination. The aim of this research was to evaluate the sensitivity of different maize hybrids to A. flavus infection and aflatoxin accumulation. Twenty commercial maize hybrids were evaluated in field trials with artificial inoculations using the colonized toothpicks method. The mycotoxin production potential of A. flavus isolates was confirmed by cluster amplification patterns (CAPs) analysis. The results of this research indicated the existence of significant ...
Alfalfa is the most important forage legume in our agroecological conditions for feeding cattle. ... more Alfalfa is the most important forage legume in our agroecological conditions for feeding cattle. In the area of Jablanica district, alfalfa occupies a considerable place in the total plant production. The restrictive factor in the establishment and short durability of alfalfa stand is the low pH of arable agricultural soil. Within the three-year field trial on Vertisol soil type (pH in KCl 4.9), from 2016 to 2018, alfalfa plot yield has been analyzed with different fertilization variants. The research results indicate that alfalfa provides a significantly higher yield on the plot where amelioration measures were applied, through the application of limestone and manure, with the addition of mineral fertilizer. A barely lower yield was achieved on the calcified and manured plot, while the lowest yield was on the control plot, where a generous amount of mineral fertilizer was added, which is a common practice of agricultural producers in the area of Jablanica district.
Evaluating maize genotypes under different conditions is important for identifying which genotype... more Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes grown in field trials; one control trial without nitrogen, and three applying different levels of nitrogen (0, 70, 140, and 210 kg ha−1, respectively). Across two growing seasons, both the phenotypic variability and GEI for yield traits over four maize genotypes (P0725, P9889, P9757 and P9074) grown in four different fertilization treatments were studied. The additive main effects and multiplicative interaction (AMMI) models were used to estimate the GEI. The results revealed that genotype and environmental effects, such as the GEI effect, significantly influenced yield, as well as revealing that maize genotypes responded differently to different conditions and fertilization measures. An...
INTRODUCTION: The less productive soils present one of the major problems in wheat production ove... more INTRODUCTION: The less productive soils present one of the major problems in wheat production over the world. Considering the importance of wheat production, it is necessary to better utilize the less productive soils and to select wheat varieties that can be successfully grown on such soils. Since that the grain yield of wheat is complex and variable trait that depends on numerous yield components and environmental factors, individual characteristics of the plant, such as the number of grains per spike, grain weight per spike, plant height and harvest index, are important in the formation of grain yield, especially in the stressful conditions of wheat cultivation. The investigation of variability and assessment the interrelationship of yield components could improve cultivar creation, selection and ability of a wheat cultivar to produce high and stable yield over a wide range of environments. OBJECTIVES: The objective of this study was to estimate the mean values the yield componen...
Grain yield of wheat is a complex trait made up of the interaction between different yield compon... more Grain yield of wheat is a complex trait made up of the interaction between different yield components and environmental effects. Due to the importance of yield traits, breeders need efficient and precise methods to measure differences among genotypes. Since that spectral proximal sensing is promising for high-throughput non-destructivephenotyping, recent findings suggest that multispectral proximal sensors can be used in place of labour intensive methods to estimate specific plant traits. The objective of this study was to evaluate the impact of different spectral reflectance indices (SRIs) in assessing stem height and spike length in 4 winter wheat genotypes grown in different conditions of seed priming. Seeds of each winter wheat genotypes were primed with different concentrations of zinc oxide nanoparticles (ZnO NPs) and after sown in soil pots. Spectral reflectance from the plants at different growth stages during vegetation was measured using an active multispectral, optical se...
With an increasing interest of the agricultural community in precision agriculture, this paper ai... more With an increasing interest of the agricultural community in precision agriculture, this paper aims to compare two novel sensing approaches for crop monitoring. The recently developed multispectral proximal sensor named Plant-O-Meter and Sentinel-2 satellite, which carries a multispectral optical instrument, are two sensors suitable for agricultural applications. Each of them has pros and cons regarding spatial, spectral and temporal resolutions and their complementary use will surely bring added value compared to information retrieved by a single sensor. In order to correctly address the problem of data fusion, compatibility studies between the two sensors are necessary. In this study, a maize field was sensed on several dates in 2018 growing season using both sensors. Numerous vegetation indices based on different spectral channel combinations were calculated and the results were compared using linear regression analysis. First results showed good positive correlations between the...
The challenges of the global food supply and environment conservation require ongoing scientific ... more The challenges of the global food supply and environment conservation require ongoing scientific observations of soil-to-plant and plant-to-environment interactions with the aim of improving agriculture resource management. This study included observations of winter wheat yield and biomass of four varieties over three consecutive growing seasons and four site-year cases to assess the effects of nitrogen (N) fertilization rate and time of application on grain yield and biomass. For different wheat varieties, the full factorial design was performed, where factorial combinations of year, location, fall and spring N applications were laid out in a randomized complete block design. The N rate significantly influenced grain yield and biomass production efficiency. The time of N application had a highly significant effect on grain yield, biomass and NUE traits. The N rate of 120 kg ha−1 was recognized as a breakpoint over which the grain yield and biomass showed a downtrend. N application ...
Active proximal sensing has been increasingly used to provide information about canopy properties... more Active proximal sensing has been increasingly used to provide information about canopy properties in a large range of crops. In this study a low cost, active multispectral optical device named Plant-OMeter (POM) was tested in real conditions at two experimental fields comparing it with the GreenSeeker handheld device. Treatments included five nitrogen (N) fertilisation rates applied during sowing. Maize was scanned between V5 to V8 growth stages. The results showed that measuring with the POM sensor within this growth stage window can provide good estimation of end-of-season yield, comparable to the GreenSeeker. This indicates that Plant-O-Meter exhibits strong potential for accurate plant canopy measurements and for real time variable rate fertilisation applications in maize
COST final meeting March 20-21 2018 KU Leuven, Abstract book, 2018
Different morpho-physiological traits have been proposed as key traits associated with grain yiel... more Different morpho-physiological traits have been proposed as key traits associated with grain yield potential of wheat. Considering that methods for assessing morpho-physiological traits are laborious and expensive, phenotyping via remote and proximal sensing techniques could contribute to improvement in wheat breeding programs. The NDVI (Normalized Difference Vegetation Index) represent one of the most promising tools for application in field phenotyping with potential to provide complex information on different morpho-physiological traits of wheat. The objective of this study was to analyze the use of different NDVIs derived from field reflectance measurements to estimate grain yield, plant height, aboveground biomass, total leaf chlorophyll and nitrogen content for the contrasting wheat cultivars. The NDVI was measured using an active hand-held sensor GreenSeeker (NTech Industries Inc., Ukiah, California, USA) and hyperspectral camera (Ximea Corp., Lakewood, CO USA) at four growth stages of wheat: full flowering, medium milk, early dough and fully ripe stage of wheat. Based on two-band combinations between red (600 - 700 nm) or far-red (700 - 750 nm) and near-infrared (756 - 955 nm) regions, 66 different hyperspectral NDVIs were calculated. Significant and positive correlations (higher than 0.6 and significant at p < 0.05) were found between the specific hyperspectral NDVIs and morpho-physiological traits, but varied with growing stages and genotypes. Furthermore, hyperspectral NDVIs provided an overall better estimate than GreenSeeker sensor since they provided additional spectral band combinations for NDVI, exclusively sensitive to targeted morpho-physiological traits of wheat. This study give promising results which can be used as a basis for development and improvement sensing devices based on wider range of wavelengths which could lead to achievement real-time information in monitoring key traits associated with grain yield potential of wheat.
Morpho-physiological traits of wheat such as a grain weight per plant, total leaf chlorophyll con... more Morpho-physiological traits of wheat such as a grain weight per plant, total leaf chlorophyll content, carotenoids, relative dry matter and nitrogen content are important traits for the growth of winter wheat genotypes. However, methods to estimate these traits are laborious and destructive. Spectral reflectance indices based on combination of visible and near-infrared wavelengths such as NDVI (Normalized Difference Vegetation Index), represent one of the most promising tools for application in field phenotyping with potential to provide complex information on different morpho-physiological traits of wheat. The aim of this study was to assess the utility of NDVI measurements of wheat canopy in identification of a specific growth stage in which remotely sensed data show the largest correlation with final grain yield, grain weight per plant, total leaf chlorophyll and carotenoid content, relative dry matter and nitrogen content in 29 winter wheat (Triticum aestivum L.) genotypes. The NDVI was measured using an active hand-held sensor GreenSeeker (NTech Industries Inc., Ukiah, California, USA) and hyperspectral camera (Ximea Corp., Lakewood, CO USA) at four growth stages of wheat: full flowering (BBCH 65), medium milk (BBCH 75), early dough (BBCH 83) and fully ripe stage (BBCH 89). Overall 66 different hyperspectral NDVIs were calculated from two-band combinations between red (600-700 nm) or far red (700-740 nm) and near-infrared (756-946 nm) regions. Pearson’s correlation coefficient was used to explore the relationship among examined traits and NDVI measured at different growth stages of wheat. Obtained results indicate that most of observed NDVI indices showed negative correlation with the relative dry matter content at all observed growth stages. Significant positive correlations (higher than 0.6 and significant at P < 0.05) were found between the specific hyperspectral NDVIs measured at medium milk stage and grain weight per plant, total leaf chlorophyll, carotenoid and nitrogen content, as well as with final grain yield of wheat. The strong positive relationship between NDVI and examined traits found at medium milk stage suggests that this stage is the most appropriate for estimation of these traits of winter wheat in semiarid or similar wheat growing conditions. The overall results indicate that spectral reflectance tools based on combined visible and near-infrared wavelengths, such as NDVI, could be successfully applied to assess morpho-physiological traits of a large number of winter wheat genotypes in a rapid and non-destructive manner. Furthermore, although neither device appeared to have a sizeable advantage over the other, NDVI acquired by hyperspectral camera does appear to be more indicative than NDVI acquired by GreenSeeker sensor, suggesting that alternative spectral combinations can be used in assessing targeted traits of winter wheat genotypes.
Spectral reflectance indices as a phenotyping tool for assessing morpho-physiological traits of winter wheat (Triticum aestivum L.), 2017
Spectral reflectance indices as a phenotyping tool for assessing morpho-physiological traits of w... more Spectral reflectance indices as a phenotyping tool for assessing morpho-physiological traits of winter wheat (Triticum aestivum L.)
Nataša Ljubičić1, Oskar Marko1, Ivana Maksimović2, Marko Panić1, Marina Putnik-Delić2, Marko Kostić2, Milena Daničić2, Sanja Brdar1, Radivoje Jevtić3 and Vladimir Crnojević1
1BioSense Institute, Dr Zorana Đinđića 1, 21 000 Novi Sad, Serbia 2 University of Novi Sad, Faculty of Agriculture, 21 000 Novi Sad, Serbia 3 Institute of Field and Vegetable Crops, 21 000 Novi Sad, Serbia
Morpho-physiological traits of wheat such as a grain weight per plant, total leaf chlorophyll content, carotenoids, relative dry matter and nitrogen content are important traits for the growth of winter wheat genotypes. However, methods to estimate these traits are laborious and destructive. Spectral reflectance indices based on combination of visible and near-infrared wavelengths such as NDVI (Normalized Difference Vegetation Index), represent one of the most promising tools for application in field phenotyping with potential to provide complex information on different morpho-physiological traits of wheat. The aim of this study was to assess the utility of NDVI measurements of wheat canopy in identification of a specific growth stage in which remotely sensed data show the largest correlation with final grain yield, grain weight per plant, total leaf chlorophyll and carotenoid content, relative dry matter and nitrogen content in 29 winter wheat (Triticum aestivum L.) genotypes. The NDVI was measured using an active hand-held sensor GreenSeeker (NTech Industries Inc., Ukiah, California, USA) and hyperspectral camera (Ximea Corp., Lakewood, CO USA) at four growth stages of wheat: full flowering (BBCH 65), medium milk (BBCH 75), early dough (BBCH 83) and fully ripe stage (BBCH 89). Overall 66 different hyperspectral NDVIs were calculated from two-band combinations between red (600-700 nm) or far red (700-740 nm) and near-infrared (756-946 nm) regions. Pearson’s correlation coefficient was used to explore the relationship among examined traits and NDVI measured at different growth stages of wheat. Obtained results indicate that most of observed NDVI indices showed negative correlation with the relative dry matter content at all observed growth stages. Significant positive correlations (higher than 0.6 and significant at P < 0.05) were found between the specific hyperspectral NDVIs measured at medium milk stage and grain weight per plant, total leaf chlorophyll, carotenoid and nitrogen content, as well as with final grain yield of wheat. The strong positive relationship between NDVI and examined traits found at medium milk stage suggests that this stage is the most appropriate for estimation of these traits of winter wheat in semiarid or similar wheat growing conditions. The overall results indicate that spectral reflectance tools based on combined visible and near-infrared wavelengths, such as NDVI, could be successfully applied to assess morpho-physiological traits of a large number of winter wheat genotypes in a rapid and non-destructive manner. Furthermore, although neither device appeared to have a sizeable advantage over the other, NDVI acquired by hyperspectral camera does appear to be more indicative than NDVI acquired by GreenSeeker sensor, suggesting that alternative spectral combinations can be used in assessing targeted traits of winter wheat genotypes.
Normalized Difference Vegetation Index (NDVI) as a tool for wheat yield traits estimation
Nataša... more Normalized Difference Vegetation Index (NDVI) as a tool for wheat yield traits estimation
Nataša Ljubičić1, Radivoje Jevtić2, Sanja Brdar1, Oskar Marko1, Marko Panić1, Marko Kostić3, Milivoje Knežević1, Vladan Minić1, Predrag Lugonja1 and Vladimir Crnojević1
1BioSense Institute, Dr. Zorana Đinđića 1, 21 000 Novi Sad, Serbia 2Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21 000 Novi Sad, Serbia 3Faculty of Agriculture, University of Novi Sad, Sq. D. Obradovića 8, 21 000 Novi Sad, Serbia
Field-based high-throughput plant phenotyping using spectral reflectance measurements possess the great potential to improve genetic gains for different yield traits of wheat. The objective of this study was to estimate the potential of using NDVI (Normalized Difference Vegetation Index) measurements of wheat crop canopy in identification of a specific growth stage in which remotely sensed data shows the highest correlation with aboveground biomass, grain weight per spike and final grain yield of 28 winter wheat genotypes. The NDVI was determined using an integrated proximal sensor Green-Seeker (NTech Industries Inc., Ukiah, California, USA) and hyperspectral camera (Ximea Corp., Lakewood, CO USA) at five development stages of wheat: full flowering (BBCH 65), medium milk (BBCH 75), late milk (BBCH 77), early dough (BBCH 83) and fully ripe stage of wheat (BBCH 89). Overall 26 hyperspectral NDVI were calculated from two-band combinations between red (600-700 nm) or far red (700-740 nm) and near-infrared (756-946 nm) regions. The relationships between examined traits and NDVI readings at different development stages were determined using Pearson correlation coefficient. Obtained results indicated that NDVI values depend upon the particular phenology stage. Wheat genotypes differed in the decline of NDVI from full flowering to fully ripe stage of wheat. While high yielding genotypes maintained high NDVI values, lower yielding genotypes expressed steep descent. Highly significant correlations (higher than 0.7 and significant at p < 0.05) were found between the specific hyperspectral NDVI indices at medium milk stage and all examined yield traits of wheat. The strong positive relationship between NDVI and examined traits found at medium milk stage of wheat implies that this stage is optimal for wheat traits assessment in semiarid conditions or similar wheat growing environments. Results also indicate that significant differences between NDVI values obtained through Green-Seeker sensor and hyperspectral camera at the most comparable spectral band combination were not observed. This suggests that both can be used for the assessment of aboveground biomass, grain weight per spike and final grain yield of a large number of wheat genotypes in rapid and non-destructive manner. Additionally, our study reveals that richer information from hyperspectral camera provides alternative spectral combinations that can be utilized for more precise phenotyping.
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Papers by Natasa Ljubicic
Nataša Ljubičić1, Oskar Marko1, Ivana Maksimović2, Marko Panić1, Marina Putnik-Delić2, Marko Kostić2, Milena Daničić2, Sanja Brdar1, Radivoje Jevtić3 and Vladimir Crnojević1
1BioSense Institute, Dr Zorana Đinđića 1, 21 000 Novi Sad, Serbia
2 University of Novi Sad, Faculty of Agriculture, 21 000 Novi Sad, Serbia
3 Institute of Field and Vegetable Crops, 21 000 Novi Sad, Serbia
Morpho-physiological traits of wheat such as a grain weight per plant, total leaf chlorophyll content, carotenoids, relative dry matter and nitrogen content are important traits for the growth of winter wheat genotypes. However, methods to estimate these traits are laborious and destructive. Spectral reflectance indices based on combination of visible and near-infrared wavelengths such as NDVI (Normalized Difference Vegetation Index), represent one of the most promising tools for application in field phenotyping with potential to provide complex information on different morpho-physiological traits of wheat. The aim of this study was to assess the utility of NDVI measurements of wheat canopy in identification of a specific growth stage in which remotely sensed data show the largest correlation with final grain yield, grain weight per plant, total leaf chlorophyll and carotenoid content, relative dry matter and nitrogen content in 29 winter wheat (Triticum aestivum L.) genotypes. The NDVI was measured using an active hand-held sensor GreenSeeker (NTech Industries Inc., Ukiah, California, USA) and hyperspectral camera (Ximea Corp., Lakewood, CO USA) at four growth stages of wheat: full flowering (BBCH 65), medium milk (BBCH 75), early dough (BBCH 83) and fully ripe stage (BBCH 89). Overall 66 different hyperspectral NDVIs were calculated from two-band combinations between red (600-700 nm) or far red (700-740 nm) and near-infrared (756-946 nm) regions. Pearson’s correlation coefficient was used to explore the relationship among examined traits and NDVI measured at different growth stages of wheat. Obtained results indicate that most of observed NDVI indices showed negative correlation with the relative dry matter content at all observed growth stages. Significant positive correlations (higher than 0.6 and significant at P < 0.05) were found between the specific hyperspectral NDVIs measured at medium milk stage and grain weight per plant, total leaf chlorophyll, carotenoid and nitrogen content, as well as with final grain yield of wheat. The strong positive relationship between NDVI and examined traits found at medium milk stage suggests that this stage is the most appropriate for estimation of these traits of winter wheat in semiarid or similar wheat growing conditions. The overall results indicate that spectral reflectance tools based on combined visible and near-infrared wavelengths, such as NDVI, could be successfully applied to assess morpho-physiological traits of a large number of winter wheat genotypes in a rapid and non-destructive manner. Furthermore, although neither device appeared to have a sizeable advantage over the other, NDVI acquired by hyperspectral camera does appear to be more indicative than NDVI acquired by GreenSeeker sensor, suggesting that alternative spectral combinations can be used in assessing targeted traits of winter wheat genotypes.
Nataša Ljubičić1, Radivoje Jevtić2, Sanja Brdar1, Oskar Marko1, Marko Panić1, Marko Kostić3, Milivoje Knežević1, Vladan Minić1, Predrag Lugonja1 and Vladimir Crnojević1
1BioSense Institute, Dr. Zorana Đinđića 1, 21 000 Novi Sad, Serbia
2Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21 000 Novi Sad, Serbia
3Faculty of Agriculture, University of Novi Sad, Sq. D. Obradovića 8, 21 000 Novi Sad, Serbia
Field-based high-throughput plant phenotyping using spectral reflectance measurements possess the great potential to improve genetic gains for different yield traits of wheat. The objective of this study was to estimate the potential of using NDVI (Normalized Difference Vegetation Index) measurements of wheat crop canopy in identification of a specific growth stage in which remotely sensed data shows the highest correlation with aboveground biomass, grain weight per spike and final grain yield of 28 winter wheat genotypes. The NDVI was determined using an integrated proximal sensor Green-Seeker (NTech Industries Inc., Ukiah, California, USA) and hyperspectral camera (Ximea Corp., Lakewood, CO USA) at five development stages of wheat: full flowering (BBCH 65), medium milk (BBCH 75), late milk (BBCH 77), early dough (BBCH 83) and fully ripe stage of wheat (BBCH 89). Overall 26 hyperspectral NDVI were calculated from two-band combinations between red (600-700 nm) or far red (700-740 nm) and near-infrared (756-946 nm) regions. The relationships between examined traits and NDVI readings at different development stages were determined using Pearson correlation coefficient. Obtained results indicated that NDVI values depend upon the particular phenology stage. Wheat genotypes differed in the decline of NDVI from full flowering to fully ripe stage of wheat. While high yielding genotypes maintained high NDVI values, lower yielding genotypes expressed steep descent. Highly significant correlations (higher than 0.7 and significant at p < 0.05) were found between the specific hyperspectral NDVI indices at medium milk stage and all examined yield traits of wheat. The strong positive relationship between NDVI and examined traits found at medium milk stage of wheat implies that this stage is optimal for wheat traits assessment in semiarid conditions or similar wheat growing environments. Results also indicate that significant differences between NDVI values obtained through Green-Seeker sensor and hyperspectral camera at the most comparable spectral band combination were not observed. This suggests that both can be used for the assessment of aboveground biomass, grain weight per spike and final grain yield of a large number of wheat genotypes in rapid and non-destructive manner. Additionally, our study reveals that richer information from hyperspectral camera provides alternative spectral combinations that can be utilized for more precise phenotyping.