R. Dhandapani

Indian Council of Agricultural Research

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Sudhir Kumar

Indian Agricultural Research Institute

Viswanathan Chinnusamy

Indian Agricultural Research Institute

Rabi Narayan Sahoo

Indian Council of Agricultural Research

Shalini Gakhar

Indian Agricultural Research Institute

Mahesh Kumar

Velammal Medical College Hospital and Research Institute

R. G. Rejith

Indian Space Research Organisation

S. Natarajan

Indian Council of Agricultural Research

H. P. Vijayakumar

Indian Agricultural Research Institute

Gopi Somasundaram

Ramakrishna Mission Vidyalaya

Bappa Das

Central Coastal Agricultural Research Institute

Cooperative Institutions

Indian Agricultural Research Institute

Indian Council of Agricultural Research

Tamil Nadu Agricultural University

National Bureau of Plant Genetic Resources

Periyar University

Indian Space Research Organisation

Punjab Agricultural University

Govind Ballabh Pant University of Agriculture and Technology

Banaras Hindu University

Indian Agricultural Statistics Research Institute

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Understanding the physiological, genetic and molecular basis of nitrogen deficiency tolerance and their application in rice improvement

ORYZA- An International Journal on Rice (2023)

A Harika R. Dhandapani Sudhir Kumar S. Lekshmy T. Vinutha

Nitrogen (N) is a major nutrient required for growth and yield of rice plants. Several factors including plant, edapic and climate conditions influence the criticle yield response curve of the plants. Apart from breeding for N responsive rice varieties, excessive use of nitrogenous fertilizers have become a general farmers practice to boost rice productivity under intensive cropping system. Now, it is imperative to orient the crop improvement programme for sustainable crop production strategy as well as to achieve the evergreen revolution through improving nitrogen use efficiency (NUE) under global climate change condition. To develop N-efficient rice varieties under crop breeding programs, it is crucial to comprehend the physiological, genetic and molecular features associated with tolerance to nitrogen deprivation. It has always been challenging for a rice breeders to develop rice varieties with high nitrogen use efficiency (NUE), as it is highly complex physiological trait involving several component traits and its dynamic interaction with environemental factor. NUE is a polygenic traits controlled by number of quantitative trait loci's at genomic level. Till date, researchers targeted component traits for increasing NUE such as, nitrogen uptake/absorption, transport from root to shoot, assimilation, utilisation, remobilisation, reasssssmilation and partitioning /redistribution. Here, we described a short summary of the physiological, genetic and molecular underpinnings of nitrogen deficit tolerance and how these prior art information can be used for improving NUE in rice. Insight from our discussions may facilitate the breeders to improve the NUE of rice plants in future.

Trait

Molecular breeding

10.35709/ory.2023.60.0.3

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Trace metals and mineral contents of some green algal seaweeds from Vadakadu (Rameswaram) coastal regions, Tamil Nadu, India

Journal of Pharmacognosy and Phytochemistry (2018)

N Lalitha R. Dhandapani

The present study focused on the trace metal and mineral composition analysis of fiver green algal seaweeds such as Caulerpa racemosa, Caulerpa sertularioides, Ulva reticulate, Ulva lactuca and Codium tomentosum were collected from Vadakadu (Rameswaram) coastal regions, Tamilnadu, India. Among this group of seaweeds, Caulerpa sertularioides showed the maximum contents of mineral elements such as chromium, copper, and magnesium and Ulva lactuca observed the minimum level of mineral content such as cobalt, iron, magnesium, manganese, nickel, lead and zinc.

Ulva lactuca

Ulvophyceae

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Next generation phenotyping for developing climate resilient rice varieties

ORYZA- An International Journal on Rice (2019)

Rabi Narayan Sahoo Viswanathan Chinnusamy Gopal Krishna Bappa Das Swati Goel

Present paper deals with different components of next generation phenomics for characterizing rice genotypes for water deficit stress. Major sensors used in the study were non-imaging hyperspectal remote sensing, thermal imaging at ground platform and RGB and multispectral imaging sensors from drone platform. Different spectral indices were evaluated along with new proposed index and different multivariate models were studied for non-invasive estimation of relative water content (RWC) and sugar content in rice plant using spectral reflectance data collected in spectral range 350 to 2500 nm. Spectral data were further used for spectral discrimination of rice genotypes. Crop water stress index derived from thermal images acquired for rice genotypes could well characterize the drought resistant and sensitive genotypes. Initial study on field phenotyping through drone remote sensing using multispectral and RGB sensor was also explored to capture differential response of genotypes, trait and heat map mapping. All developed protocols as reliable alternative to conventional methods are fast, economic and non-invasive and in use in plant phenomics centre for high throughput plant phenotyhping for water deficit stress studies.

Phenomics

RGB color model

10.35709/ory.2019.56.s.2

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Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring

Geocarto International (2019)

Gopal Krishna Rabi Narayan Sahoo Prafull Singh Himesh Patra Vaishangi Bajpai

Water deficit in crops induces a stress that may ultimately result in low production. Identification of response of genotypes towards water deficit stress is very crucial for plant phenotyping. The study was carried out with the objective to identify the response of different rice genotypes to water deficit stress. Ten rice genotypes were grown each under water deficit stress and well watered or nonstress conditions. Thermal images coupled with visible images were recorded to quantify the stress and response of genotypes towards stress, and relative water content (RWC) synchronized with image acquisition was also measured in the lab for rice leaves. Synced with thermal imaging, Canopy reflectance spectra from same genotype fields were also recorded. For quantification of water deficit stress, Crop Water Stress Index (CWSI) was computed and its mode values were extracted from processed thermal imageries. It was ascertained from observations that APO and Pusa Sugandha-5 genotypes exhibited the highest resistance to the water deficit stress or drought whereas CR-143, MTU-1010, and Pusa Basmati-1 genotypes ascertained the highest sensitiveness to the drought. The study reveals that there is an effectual relationship (R2 = 0.63) between RWC and CWSI. The relationship between canopy reflectance spectra and CWSI was also established through partial least square regression technique. A very efficient relationship (calibration R2 = 0.94 and cross-validation R2 = 0.71) was ascertained and 10 most optimal wavebands related to water deficit stress were evoked from hyperspectral data resampled at 5 nm wavelength gap. The identified ten most optimum wavebands can contribute in the quick detection of water deficit stress in crops. This study positively contributes towards the identification of drought tolerant and drought resistant genotypes of rice and may provide valuable input for the development of drought-tolerant rice genotypes in future.

Water Stress

10.1080/10106049.2019.1618922

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Impact of salinity on the growth and productivity of selected mustard (Brasicca juncea L.) varieties.

International Journal of Plant Sciences Muzaffarnagar (2009)

R. Dhandapani S. K. S. Parihar

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Extraction of sulfated polysaccharide from marine macro- alga Gracilaria edulis and its biological applications

Applied Biological Research (2023)

V. Hemalatha Silambarasan Tamil Selvan R. Dhandapani

Gracilaria

10.5958/0974-4517.2023.00021.6

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Estimation of wheat biophysical variables through UAV hyperspectral remote sensing using machine learning and radiative transfer models

Computers and Electronics in Agriculture (2024)

Rabi Narayan Sahoo R. G. Rejith Shalini Gakhar Jochem Verrelst Rajeev Ranjan

10.1016/j.compag.2024.108942

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Correlation among physiological and histological changes in soybean seeds during storage

Journal of Environmental Biology (2019)

H. P. Vijayakumar A. G. Vijaya Kumar P. Srimathi Gopi Somasundaram Sant Prasad

10.22438/jeb/40/2/mrn-753

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High-Throughput Phenomics of Crops for Water and Nitrogen Stress

Rabi Narayan Sahoo Viswanathan Chinnusamy Mahesh Kumar Swati Bhugra Sourabh Karwa

While both water and nitrogen (N) are necessary for crop output and quality, excessive N application increases production costs and environmental degradation. Recent years have seen the development of NUE and WUE assessment tools, which have shown value. This chapter discusses the properties of next-generation phenomics that are critical for recognising rice genotypes during periods of water scarcity. In addition to the newly proposed one, the experiment featured non-imaging hyperspectral remote sensing, thermal imaging, and colour and multispectral imaging sensors from the ground and aerial platforms. Numerous multivariate models for the non-invasive evaluation of rice plants' relative water content (RWC) and sugar content were examined using spectral reflectance data gathered in the 350–2500 nm spectral region. Differentiating rice genotypes was accomplished using spectral data. A crop water stress score developed from thermal imaging of selected rice genotypes may be used to identify rice with high drought resistance and low drought sensitivity. The researchers used multispectral and RGB sensors mounted on a drone for field remote sensing and heat map mapping to record the distinct responses of various genotypes and characteristics. The procedures established are rapid, low-cost, and non-invasive, providing a viable alternative to traditional approaches. These techniques are now being used to do high-throughput plant phenotyping in water scarcity and nutrient deficiency conditions.

Phenomics

10.1007/978-981-19-7498-4_13

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Next generation phenotyping for developing climate resilient rice varieties

ORYZA- An International Journal on Rice (2019)

Rabi Narayan Sahoo Viswanathan Chinnusamy Gopal Krishna Bappa Das Swati Goel

Phenomics

RGB color model

10.35709/ory.2019.56.spl.2

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Citations (1)