Pedogenic characteristics of soil in Melur block, Madurai district, Tamil Nadu in India: A case study

Soil is an important source of human life and agricultural production. Studying on the pedon and its site characteristics pave the way for understanding the nature of soils and its utility. A study on pedological characterization of soils in Melur block, Madurai District (Tamil Nadu), was carried out during 2019-2020 using grid sampling with village map/cadastral maps. Soil mapping unit-based soil samples were collected in Chunampoor, Thuvarangulam, Poonjuthi and Veppapadupu and pedons were characterized as per the standard procedure. The results showed that soils were moderately deep to very deep in nature, ranging from 2.5 YR  3/6 to 10YR 4/6. The soil texture varied from sandy clay loam to sandy clay with weak to moderate sub-angular blocky structure. The consistency of soil varied from slightly hard to very hard when dry, very friable to firm when moist, slightly sticky to very sticky and slightly plastic to very plastic in wet condition. The crops viz., paddy, sugarcane, banana, groundnut and vegetables were very suitable for such type of soil of the Madurai district

Assessing spatial variability of soil and drawing location-specific management zones for coastal saline soils in Ramanathapuram District, Tamil Nadu

The production of crops in saline and alkali-degraded areas is difficult due to the heterogeneous and spatial variation of soil fertility.  First, their spatial variability was analyzed and maps of the spatial distribution were created using Geostatistical techniques.  The fuzzy k-mean clustering analysis was then used to define Management zones in the coastal saline soils of Ramanathapuram district in Tamil Nadu.  One hundred and fifty geo-referenced soil samples  (30 cm depth) were taken and analyzed for pH, electrical conductivity (ECe) in the saturated paste extract (USSL method), organic carbon (OC) (Walkley-Black chromic acid wet oxidation method), calcium carbonate (CaCO3) (Rapid titration method) and available phosphorus and extractable micronutrients (Multinutrients extraction method), revealing significant variation in soil characteristics throughout the coastal saline soils of Ramanathapuram district.  The most significant factors, which together accounted for four principal components and 69% of the overall variability, were pH, electrical conductivity (ECe), calcium Carbonate and available zinc.  According to Geostatistical analysis, the Exponential (pH, OC (organic carbon), P, Fe, Mn and Zn) and Stable (ECe) was the best fit semivariogram ordinary kriging model with weak to moderate spatial dependence.  Fuzzy k-mean clustering was also used to identify zone 1, zone 2 and zone 3.  For every soil property, there was a significant difference between MZ1(zone 1), MZ2(zone 2) and MZ3(zone 3).  These results also showed that cluster analysis gave farmers a chance to use location-specific nutrient management strategies by minimizing variability within the zone. The management zones can decrease agricultural inputs and environmental pollutants while increasing crop productivity.

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Rice Crop Monitoring and Yield Estimation Through Cosmo Skymed and TerraSAR-X: A SAR-Based Experience in India

Rice is the most important cereal crop governing food security in Asia. Reliable and regular information on the area under rice production is the basis of policy decisions related to imports, exports and prices which directly affect food security. Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems. High resolution (3m) Synthetic Aperture Radar (SAR) imageries were used to map and monitor rice growing areas in selected three sites in TamilNadu, India to determine rice cropping extent, track rice growth and estimate yields. A simple, robust, rule-based classification for mapping rice area with multi-temporal, X-band, HH polarized SAR imagery from COSMO Skymed and TerraSAR X and site specific parameters were used. The robustness of the approach is demonstrated on a very large dataset involving 30 images across 3 footprints obtained during 2013-14. A total of 318 in-season site visits were conducted across 60 monitoring locations for rice classification and 432 field observations were made for accuracy assessment. Rice area and Start of Season (SoS) maps were generated with classification accuracies ranging from 87- 92 per cent. Using ORYZA2000, a weather driven process based crop growth simulation model; yield estimates were made with the inclusion of rice crop parameters derived from the remote sensing products viz., seasonal rice area, SoS and backscatter time series. Yield Simulation accuracy levels of 87 per cent at district level and 85- 96 per cent at block level demonstrated the suitability of remote sensing products for policy decisions ensuring food security and reducing vulnerability of farmers in India

Towards an Operational SAR-Based Rice Monitoring System in Asia: Examples from 13 Demonstration Sites across Asia in the RIICE Project

Rice is the most important food security crop in Asia. Information on its seasonal extent forms part of the national accounting of many Asian countries. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland rice, especially in tropical and subtropical regions, where pervasive cloud cover in the rainy seasons precludes the use of optical imagery. Here, we present a simple, robust, rule-based classification for mapping rice area with regularly acquired, multi-temporal, X-band, HH-polarized SAR imagery and site-specific parameters for classification. The rules for rice detection are based on the well-studied temporal signature of rice from SAR backscatter and its relationship with crop stages. We also present a procedure for estimating the parameters based on “temporal feature descriptors” that concisely characterize the key information in the rice signatures in monitored field locations within each site. We demonstrate the robustness of the approach on a very large dataset. A total of 127 images across 13 footprints in six countries in Asia were obtained between October 2012, and April 2014, covering 4.78 m ha. More than 1900 in-season site visits were conducted across 228 monitoring locations in the footprints for classification purposes, and more than 1300 field observations were made for accuracy assessment. Some 1.6 m ha of rice were mapped with classification accuracies from 85% to 95% based on the parameters that were closely related to the observed temporal feature descriptors derived for each site. The 13 sites capture much of the diversity in water management, crop establishment and maturity in South and Southeast Asia. The study demonstrates the feasibility of rice detection at the national scale using multi-temporal SAR imagery with robust classification methods and parameters that are based on the knowledge of the temporal dynamics of the rice crop. We highlight the need for the development of an open-access library of temporal signatures, further investigation into temporal feature descriptors and better ancillary data to reduce the risk of misclassification with surfaces that have temporal backscatter dynamics similar to those of rice. We conclude with observations on the need to define appropriate SAR acquisition plans to support policies and decisions related to food security