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V. K. Gupta

Bio: V. K. Gupta is an academic researcher from Indian Agricultural Research Institute. The author has contributed to research in topics: Partial least squares regression & Leaf area index. The author has an hindex of 9, co-authored 21 publications receiving 576 citations. Previous affiliations of V. K. Gupta include Indian Council of Agricultural Research.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the soil and plant water status in wheat under synthetic (transparent and black polyethylene) and organic (rice husk) mulches with limited irrigation and compared with adequate irrigation with no mulch (conventional practices by the farmers).

346 citations

Journal ArticleDOI
15 Sep 2009-Geoderma
TL;DR: In this paper, the spectral reflectance of air-dried and sieved soil samples was measured using a handheld spectroradiometer equipped with a contact probe and transfer functions in the form of multiple linear regression relationships between soil hydraulic properties and different attributes of measured spectral reflectances were developed.

68 citations

Journal ArticleDOI
TL;DR: In this paper, the optimal wavebands were identified through spectral indices, multivariate techniques and neural network technique, and prediction models were developed for predicting water deficit stress levels in rice genotypes.

60 citations

Journal ArticleDOI
TL;DR: This study for the first time identifies the yellow mosaic sensitive band as R688 and R750/R445, which could be utilized to scan satellite data for monitoring YMD affected soybean cropping regions.
Abstract: Remote sensing technique is useful for monitoring large crop area at a single time point, which is otherwise not possible by visual observation alone. Yellow mosaic disease (YMD) is a serious constraint in soybean production in India. However, hardly any basic information is available for monitoring YMD by remote sensing. Present study examines spectral reflectance of soybean leaves due to Mungbean yellow mosaic India virus (MYMIV) infection in order to identify YMD sensitive spectral ratio or reflectance. Spectral reflectance measurement indicated significant (p < 0.001) change in reflectance in the infected soybean canopy as compared to the healthy one. In the infected canopy, reflectance increased in visible region and decreased in near infra-red region of spectrum. Reflectance sensitivity analysis indicated wavelength ~642, ~686 and ~750 nm were sensitive to YMD infection. Whereas, in yellow leaves induced due to nitrogen deficiency, the sensitive wavelength was ~589 nm. Due to viral infection, a shift occurred in red and infra-red slope (called red edge) on the left in comparison to healthy one. Red edge shift was a good indicator to discriminate yellow mosaic as chlorophyll gets degraded due to MYMIV infection. Correlation of reflectance at 688 nm (R688) and spectral reflectance ratio at 750 and 445 nm (R750/R445) with the weighted mosaic index indicated that detection of yellow mosaic is possible based on these sensitive bands. Our study for the first time identifies the yellow mosaic sensitive band as R688 and R750/R445, which could be utilized to scan satellite data for monitoring YMD affected soybean cropping regions.

47 citations

Journal ArticleDOI
TL;DR: Results indicated that VNIR and SWIR spectroscopy combined with multivariate calibration can be used as a reliable alternative to conventional methods for measurement of sucrose, reducing sugars and total sugars of rice under water-deficit stress as this technique is fast, economic, and noninvasive.

47 citations


Cited by
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Journal ArticleDOI
TL;DR: Key challenges in modeling soil processes are identified, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes.
Abstract: The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

542 citations

Book ChapterDOI
TL;DR: In this paper, the authors examined the scientific basis of a ridge-furrow mulching system (RF system) for increasing PUE, and summarized the effects of this system on crop performance, microclimates, soil attributes, and environmental sustainability.
Abstract: Increasing food demands by a growing human population require substantial increases in crop productivity. In rain-fed arid and semiarid areas where the water supply is limited, an increase in the precipitation use efficiency (PUE) is the key to reach this goal. This chapter examines the scientific basis of a ridge-furrow mulching system (RF system) for increasing PUE, and summarizes the effects of this system on crop performance, microclimates, soil attributes, and environmental sustainability. Studies have shown that using crop straw, plastic film, or gravel–sand materials to mulch the soil surface significantly reduces the evaporation of soil moisture, increases water availability to crop plants, and decreases soil erosion caused by wind and water. Plastic mulching increases topsoil temperature during cool spring, promoting plant growth; during hot summer, straw mulching can moderate soil temperature, preventing the topsoil from reaching temperatures that inhibit plant growth. Ridge furrows with plastic mulching on the ridges and crop straw covering the furrows channel water to the furrows, and enhance soil water infiltration and water availability to the crop. Microclimates under mulched ridges and furrows favor soil microbial activity, increase soil biodiversity, and improve environmental benefits. The effectiveness of ridge-furrow systems is reflected in increased crop yields (20–180%) compared with that of the conventional-flat planting. Although more research is required to document physiochemical strengths, technique details and potential drawbacks, and more importantly to define long-term sustainability, we strongly suggest that RF systems are an innovative approach for increasing crop water availability, improving soil productivity, and enhancing food security for arid and semiarid rain-fed areas.

469 citations

Journal ArticleDOI
TL;DR: In this paper, the authors reviewed 189 published research papers, which described the effects of various mulching materials and methods on soil and environment that influence crop productivity, and they described the extent of influence of different mulch materials and method on the hydrothermal environment of soils.
Abstract: The global temperature has been increasing over the years due to climate change that, directly or indirectly, affects water and energy consumptions in the agriculture sector. The application of mulching practices reduces soil evaporation, conserves soil moisture, suppresses weed growth, controls soil structure and temperature, influences soil micro-organisms, and is aesthetically pleasing. This study has reviewed 189 published research papers, which described the effects of various mulching materials and methods on soil and environment that influence crop productivity. This paper describes the extent of influence of different mulching materials and methods on the hydrothermal environment of soils. It is imperative to know the processes that control soil environments under various mulching conditions and the effects of mulching materials on crop yield, productivity and water use efficiency. These issues of mulching are the prime concerns of this review study. Plastic mulching materials have a greater importance than the organic ones to control soil environment and increase crop yield. But, the organic mulching materials are inexpensive and environment friendly. The selection of an appropriate mulching material is, however, guided by crop type, crop management practices and climatic conditions. Future research is needed on the effects of low-cost biodegradable mulching materials on microclimate modifications, soil biota, soil fertility, crop growth and crop yields.

369 citations

Journal ArticleDOI
TL;DR: In this paper, a rice grain yield was predicted with single stage vegetation indices (VIs) and multi-temporal VIs derived from the multispectral (MS) and digital images.
Abstract: Timely and non-destructive assessment of crop yield is an essential part of agricultural remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a novel approach for RS, and makes it possible to acquire high spatio-temporal resolution imagery on a regional scale. In this study, the rice grain yield was predicted with single stage vegetation indices (VIs) and multi-temporal VIs derived from the multispectral (MS) and digital images. The results showed that the booting stage was identified as the optimal stage for grain yield prediction with VIs at a single stage for both digital image and MS image. And corresponding optimal color index was VARI with R 2 value of 0.71 (Log relationship). While the optimal vegetation index NDVI [800,720] based on MS images showed a linear relationship with the grain yield and gained a higher R 2 value (0.75) than color index did. The multi-temporal VIs showed a higher correlation with grain yield than the single stage VIs did. And the VIs at two random growth stage with the multiple linear regression function [MLR(VI)] performed best. The highest correlation coefficient were 0.76 with MLR(NDVI [800,720] ) at the booting and heading stages (for the MS image) and 0.73 with MLR(VARI) at the jointing and booting stages (for the digital image). In addition, the VIs that showed a high correlation with LAI performed well for yield prediction, and the VIs composed of red edge band (720 nm) and near infrared band (800 nm) were found to be more effective in predicting yield and LAI at high level. In conclusion, this study has demonstrated that both MS and digital sensors mounted on the UAV are reliable platforms for rice growth and grain yield estimation, and determined the best period and optimal VIs for rice grain yield prediction.

353 citations

Journal ArticleDOI
Chuan Liu1, S.L. Jin, Li-Min Zhou1, Yu Jia1, Feng-Min Li1, You-Cai Xiong1, Xiao Gang Li1 
TL;DR: In this article, the effects of mulching time for double furrows and ridges using plastic film on soil water status, grain yield of maize, soil quality, and economic benefits were determined.

305 citations