Nutrient requirement and use efficiency of rice (<i>Oryza sativa</i>L.) as influenced by graded levels of customized fertilizer

Basavarajappa, Prakash Nagabovanalli; Shruthi, .; Lingappa, Mallikarjuna; G, Kadalli G.; Mahadevappa, Sujith Goudra

doi:10.1080/01904167.2021.1927081

Cited by 9 publications

(4 citation statements)

References 19 publications

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“…In the case of phosphorus, the highest PFP P was observed at 45 kg P 2 O 5 ha −1 but PFP N was highest at 60 kg N ha −1 . A similar result was found by Basavarajappa et al, 2021, who concluded that PFP for phosphorus decreased progressively as CF levels increased [21]. According to the previous research result, they concluded that N absorption showed a positive impact with P fertilizer application [43].…”

Section: Nutrient-use Efficienciessupporting

confidence: 81%

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Optimizing Nutrient and Energy Efficiency in a Direct-Seeded Rice Production System: A Northwestern Punjab Case Study

Kaur,

Chhina,

Kaur

et al. 2024

Agronomy

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This study was carried out in Amritsar, Punjab, to find out how efficiently nutrients were used and how much energy was employed in direct-seeded rice (DSR) production. In this study, four levels of nitrogen (0, 40, 50, and 60 kg N ha−1) and three levels of phosphorus (0, 37.5, and 45 kg P2O5 ha−1) were tested. In a rice production system, the energy indices of various inputs and outputs were evaluated through the application of energy equivalency. The nutrient-use efficiencies in rice were assessed using different efficiency indices. The maximum grain yields of 38.9 q ha−1 and 36.9 q ha −1 were recorded at 50 kg N ha−1 and 45 kg P2O5 ha−1, respectively. On the other hand, application of nitrogen at 60 kg N ha−1 and phosphorus at 45 kg P2O5 ha−1 resulted in maximum straw yield of 57.1 q ha−1 and 51.1 q ha−1, respectively. In comparison with the control, application of 60 and 50 kg N ha−1 resulted in 161.9% and 151.0% higher grain yield, respectively. On the other hand, with applications of 45 kg P2O5 ha−1 and 37.5 kg P2O5 ha−1, an increase in the grain yield of 17.3 and 28.6%, respectively, over the control was recorded. Moving further towards nutrient-use efficiencies (NUEs), the highest values of partial factor productivity of nitrogen (PFPN), agronomic efficiency of nitrogen (AEN), partial nutrient balance of nitrogen (PNBN), and recovery efficiency of nitrogen (REN) were 89.1, 50.4, 1.78 and 0.72, respectively, which were obtained at 40 kg N ha−1, after which the values started decreasing steadily. In the case of phosphorus, the partial factor productivity (PFPP) of 88.6 was the maximum at 37.5 kg P2O5 ha−1, but partial nutrient balance (PNBP) of 0.36 and recovery efficiency (REP) of 0.08 were highest at 45 kg P2O5 ha−1. The main results revealed that the farmer field had an excessive amount of non-renewable energy inputs. The experimental field depicted greater energy-usage efficiency (EUE) of 4.5, energy productivity (EP) of 0.14, and energy profitability (EP1) of 3.5. These results were primarily ascribed to a significant drop in energy inputs under direct-seeded rice (DSR). In the case of non-renewable energy inputs, fertilizer made the maximum contribution to energy input (47.9%) in the farmer’s field. We conclude that nutrient-use efficiencies and energy-use efficiency were highest at 50 kg N and 45 kg P2O5 ha−1. This recommendation is beneficial for farmers because lower inputs and higher outputs are the main objective of every farmer.

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Section: Nutrient-use Efficienciessupporting

confidence: 81%

“…For many years, scientists have been trying to identify the patterns and mechanisms for controlling the emissions of CH 4 from paddy fields [19,20]. Farmers often apply huge quantities of N fertilizer because of the government's substantial urea fertilizer subsidies, but these quantities are more than what plants require [21].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Nutrient and Energy Efficiency in a Direct-Seeded Rice Production System: A Northwestern Punjab Case Study

Kaur,

Chhina,

Kaur

et al. 2024

Agronomy

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“…Scientists examining the nutritional response of crops frequently choose this as their preferred NUE expression (Addisu, 2022). Similar to AE, it is necessary to measure the concentration of nutrients in crops, which can only be assessed when a nutrient-free plot has been established (Prakash et al, 2021). Similar to AE, when calculated from annual response data, it will often underestimates long-term NUE (Paul, 2014).…”

Section: Apparent Recovery Efficiency (Re)mentioning

confidence: 99%

Improving Primary Nutrients (NPK) Use Efficiency for the Sustainable Production and Productivity of Cereal Crops: A Compressive Review

Andualem,

Wato,

Asfaw

et al. 2024

JASE

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Nutrient Use Efficiency (NUE) is the capacity of certain crops to use the available nutrients for growth, development, and productivity. Enhancing the efficiency of nutrient utilization by cereals is an admirable objective and a major problem for the fertilizer sector and agriculture as a whole. Nutrient use efficiency (NUE) is a critical concept in the evaluation of cereal production systems. Therefore, this study aimed to review methods for improving the efficiency of primary nutrient (NPK) use in cereals (Barley, Rice, wheat, Maize, Sorghum, and Sugarcane) for sustainable production and productivity. Soil, plant water, and fertilizer management can have important impacts on the nutrient-use efficiency of cereals. Nutrient utilization aims to maximize the overall performance of cropping systems by providing the crop with the most inexpensive sustenance possible, while reducing nutrient losses from the field. The NUE takes care of some, but not all, of that performance. Thus, in addition to NUE, total productivity must is one of the aims of system enhancement. The question being posed and, frequently, the spatial or temporal scale of interest for which trustworthy data are available, dictate the most appropriate approach to NUE. For N, P, and K, the partial nutrient balance (the ratio of nutrients removed by crop harvest to fertilizer. Although opinions differ, agronomic nutrient use efficiency is the foundation for both economic and environmental efficiency. Economic and environmental efficiencies arise from increased agricultural efficiency. Therefore, different researchers have investigated ways to improve the nutrient use efficiency of cereals by using mechanisms including optimizing nutrient usage, nano-fertilizer usage, breeding for nutrient use efficiency, and precision farming.

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“…Variety classification plays a pivotal role in assessing yield and optimizing rice-field cultivation. Different rice varieties possess distinctive characteristics, including growth habits [1][2][3], nutrient requirements [4][5][6], disease resistance [7][8][9][10], and tolerance to environmental stressors, such as drought, heat, and pests [11,12]. Identifying the best-performing varieties in each region allows farmers to enhance their yields and increase profitability.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Precise Rice Variety Classification in Tropical Environments Using UAV-Based Multispectral Sensing

Wijayanto,

Junaedi,

Sujaswara

et al. 2023

AgriEngineering

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An efficient assessment of rice varieties in tropical regions is crucial for selecting cultivars suited to unique environmental conditions. This study explores machine learning algorithms that leverage multispectral sensor data from UAVs to evaluate rice varieties. It focuses on three paddy rice types at different ages (six, nine, and twelve weeks after planting), analyzing data from four spectral bands and vegetation indices using various algorithms for classification. The results show that the neural network (NN) algorithm is superior, achieving an area under the curve value of 0.804. The twelfth week post-planting yielded the most accurate results, with green reflectance the dominant predictor, surpassing the traditional vegetation indices. This study demonstrates the rapid and effective classification of rice varieties using UAV-based multispectral sensors and NN algorithms to enhance agricultural practices and global food security.

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Nutrient requirement and use efficiency of rice (Oryza sativaL.) as influenced by graded levels of customized fertilizer

Cited by 9 publications

References 19 publications

Optimizing Nutrient and Energy Efficiency in a Direct-Seeded Rice Production System: A Northwestern Punjab Case Study

Optimizing Nutrient and Energy Efficiency in a Direct-Seeded Rice Production System: A Northwestern Punjab Case Study

Improving Primary Nutrients (NPK) Use Efficiency for the Sustainable Production and Productivity of Cereal Crops: A Compressive Review

Machine Learning for Precise Rice Variety Classification in Tropical Environments Using UAV-Based Multispectral Sensing

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