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A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of a deep learning network model (DLNM). To explore the influence of label image accuracy on the performance of a concrete crack segmentation network model in a semantic segmentation dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening labelling and topological structure widening labelling, respectively, to generate crack label images and construct three sets of crack semantic segmentation datasets with different accuracy. Four semantic segmentation network models (SSNMs), U-Net, High-Resolution Net (HRNet)V2, Pyramid Scene Parsing Network (PSPNet) and DeepLabV3+, were used for learning and training. The results show that the datasets constructed from the crack label images with pix-el-level fine labelling are more conducive to improving the accuracy of the network model for crack image segmentation. The U-Net had the best performance among the four SSNMs. The Mean Intersection over Union (MIoU), Mean Pixel Accuracy (MPA) and Accuracy reached 85.47%, 90.86% and 98.66%, respectively. The average difference between the quantized width of the crack image segmentation obtained by U-Net and the real crack width was 0.734 pixels, the maximum difference was 1.997 pixels, and the minimum difference was 0.141 pixels. Therefore, to improve the segmentation accuracy of crack images, the pixel-level fine labelling strategy and U-Net are the best choices. [ABSTRACT FROM AUTHOR]

The QUEFTS (QUantitative Evaluation of the Fertility of Tropical Soils) model is a valuable tool for developing location-specific management of macronutrients such as N, P, and K to attain higher yields. A review analysis is conducted to understand the applicability of the QUEFTS model in developing site-specific nutrient management (SSNM) for different crops. A total of 33 published articles are available for the QUEFTS model for different crops across the world. The SSNM is available for rice, wheat, maize, potato, tropical tuber crops (cassava, sweet potato, elephant foot yam, taro, and yam), peanut, watermelon, soybean, radish, tea, sweet potato, elephant foot yam, yam, and taro in different countries using the QUEFTS model, and it is discussed in this review. The maximum values of accumulation and dilution of N, P, and K; the balanced nutrient requirements to produce 1000 kg of crop yield; and their internal efficiencies are discussed in this review paper. The review shows that the QUEFTS model parameters derived for rice, wheat, and maize can be directly adapted to different environmental conditions. The data available for potato demand further refinement of the model for its general application irrespective of the agro-climatic conditions. The two sets of data available for cassava are similar and can use the same model parameters for further studies for nutrient management. Single set of data for other crops shows the necessity for more studies to increase their production. The modeled values for different crops presented in this review can further assist the decision-makers in scheduling fertilizer applications for the respective crops, reducing fertilizer and economic losses, and maintaining soil quality. Thus, QUEFTS can be widely used as a simple model to recommend nutrient management practices. However, the QUEFTS model considers only the mean meteorological parameters irrespective of their daily variations. It also considers the soil as a homogeneous medium, which influences the crop yield estimation, which needs to be addressed among agricultural researchers. Therefore, further modifications are also needed for QUEFTS to incorporate different agro-climatic and management conditions and different interactive processes, including other micronutrients, irrigation practices, and sub-soil properties as this model assumes that nutrients are the only limiting factors in crop yield. This review also demands the necessity to focus on the nutrient management of other food crops to ensure food security. [ABSTRACT FROM AUTHOR]

Nepal is a major rice producer of South Asia, feeding more than 20 million people of the country and abroad. However, productivity and profitability of rice are low in Nepal compared to other regional countries. Large yield gaps exist between attainable and farmers' yields and nutrient management is identified as one of the major reasons. Nutrient Expert® (NE), a decision-support tool based on site-specific nutrient management (SSNM) principles has been validated and applied in many countries of Asia and Africa as new recommendation protocol for nutrient management in selected crops, including rice. Present study used NE® Rice as nutrient management protocol in farmers' fields across Terai and mid-hills regions of Nepal during 2014–2018. The study revealed that NE-based fertilizer recommendations resulted in increase in yield over 2.0 t.ha−1 (p ≤ 0.05) and double the profits compared to existing blanket fertilizer recommendation, and farmers' fertilizer practice. Due to large variations in slope, altitude, soil, and management, performance of NE® varied across locations. Its performance was better in Terai due to flat lands and less variations in soil types, compared to sloping lands and varied soils of mid-hills. NE tool provided adequate guidance to apply the required rate of fertilizer that matched the crop requirement and soil nutrient supply of each farmer fields. The novelty of the study is introduction of a dynamic fertilizer recommendation approach that can supplement the existing static blanket recommendation system. We conclude that Nutrient Expert® - Rice can be considered as an effective tool for nutrient recommendation for rice in Nepal. [ABSTRACT FROM AUTHOR]

An experiment was conducted to study the effect of nutrient management and varieties of maize on productivity and economics and their residual effect on succeeding gobhi sarson crop. Four nutrient management treatments (viz. site-specific nutrient management, SSNM; recommended fertilizer dose, RFD; 50% RFD and farmer's practice) were applied to five varieties of maize (viz. PAC 740, PMZ-4, PSCL 4640, HQPM 1, and BISCO 855) during the kharif seasons of 2012 and 2013 at Palampur. The residual effects of fertilizers were studied in succeeding gobhi sarson. The SSNM-based nutrient application in maize significantly increased crop dry matter, cobs/ha, grain yield, nitrogen, phosphorus and potassium (NPK) uptake, succeeding gobhi sarson seed yield, maize grain equivalent yield, net return, profitability, and B:C. The SSNM-based nutrient application in maize resulted in 4.2–4.6% and 32.6–46.2% higher system productivity and Indian Net Rupee (INR) 4,507–4,926 and INR 28,837–30,078 higher net returns of over recommended fertilizer application and farmer practice, respectively. SSNM had lowest productivity cost of INR 3.1/kg grain. Apparent NPK productivity (62.4 kg grain/kg NPK applied) was highest under 50% RFD. BISCO 855 was earliest in silking with bolder grain. PMZ-4 and PSCL 4640 gave significantly higher dry matter, cob number, grain and stover yield, apparent NPK and physiological productivity, maize equivalent yield, net return and B:C, and lower productivity cost. Gobhi sarson seed yield was not significantly affected by preceding maize varieties. For higher system productivity and income from the maize-gobhi sarson, SSNM with PMZ 4 or PSCL 4640 varieties of maize must be adopted. [ABSTRACT FROM AUTHOR]

This study was conducted in order to determine the status of different pools of inorganic phosphorus in surface and sub-surface soils, changed over 3 years of intensive cropping with Rice-Maize-Green gram (residual) under site-specific nutrient management and work out the correlation among different pools of P. Postharvest soil properties indicated that soil pH was increasing gradually due to lime addition as one input, in spite of the removal of basic cations. There was small but a positive build up of organic carbon, available N and P. There was a drastic reduction in available K status in postharvest soil with available S were found. Phosphorus was fractionated broadly in two groups (a) Inorganic-P and (b) Organic-P. The inorganic P fractions constituted 71.9–86.0% of total P, whereas organic-P constituted 14.0–28.1% in surface soil and 75.9–81% and 18.1–24.1% in subsoil, respectively. The sequence of different pools in order of Fe-P > RS-P > Al-P > Ca-P > occluded-P > saloid-P (surface soil 0–15 cm) and RS-P > Fe-P > Ca-P > Occluded-P > Al-P > saloid-P (Subsurface soil 15–30 cm). Bray's extracted-P is positively correlated with Fe (r = 0.71*) and Al-P (r = 0.67*) indicating the major contribution of both fractions toward available P pool in surface soil, whereas, Al-P majorly contribute in sub-surface soil. Among the inorganic fractions of Phosphorus, Fe-P (r = 0.72*) are showing positive and significant relationship with total uptake of P, in surface soil and Al-P (0.70*) in sub-surface soil. Thus, understanding the use of both inorganic and organic fertilizer under intensive cropping for 3 years must be planned carefully because the interaction of different forms of P, in acidic soil and various other factors influencing P availability to plants. [ABSTRACT FROM AUTHOR]

Understanding, predicting, and managing the spatiotemporal complexity of stream thermal regimes requires monitoring strategies designed specifically to make inference about spatiotemporal variability on the whole stream network. Moreover, monitoring can be tailored to capture particular facets of this complex thermal landscape that may be important indicators for species and life stages of management concern. We applied spatial stream network models (SSNMs) to an empirical dataset of water temperature from the Snoqualmie River watershed, WA, and use results to provide guidance with respect to necessary sample size, location of new sites, and selection of a modeling approach. As expected, increasing the number of monitoring stations improved both predictive precision and the ability to estimate covariates of stream temperature; however, even relatively small numbers of monitoring stations, n = 20, did an adequate job when well-distributed and when used to build models with only a few covariates. In general, winter data were easier to model and, across seasons, mean temperatures were easier to model than summer maximums, winter minimums, or variance. Adding new sites was advantageous but we did not observe major differences in model performance for particular new site locations. Adding sites from parts of the river network with thermal regimes which differed from the rest of the network, and which were therefore highly influential, improved nearby predictions but reduced model-estimated precision of predictions in the rest of the network. Lastly, using models which accounted for the network-based spatial correlation between observations made it much more likely that estimated prediction confidence intervals covered the true parameter; the exact form of the spatial correlation made little difference. By incorporating spatial structure between observations, SSNMs are particularly valuable for accurate estimation of prediction uncertainty at unmeasured locations. Based on our results, we make the following suggestions for designing water temperature monitoring arrays: (1) make use of pilot data when possible; (2) maintain a distribution of monitors across the stream network (i.e., over space and across the full range of covariates); (3) maintain multiple spatial clusters for more accurately estimating correlation of nearby sites; (4) if sites are to be added, prioritize capturing a range of covariates over adding new tributaries; (5) maintain a sensor array in winter; and (6) expect reduced accuracy and precision when predicting metrics other than means. [ABSTRACT FROM AUTHOR]

The present experiment was carried out during 2013-14 and 2014-15 at Norman E. Borlaug Crop Research Centre, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India representing the Tarai belt of Uttarakhand. The experiment was laid out in a split plot design with 18 treatments with 06 tillage options i.e. FIRBS, conventional tillage (CT), sub soiling (SS), zero tillage (ZT), minimum tillage with two pass of rotavator (MT) and permanent raised bed system (PRBS) in main plot and 03 nutrient levels i.e. 50% of recommended dose of fertilizers (50% RDF), site specific nutrient management (SSNM) and 100% recommended dose of fertilizer (RDF) in sub plot with three replications. The tillage options and nutrients levels influenced significantly most of the growth and yield attributes. Based on pooled values PRBS the highest grain yield that was statistically equal to FIRBS and SS. In general wheat grain yield was almost equal at PRBS, FIRBS and SS that was 9.5 and 16% and 32.5% greater than CT, MT and ZT respectively. The harvest index was also recorded significantly highest under FIRBS followed by PRBS and Nutrient use efficiency was recorded highest under PRBS followed by SS and FIRBS, though remained non significant on pooled basis. Similarly RDF produced highest grain yield on pooled basis that was 11.7 and 48.6% higher than SSNM and 50% RDF, respectively but the harvest index was found significantly highest under at 50% RDF. The Nutrient use efficiency was recorded significantly highest under 50% during growth stages. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilizer has been excessively used in China's crop production, resulting in nonpoint pollution and significant greenhouse gas emissions. Previous studies show that farmers can reduce N-fertilizer upon receiving knowledge training. However, there is little evidence of the effectiveness of this effort in the long term. Based on an experimental study of site-specific nutrient management for rice production in China and a unique household dataset captured over seven years, this study shows that the traditional training approach has not been effective in reducing Chinese farmers' N-fertilizer use. Persistently reducing farmers' excessive use of N-fertilizer in the long term will require intensive in-field guidance – something that requires substantial investment and institutional innovation. [ABSTRACT FROM AUTHOR]

The experiment was conducted during kharif 2011 in sandy clay loam soil at Zonal Agricultural Research Station, UAS, GKVK campus, Bengaluru, Karnataka to study yield attributes, nutrient uptake and yield of maize (Zea mays L.) hybrid NAH 1137 (Hema) and economics of maize cultivation as influenced by nutrient management through various fertilization approaches. The investigation consisted SSNM through fertilizers for targeted yield of 8 and 10 t ha-1, SSNM through INM for targeted yield of 8 and 10 t ha-1, STCR through fertilizers for targeted yield of 8 and 10 t ha-1, STCR through INM for targeted yield of 8 and 10 t ha-1. These eight treatments were compared with 100 per cent RDF and100 per cent RDF + FYM @ 10 t ha-1, and were replicated thrice. Among the treatments, SSNM through fertilizers for targeted yield of 10 t ha-1 recorded higher dry matter production (501.4 g), cob length (20.3 cm), number of grain rows cob-1 (20.5), number of grains row-1 (41.3), number of grains plant-1 (891.2) test weight (32.9 g) and significantly higher grain yield (9.77 t ha-1) as compared to other treatments. Whereas, significantly lower cob length (16.5 cm) number of grain rows cob-1 (13.6), number of grains row-1 (31.4), number of grains plant-1 (426.7) test weight (21.4 g), Grain yield (4.04 t ha-1) were recorded in the treatment with the application of 100 % RDF. Significantly higher nutrient uptake (504.8, 103.1 and 212.3 N, P and K kg ha-1) was recorded in SSNM through fertilizers for targeted yield of 10 t ha-1 over 100 % RDF (219.4, 32.2 and 73; N, P and K kg ha-1) and economics. [ABSTRACT FROM AUTHOR]

The experiment was conducted during kharif 2011 in sandy clay loam soil at Zonal Agricultural Research Station, UAS, GKVK campus, Bengaluru, Karnataka to study yield attributes, nutrient uptake and yield of maize (Zea mays L.) hybrid NAH 1137 (Hema) and economics of maize cultivation as influenced by nutrient management through various fertilization approaches. The investigation consisted SSNM through fertilizers for targeted yield of 8 and 10 t ha-1, SSNM through INM for targeted yield of 8 and 10 t ha-1, STCR through fertilizers for targeted yield of 8 and 10 t ha-1, STCR through INM for targeted yield of 8 and 10 t ha-1. These eight treatments were compared with 100 per cent RDF and100 per cent RDF + FYM @ 10 t ha-1, and were replicated thrice. Among the treatments, SSNM through fertilizers for targeted yield of 10 t ha-1 recorded higher dry matter production (501.4 g), cob length (20.3 cm), number of grain rows cob-1 (20.5), number of grains row-1 (41.3), number of grains plant-1 (891.2) test weight (32.9 g) and significantly higher grain yield (9.77 t ha-1) as compared to other treatments. Whereas, significantly lower cob length (16.5 cm) number of grain rows cob-1 (13.6), number of grains row-1 (31.4), number of grains plant-1 (426.7) test weight (21.4 g), Grain yield (4.04 t ha-1) were recorded in the treatment with the application of 100% RDF. Significantly higher nutrient uptake (504.8, 103.1 and 212.3 N, P and K kg ha-1) was recorded in SSNM through fertilizers for targeted yield of 10 t ha-1 over 100% RDF (219.4, 32.2 and 73; N, P and K kg ha-1) and economics. [ABSTRACT FROM AUTHOR]

Fertilizer K and P requirements for rice ( Oryza sativa L.) can be determined with site-specific nutrient management (SSNM) using estimated target yield, nutrient balances, and yield gains from added nutrient. We used the QUEFTS (QUantitative Evaluation of the Fertility of Tropical Soils) model with >8000 plot-level observations to estimate the relationship between grain yield and nutrient accumulation in above-ground dry matter of irrigated rice with harvest index ≥ 0.4. Predicted reciprocal internal efficiencies (RIEs) at 60–70% of yield potential corresponded to plant accumulation of 14.6 kg N, 2.7 kg P, and 15.9 kg K per tonne of grain yield. These RIEs enable determination of plant requirements for K and P and net output of K and P in harvested grain and removed crop residues at a target yield. Yield gains for nutrient applied to irrigated rice averaged 12% for K and 9% for P for 525 to 531 observations. For fields without certain yield gain, fertilizer K and P requirements can be determined by a partial maintenance approach (i.e., fertilizer input < output in nutrient balance), which considers nutrient supply mediated through soil processes and balances trade-offs between financial loss with full maintenance rates and risk of excessive nutrient depletion without nutrient application. When yield gains to an added nutrient are certain, partial maintenance plus yield gain can be used to determine fertilizer requirements. The SSNM-based approach and algorithms enable rapid development of field-specific K and P management. [ABSTRACT FROM AUTHOR]

Crop modelling can provide us with a vast amount of real-time information about fertilizer dose to achieve the target yield, crop conditions, etc. Nutrient-use efficiency in wheat is low because of conventional blanket and imbalanced fertilizer use. Estimation of fertilizer requirements based on quantitative approaches can assist in improving yields and nutrient-use efficiency. Field experiments were conducted in 20 sites in eastern India to assess the soil supply, requirement and internal efficiency of nitrogen (N), phosphorous (P), potassium (K) and zinc (Zn) in wheat. The data were used to calibrate the QUEFTS (QUantitative Evaluation of the Fertility of Tropical Soils) model for site-specific, balanced fertilizer recommendations. The parameters of maximum accumulation (a) and maximum dilution (d) in wheat were calculated for N (35 and 100 kg), P (129 and 738 kg), K (17 and 56 kg), and Zn (21502 and 140244 mg). Grain yield of wheat showed good correlation with N (R² = 0.937**), P (R² = 0.901**) and K uptake (R² = 0.801**). The NPK ratio to produce 1 ton grain yield of wheat was derived to be 4.9:1.0:8.9. The relationships between chemical properties and nutrient supplying capacity of soils were also established. The model was validated using the data of four other experiments. Observed yields with different amounts of N, P, K and Zn were in good agreement with the predicted values suggesting that the validated QUEFTS model can be used for site-specific nutrient management in wheat. [ABSTRACT FROM AUTHOR]