scholarly journals Predicting Phosphorus and Potato Yield Using Active and Passive Sensors

Agriculture ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 564
Author(s):  
Ahmed Jasim ◽  
Ahmed Zaeen ◽  
Lakesh K. Sharma ◽  
Sukhwinder K. Bali ◽  
Chunzeng Wang ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Multispectral Imaging ◽  
P Uptake ◽  
Potato Yield ◽  
Sensor Data ◽  
Poor Correlation ◽  
Linear Regression Models ◽  
Plant P Uptake ◽  
Passive Sensors ◽  
Potato Yields

Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as triple superphosphate (46% P2O5). Vegetation indices (VIs) and plant pigment levels were calculated at various time points during the potato growth cycle, correlated with total potato yields and P uptake by the stepwise fitting of multiple linear regression models. Data generated by Crop Circle™ and GreenSeeker™ had a low predictive value of potato yields, especially early in the season. Crop Circle™ performed better than GreenSeeker™ in predicting plant P uptake. In contrast, the passive sensor data provided good estimates of total yields early in the season but had a poor correlation with P uptake. The combined use of active and passive sensors presents an opportunity for better P management in potatoes.

scholarly journals APLIKASI PUPUK ORGANIK HAYATI, KIMIA DAN METODE KONSERVASI TANAH UNTUK MENINGKATKAN HASIL KENTANG (Solanum tuberosum L.) PADA ANDISOL DI BREBES

Agrin ◽  
2019 ◽  
Vol 22 (2) ◽  
pp. 132
Author(s):  
Naimatul Khoiriyah ◽  
Tamad Tamad ◽  
Joko Maryanto
Keyword(s):  
Soil Conservation ◽  
Solanum Tuberosum L ◽  
Organic Fertilizer ◽  
P Uptake ◽  
Potato Yield ◽  
Organic Fertilizers ◽  
Soil Science ◽  
Recommended Dosage ◽  
Potato Yields ◽  
The Relationship

Penelitian ini bertujuan untuk mengetahui pengaruh pupuk organik hayati, kimia dan metode konservasitanah terhadap hasil kentang di andisol, serta hubungan hasil kentang dan serapan P dengan perlakuan pupukorganik hayati, kimia dan metode konservasi di andisol. Penelitian dilakukan bulan Maret-Desember 2017 di DesaPandansari, Paguyangan, Brebes dan Laboratorium Ilmu Tanah, Fakultas Pertanian, Universitas JenderalSoedirman, Purwokerto. Rancangan percobaan yang digunakan adalah RAK faktorial dengan tiga faktor. Faktorpertama yaitu pupuk organik (P) dengan 6 taraf terdiri dari P1 (kontrol), P2 (POH 20 ton/ha), P3 (POH 15 ton/ha),P4 (POH 10 ton/ha), P5 (POH 5 ton/ha) dan P6 (POH 2,5 ton/ha). Faktor kedua adalah pupuk kimia (K) dengan 4taraf yaitu K1 (kontrol), K2 (dosis anjuran dan 200 kg kapur), K3 (1/2 dosis anjuran dan 200 kg kapur) dan K4(1/4 dosis anjuran dan 200 kg kapur). Faktor ketiga yaitu lereng dengan 3 taraf, yang terdiri dari L1 (kontrol), L2(bedengan sejajar kontur miring 10%) dan L3 (bedengan sejajar kontur). Variabel yang diamati yaitu tinggitanaman, jumlah daun, hasil kentang, pH H2O, dan serapan P. Hasil penelitian menunjukkan bahwa pupuk organikhayati dan kimia dengan metode konservasi tanah berpengaruh terhadap hasil kentang di andisol dan terdapathubungan korelasi antara hasil kentang dan serapan P.Kata kunci: serapan P, hasil kentang dan andisolABSTRACTThis study aims to determine the effect of biological organic fertilizer, chemistry and soil conservation methodson the results of potatoes at andisol, as well as the relationship between potato yield and P uptake by treatment ofbiological organic fertilizers, chemicals and conservation methods in andisol. This research was conducted inMarch-December 2017 in Pandansari Village, Paguyangan, Brebes and Soil Science Laboratory, Faculty ofAgriculture, Jenderal Soedirman University, Purwokerto. The experimental design used was factorial RandomizedGroup Design (RAK) with three factors. The first factor is organic fertilizer (P) with 6 levels consisting of P1(control), P2 (POH 20 tons / ha), P3 (POH 15 tons / ha), P4 (POH 10 tons / ha), P5 (POH 5 tons / ha) and P6(POH 2.5 tons / ha). The second factor is chemical fertilizer (K) with 4 levels, namely K1 (control), K2(recommended dosage and 200 kg of lime), K3 (1/2 recommended dose and 200 kg of lime) and K4 (1/4recommended dose and 200 kg chalk). The third factor is the slope with 3 levels, which consists of L1 (control),L2 (10% sloping contour parallel beds) and L3 (contour parallel beds). The variables observed were plant height,leaf number, potato yield, H2O pH, and P. uptake. The results showed that biological and chemical organicfertilizers with soil conservation methods influenced the yield of potatoes in andisol and there was a correlationbetween potato yields and P uptake.Keywords: P uptake, potato yield and andisol

scholarly journals Potato Yield Prediction Using Machine Learning Techniques and Sentinel 2 Data

2019 ◽  
Vol 11 (15) ◽  
pp. 1745 ◽  
Author(s):  
Gómez ◽  
Salvador ◽  
Sanz ◽  
Casanova
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Precision Agriculture ◽  
Input Data ◽  
Spatial Information ◽  
Potato Yield ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Potato Yields ◽  
Sentinel 2

Traditional potato growth models evidence certain limitations, such as the cost of obtaining the input data required to run the models, the lack of spatial information in some instances, or the actual quality of input data. In order to address these issues, we develop a model to predict potato yield using satellite remote sensing. In an effort to offer a good predictive model that improves the state of the art on potato precision agriculture, we use images from the twin Sentinel 2 satellites (European Space Agency—Copernicus Programme) over three growing seasons, applying different machine learning models. First, we fitted nine machine learning algorithms with various pre-processing scenarios using variables from July, August and September based on the red, red-edge and infra-red bands of the spectrum. Second, we selected the best performing models and evaluated them against independent test data. Finally, we repeated the previous two steps using only variables corresponding to July and August. Our results showed that the feature selection step proved vital during data pre-processing in order to reduce multicollinearity among predictors. The Regression Quantile Lasso model (11.67% Root Mean Square Error, RMSE; R2 = 0.88 and 9.18% Mean Absolute Error, MAE) and Leap Backwards model (10.94% RMSE, R2 = 0.89 and 8.95% MAE) performed better when predictors with a correlation coefficient > 0.5 were removed from the dataset. In contrast, the Support Vector Machine Radial (svmRadial) performed better with no feature selection method (11.7% RMSE, R2 = 0.93 and 8.64% MAE). In addition, we used a random forest model to predict potato yields in Castilla y León (Spain) 1–2 months prior to harvest, and obtained satisfactory results (11.16% RMSE, R2 = 0.89 and 8.71% MAE). These results demonstrate the suitability of our models to predict potato yields in the region studied.

scholarly journals Nondestructive estimation of potato yield using relative variables derived from multi-period LAI and hyperspectral data based on weighted growth stage

Plant Methods ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Shanjun Luo ◽  
Yingbin He ◽  
Qian Li ◽  
Weihua Jiao ◽  
Yaqiu Zhu ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Growth Stage ◽  
Estimation Error ◽  
Potato Yield ◽  
Hyperspectral Data ◽  
Single Stage ◽  
Accurate Estimation ◽  
Yield Estimation ◽  
Area Index ◽  
Red Edge

Abstract Background The accurate estimation of potato yield at regional scales is crucial for food security, precision agriculture, and agricultural sustainable development. Methods In this study, we developed a new method using multi-period relative vegetation indices (rVIs) and relative leaf area index (rLAI) data to improve the accuracy of potato yield estimation based on the weighted growth stage. Two experiments of field and greenhouse (water and nitrogen fertilizer experiments) in 2018 were performed to obtain the spectra and LAI data of the whole growth stage of potato. Then the weighted growth stage was determined by three weighting methods (improved analytic hierarchy process method, IAHP; entropy weight method, EW; and optimal combination weighting method, OCW) and the Slogistic model. A comparison of the estimation performance of rVI-based and rLAI-based models with a single and weighted stage was completed. Results The results showed that among the six test rVIs, the relative red edge chlorophyll index (rCIred edge) was the optimal index of the single-stage estimation models with the correlation with potato yield. The most suitable single stage for potato yield estimation was the tuber expansion stage. For weighted growth stage models, the OCW-LAI model was determined as the best one to accurately predict the potato yield with an adjusted R2 value of 0.8333, and the estimation error about 8%. Conclusion This study emphasizes the importance of inconsistent contributions of multi-period or different types of data to the results when they are used together, and the weights need to be considered.

scholarly journals Phosphorus acquisition and internal utilization efficiency in tropical maize genotypes

2008 ◽  
Vol 43 (7) ◽  
pp. 893-901 ◽  
Author(s):  
Sidney Netto Parentoni ◽  
Claudio Lopes de Souza Júnior
Keyword(s):  
Grain Yield ◽  
Selection Index ◽  
P Uptake ◽  
Utilization Efficiency ◽  
Available P ◽  
Phosphorus Acquisition ◽  
Tropical Maize ◽  
Maize Genotypes ◽  
Plant P Uptake ◽  
Soil Available P

The objective of this work was to determine the relative importance of phosphorus acquisition efficiency (PAE - plant P uptake per soil available P), and phosphorus internal utilization efficiency (PUTIL - grain yield per P uptake) in the P use efficiency (PUE - grain yield per soil available P), on 28 tropical maize genotypes evaluated at three low P and two high P environments. PAE was almost two times more important than PUTIL to explain the variability observed in PUE, at low P environments, and three times more important at high P environments. These results indicate that maize breeding programs, to increase PUE in these environments, should use selection index with higher weights for PAE than for PUTIL. The correlation between these two traits showed no significance at low or at high P environments, which indicates that selection in one of these traits would not affect the other. The main component of PUTIL was P quotient of utilization (grain yield per grain P) and not the P harvest index (grain P per P uptake). Selection to reduce grain P concentration should increase the quotient of utilization and consequently increase PUTIL.

scholarly journals Gafsa rock phosphate and triple superphosphate for dry matter production and P uptake by corn

2005 ◽  
Vol 62 (2) ◽  
pp. 159-164 ◽  
Author(s):  
Rossini Mattos Corrêa ◽  
Clístenes Williams Araújo do Nascimento ◽  
Silvana Keely de Sá Souza ◽  
Fernando José Freire ◽  
Gleibson Barbosa da Silva
Keyword(s):  
Dry Matter ◽  
Rock Phosphate ◽  
P Uptake ◽  
Production Costs ◽  
Dry Matter Production ◽  
Triple Superphosphate ◽  
Broadcast Application ◽  
Matter Production ◽  
Plant P Uptake ◽  
Corn Plants

Crops in general make poor use of phosphorous fertilizer and, as a result, recommended rates and production costs are very high. Phosphorus can be made more readily available to plants by proper management of phosphate fertilization, selecting both, type of fertilizer and application method. This study was carried out to evaluate the efficiency of the natural Gafsa rock phosphate and the triple superphosphate on dry matter production and P uptake by corn plants cultivated in a greenhouse. Fertilizers were applied localized and broadcast/incorporated on to two soils with contrasting phosphorus capacity factors (PCF). Rock phosphate broadcast application was as efficient as triple superphosphate in increasing corn plant dry matter in the Tropudult, with lower PCF. This effect was not observed on the Haplustox, owing to the lower P solubility due to the higher Ca concentration in this soil. Triple superphosphate rates increased plant P uptake in both soils and for both application forms. Rock phosphate resulted in higher P-content in plants, but only for broadcast application on the Ultisol.

scholarly journals Agroecological Determinants of Potato Spatiotemporal Yield Variation at the Landscape Level in the Central and Northern Ukraine

2021 ◽  
Vol 4 (2) ◽  
pp. 34-47
Author(s):  
Anastasiia Zymaroieva ◽  
Tetiana Fedoniuk ◽  
Svitlana Matkovska ◽  
Olena Andreieva ◽  
Victor Pazych
Keyword(s):  
Crop Yields ◽  
Climatic Factors ◽  
High Sensitivity ◽  
Potato Yield ◽  
Limiting Factors ◽  
Forest Steppe ◽  
Yield Parameters ◽  
Bioclimatic Variables ◽  
Potato Yields ◽  
The Relationship

Global food security largely depends on the crop yield increase, so the study of the yield-limiting factors of potato (the second bread) is a pressing issue today. This study determines the contribution of the agroecological factors, namely, bioclimatic variables, soil indicators, and factors of landscape diversity, to the variation in potato yields. Conducted in Polissya and Forest-steppe zones of Ukraine during 1991–2017, this study has not only addressed the relationship between ecological determinants and potato yields, but also considered crop yields as a dynamic system. The dynamics of potato yields from the mid-1990s to the present is described by a log-logistic model. There are statistically significant regression dependencies between potato yield parameters and agroecological factors. Potato yield is dependent on the diversity of landscape cover. The relationship between yield parameters and landscape-ecological diversity is non-linear, which determines the presence of optimal landscape structure for the highest potato yields. Among climatic factors, the continental climate is of the greatest importance for potato yield. The high sensitivity of potato yield parameters to soil indices was found, and mostly the soil texture components (silt content), which largely determines the potato yield spatial variation.

scholarly journals MULTI-SENSOR DATA ACQUISITION AND INTEGRATION PROCESSES FOR THE STUDY AND DOCUMENTATION OF THE CHURCH OF SANTA MARIA DEGLI ANGELI IN PIZZOFALCONE IN NAPLES

2021 ◽  
Vol XLVI-M-1-2021 ◽  
pp. 571-578
Author(s):  
M. Pulcrano ◽  
S. Scandurra ◽  
E. Fragalà ◽  
D. Palomba ◽  
A. di Luggo
Keyword(s):  
Comparative Analysis ◽  
Data Acquisition ◽  
Critical Analysis ◽  
3D Models ◽  
Sensor Data ◽  
Complete Representation ◽  
Passive Sensors ◽  
Santa Maria ◽  
The Church ◽  
3D Digital Models

Abstract. The paper presents the results of a research carried out on the Church of Santa Maria degli Angeli in Pizzofalcone in Naples, in which multi-sensor surveys have been performed in order to assess the architectonical, geometrical and colorimetric characteristics of the majestic basilica. The use of integrated technologies made it possible to realize 3D digital models that allowed the complete representation of the building, integrating data and filling the gaps of the different previous surveys. The performances of the various reality-based technologies employed have been subjected to critical analysis in order to maximize their potential, optimize survey and data elaboration phases, and obtain the expected results. These latter have been defined through the derived digital re-elaborations and representations. Hence, the objective of the research is to carry out a comparative analysis on the 3D models generated through the different active and passive sensors employed in order to proceed with their integration and achieve an accurate, original and updated methodology of building survey.

scholarly journals Water and phosphorus uptake by upland rice root systems unraveled under multiple scenarios: linking a 3D soil-root model and data

2020 ◽  
Author(s):  
Trung Hieu Mai ◽  
Pieterjan De Bauw ◽  
Andrea Schnepf ◽  
Roel Merckx ◽  
Erik Smolders ◽  
...  
Keyword(s):  
Upland Rice ◽  
Phosphorus Uptake ◽  
Root Systems ◽  
Multiscale Model ◽  
P Uptake ◽  
Water Dynamics ◽  
Small Scale ◽  
P Availability ◽  
P Deficiency ◽  
Plant P Uptake

AbstractBackground and aimsUpland rice is often grown where water and phosphorus (P) are limited and these two factors interact on P bioavailability. To better understand this interaction, mechanistic models representing small-scale nutrient gradients and water dynamics in the rhizosphere of full-grown root systems are needed.MethodsRice was grown in large columns using a P-deficient soil at three different P supplies in the topsoil (deficient, suboptimal, non-limiting) in combination with two water regimes (field capacity versus drying periods). Root architectural parameters and P uptake were determined. Using a multiscale model of water and nutrient uptake, in-silico experiments were conducted by mimicking similar P and water treatments. First, 3D root systems were reconstructed by calibrating an architecure model with observed phenological root data, such as nodal root number, lateral types, interbranch distance, root diameters, and root biomass allocation along depth. Secondly, the multiscale model was informed with these 3D root architectures and the actual transpiration rates. Finally, water and P uptake were simulated.Key resultsThe plant P uptake increased over threefold by increasing P and water supply, and drying periods reduced P uptake at high but not at low P supply. Root architecture was significantly affected by the treatments. Without calibration, simulation results adequately predicted P uptake, including the different effects of drying periods on P uptake at different P levels. However, P uptake was underestimated under P deficiency, a process likely related to an underestimated affinity of P uptake transporters in the roots. Both types of laterals (i.e. S- and L-type) are shown to be highly important for both water and P uptake, and the relative contribution of each type depend on both soil P availability and water dynamics. Key drivers in P uptake are growing root tips and the distribution of laterals.ConclusionsThis model-data integration demonstrates how multiple co-occurring single root phene responses to environmental stressors contribute to the development of a more efficient root system. Further model improvements such as the use of Michaelis constants from buffered systems and the inclusion of mycorrhizal infections and exudates are proposed.

Sign in / Sign up

Export Citation Format

Share Document