scholarly journals To Blend or Not to Blend? A Framework for Nationwide Landsat–MODIS Data Selection for Crop Yield Prediction

2020 ◽  
Vol 12 (10) ◽  
pp. 1653
Author(s):  
Yang Chen ◽  
Tim R. McVicar ◽  
Randall J. Donohue ◽  
Nikhil Garg ◽  
François Waldner ◽  
...  
Keyword(s):  
Crop Yield ◽  
Temporal Frequency ◽  
Management Strategies ◽  
Crop Growth ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Landsat Images ◽  
Yield Model ◽  
Pixel Resolution ◽  
Country Level

The onus for monitoring crop growth from space is its ability to be applied anytime and anywhere, to produce crop yield estimates that are consistent at both the subfield scale for farming management strategies and the country level for national crop yield assessment. Historically, the requirements for satellites to successfully monitor crop growth and yield differed depending on the extent of the area being monitored. Diverging imaging capabilities can be reconciled by blending images from high-temporal-frequency (HTF) and high-spatial-resolution (HSR) sensors to produce images that possess both HTF and HSR characteristics across large areas. We evaluated the relative performance of Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat, and blended imagery for crop yield estimates (2009–2015) using a carbon-turnover yield model deployed across the Australian cropping area. Based on the fraction of missing Landsat observations, we further developed a parsimonious framework to inform when and where blending is beneficial for nationwide crop yield prediction at a finer scale (i.e., the 25-m pixel resolution). Landsat provided the best yield predictions when no observations were missing, which occurred in 17% of the cropping area of Australia. Blending was preferred when <42% of Landsat observations were missing, which occurred in 33% of the cropping area of Australia. MODIS produced a lower prediction error when ≥42% of the Landsat images were missing (~50% of the cropping area). By identifying when and where blending outperforms predictions from either Landsat or MODIS, the proposed framework enables more accurate monitoring of biophysical processes and yields, while keeping computational costs low.

scholarly journals The Effect of Different Weed Management Strategies on the Growth and Yield of Direct-Seeded Dry Rice (Oryza sativa)

2016 ◽  
Vol 34 (1) ◽  
pp. 57-64 ◽  
Author(s):  
S. MUHAMMAD ◽  
I. MUHAMMAD ◽  
A. SAJID ◽  
L. MUHAMMAD ◽  
A. MAQSHOOF ◽  
...  
Keyword(s):  
Weed Control ◽  
Crop Yield ◽  
Weed Management ◽  
Management Strategies ◽  
Control Measures ◽  
Growth And Yield ◽  
Primary Concern ◽  
Herbicide Treatment ◽  
Direct Seeded ◽  
Hand Weeding

Weed management is a primary concern in direct seeded rice (DSR) cropping because weed growth becomes a major constraint on crop yield. A two year field study was set up to evaluate the effect of various weed control measures on crop growth, grain yield and grain quality of DSR. The experiment involved five different weed control measures: hand weeding, hoeing, inter-row tine cultivation, inter-row spike hoeing and herbicide treatment (Nominee 100 SC). The extent of weed control (compared to a non-weeded control) ranged from 50-95%. The highest crop yield was obtained using hand weeding. Hand weeding, tine cultivation and herbicide treatment raised the number of fertile rice tillers formed per unit area and the thousand grain weight. Tine cultivation provided an effective and economical level of weed control in the DSR crop.

scholarly journals Crop response to soils amended with biochar: expected benefits and unintended risks

2017 ◽  
Vol 11 ◽  
Author(s):  
Raghunath Subedi ◽  
Chiara Bertora ◽  
Laura Zavattaro ◽  
Carlo Grignani
Keyword(s):  
Soil Quality ◽  
Crop Yield ◽  
Crop Yields ◽  
Soil Health ◽  
Crop Growth ◽  
Plant Diseases ◽  
Growth And Yield ◽  
Yield Response ◽  
Small Scale ◽  
Positive Effects

Biochar (BC) from biomass waste pyrolysis has been widely studied due to its ability to increase carbon (C) sequestration, reduce greenhouse gas (GHG) emissions, and enhance both crop growth and soil quality. This review summarizes the current knowledge of BC production, characterization, and types, with a focus on its positive effects on crop yield and soil properties versus the unintended risks associated with these effects. Biochar-amended soils enhance crop growth and yield via several mechanisms: expanded plant nutrient and water availability through increased use efficiencies, improved soil quality, and suppression of soil and plant diseases. Yield response to BC has been shown to be more evident in acidic and sandy soils than in alkaline and fine-textured soils. Biochar composition and properties vary considerably with feedstock and pyrolysis conditions so much that its concentrations of toxic compounds and heavy metals can negatively impact crop and soil health. Consequently, more small-scale and greenhouse-sited studies are in process to investigate the role of BC/soil/crop types on crop growth, and the mechanisms by which they influence crop yield. Similarly, a need exists for long-term, field-scale studies on the effects (beneficial and harmful) of BC amendment on soil health and crop yields, so that production guidelines and quality standards may be developed for BCs derived from a range of feedstocks.

Frequency of Weeding Okra (Abelmoschus esculentus) for Optimum Growth and Yield

1988 ◽  
Vol 24 (2) ◽  
pp. 247-252 ◽  
Author(s):  
G. O. Iremiren
Keyword(s):  
Crop Yield ◽  
Field Experiments ◽  
Water Movement ◽  
Crop Growth ◽  
Abelmoschus Esculentus ◽  
Growth And Yield ◽  
Weed Competition ◽  
Optimum Growth ◽  
Pod Yield ◽  
Weed Removal

SUMMARYField experiments were carried out during the rainy seasons of 1985 and 1986 to examine the frequency of weeding necessary for the optimum growth and yield of okra in Nigeria. Weed removal within 12 weeks of sowing generally resulted in significantly better crop growth and yield than that in the weedy check. Weeding once as early as four weeks was as beneficial to okra growth and yield as two or three weedings later in the 12 week period. Weed removal four times at 3, 6, 9 and 12 weeks significantly enhanced crop growth and pod yield over all other treatments. For good pod yields, protection from weed competition over most of the duration of crop growth is therefore essential. Such weed removal may enhance crop yield partly by increasing aeration and water movement in the soil.

scholarly journals PREVISÃO DA PRODUÇÃO DE MILHO SUBMETIDO A DIFERENTES NÍVEIS DE MANEJO DE IRRIGAÇÃO VIA MODELO DE SIMULAÇÃO

Irriga ◽  
1998 ◽  
Vol 3 (2) ◽  
pp. 36-47
Author(s):  
Marcia Xavier Peiter ◽  
Fazal Hussain Chaudhry
Keyword(s):  
Agricultural Production ◽  
Water Status ◽  
Irrigation Management ◽  
Management Strategies ◽  
Simulation Models ◽  
Growth And Yield ◽  
Corn Yield ◽  
Yield Model ◽  
Area Index ◽  
Plant Available Water

PREVISÃO DA PRODUÇÃO DE MILHO SUBMETIDO A DIFERENTES NÍVEIS DE MANEJO DE IRRIGAÇÃO VIA MODELO DE SIMULAÇÃO[1]  Marcia Xavier PeiterCurso de Engenharia Agrícola - Universidade Regional do Alto Uruguai e Missões - URI Campus Santiago - Tel.(055)251-1715 - Rua 20 de setembro, 2410 - Santiago, RSFazal Hussain ChaudhryDepartamento de Hidráulica e Saneamento - Escola de Engenharia de São Carlos - USPTel.(016)274-3444 - Av. Dr. Carlos Botelho, 1465 - São Carlos, SP  1 RESUMO O advento de modelos simuladores de crescimento e produção de culturas agrícolas vem permitir que as quantidades de água aplicadas e o momento de rega possam ser testados com significativas reduções de custo, tempo e mão-de-obra, além do que, a estimativa da produção não é influenciada por eventuais fatores externos, alheios ao tratamento aplicado. Desta forma, o presente trabalho tem como objetivo a avaliação, calibração e validação de um modelo de simulação de produção para a cultura do milho quando submetido a diferentes níveis de irrigação, a fim de disponibilizar uma ferramenta que permita a análise desta cultura com maior rapidez e redução de custos. Para a validação do modelo, a cultivar de milho Pioneer 3069 foi submetida a quatro níveis de manejo de irrigação com três repetições em um conjunto de lisímetros de drenagem. Procedeu-se as irrigações sempre que a fração de água disponível fosse igual ou inferior a 0,90; 0,75; 0,60 e 0,45. Através dos resultados obtido, pode-se concluir que o modelo de simulação apresenta uma aceitável estrutura de rotinas para previsão da produção de massa seca total de milho quando a cultura é submetida a diferentes níveis de manejo de rega. Desta forma, o modelo pode ser utilizado para a avaliação das conseqüências produtivas e econômicas de diferentes estratégias de irrigação. UNITERMOS: Simulação, milho, manejo de irrigação  PEITER, M.X., CHAUDHRY, F.H. Corn yield predicted when submitted to different irrigation management levels by simulation model  2 ABSTRACT The advent of simulation models for growth and yield of crops makes it possible to test the influence of irrigation depths and their timings on the economy of agricultural production. This paper calibrates and validates a corn yield model for different irrigation management strategies to obtain a tool for rapid analysis of crop response without having to conduct repeated experiments. Thus, the corn cultivar Pioneer 3069 was submitted to four irrigation management levels with three replications in a number of drainage lysimiters. Irrigations were applied when the plant available water reaches 0,90; 0,75; 0,60 and 0,45. The results show that the calibrated model has an acceptable conceptual structure of computational routines to predict corn dry matter when the crop is irrigated according to different management levels. It is concluded further that the model is capable of predicting correctly the temporal variation of the observed leaf area index and soil water status. KEY-WORDS: Simulation, corn, irrigation management 

scholarly journals How much birch (Betula papyrifera) is too much for maximizing spruce (Picea glauca) growth: a case study in boreal spruce plantation forests

2012 ◽  
Vol 58 (No. 7) ◽  
pp. 314-327 ◽  
Author(s):  
C.D.B. Hawkins ◽  
A. Dhar ◽  
B.J. Rogers
Keyword(s):  
Picea Glauca ◽  
Management Strategies ◽  
Growth And Yield ◽  
Stem Volume ◽  
Growth Data ◽  
Mixed Species ◽  
Yield Model ◽  
Mixedwood Forests ◽  
Spruce Stands ◽  
The Impact

Interest in conifer-broadleaf mixedwood forests has greatly increased due to continuous demand for hardwood products and a shift towards more biological or ecosystem-based management. In British Columbia, more than 30% of the productive forest land is a conifer&ndash;broadleaf mixture and current forest regulations are more conifer biased rather than maintaining a mixed-species condition. The aim of this study was to examine the impact of paper birch on white spruce growth. Spruce growth data from 10 to 18 years old complex stands indicate that radial, height, and stem volume was not impacted by retaining up to 3,000 stems&middot;ha<sup>&ndash;1</sup> of birch. Similarly, growth and yield model projections suggest spruce-birch stands would be more productive up to a threshold birch density (3,000 stems&middot;ha<sup>&ndash;1</sup>) than pure spruce stands. At a 4% real interest rate, the removal of birch from these stands does not appear to be warranted as an investment. The results suggest that instead of encouraging uniform broadleaf removal across conifer plantations, mixed species management strategies could enhance the forest productivity, stand diversity and resilience. &nbsp;

Survival Functions for Site-Prepared Slash Pine Plantations in the Flatwoods of Georgia and Northern Florida

1981 ◽  
Vol 5 (2) ◽  
pp. 59-62 ◽  
Author(s):  
Leon V. Pienaar ◽  
Barry D. Shiver
Keyword(s):  
Management Strategies ◽  
Slash Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Survival Functions ◽  
Inventory Data ◽  
The Difference ◽  
Prediction Systems ◽  
Future Growth

Abstract Survival functions are derived for site-prepared slash pine plantations in the flatwoods of Georgia and northern Florida. Two functions are presented. The first is a function which may be used with any planting-survival count or estimate. This function is probably most useful in conjunction with available yield-prediction systems (with stems/acre as an input) to evaluate alternative management strategies. The second function, the difference equation form of the first function, is most useful in predicting future growth and yield based on inventory data.

Development and use of a barley crop simulation model to evaluate production management strategies in north-eastern Australia

1996 ◽  
Vol 47 (7) ◽  
pp. 997 ◽  
Author(s):  
PJ Goyne ◽  
H Meinke ◽  
SP Milroy ◽  
GL Hammer ◽  
JM Hare
Keyword(s):  
Simulation Model ◽  
Production Management ◽  
Field Experiments ◽  
Management Strategies ◽  
Crop Growth ◽  
Growth And Yield ◽  
Yield Potential ◽  
Weather Data ◽  
Eastern Australia ◽  
North Eastern

A study was undertaken to identify improved management strategies for barley (Hordeum vulgare L.), particularly in relation to time of planting, location, and frost risk in the variable climate of north-eastern Australia. To achieve this objective, a crop growth simulation model (QBAR) was constructed to integrate the understanding, gained from field experiments, of the dynamics of crop growth as influenced by soil moisture and environmental variables. QBAR simulates the growth and yield potential of barley grown under optimal nutrient supply, in the absence of pests, diseases, and weeds. Genotypic variables have been determined for 4 cultivars commonly grown in the northern cereal production areas. Simulations were conducted using long-term weather data to generate the probabilistic yield outcome of cv. Grimmet for a range of times of planting at 10 locations in the north-eastern Australian grain belt. The study indicated that the common planting times used by growers could be too late under certain circumstances to gain full yield potential. Further applications of QBAR to generating information suitable for crop management decision support packages and crop yield forecasting are discussed.

scholarly journals Spatially Weighted Estimation of Broadacre Crop Growth Improves Gap-Filling of Landsat NDVI

2021 ◽  
Vol 13 (11) ◽  
pp. 2128
Author(s):  
Fiona H. Evans ◽  
Jianxiu Shen
Keyword(s):  
Growth Curve ◽  
Cropping Systems ◽  
Crop Growth ◽  
Growth And Yield ◽  
Landsat 8 ◽  
Gap Filling ◽  
Landsat Images ◽  
Curve Estimation ◽  
Spatial Weights ◽  
Weighted Estimation

Seasonal climate is the main driver of crop growth and yield in broadacre grain cropping systems. With a 40-year record of 30 m resolution images and 16-day revisits, the Landsat satellite series is ideal for producing long-term records of remotely sensed phenology to build understanding of how climate affects crop growth. However, the time-series of Landsat images exhibits gaps caused by cloud cover, which is common in wet periods when crops reach maximum growth. We propose a novel spatial–temporal approach to gap-filling that avoids data fusion. Crop growth curve estimation is used to perform temporal smoothing and incorporation of spatial weights allows spatial smoothing. We tested our approach using Landsat NDVI data acquired for an 8000 ha study area in Western Australia using a train/test approach where 157 available Landsat-7 images between 2013 and 2019 were used to train the model, and 95 at least 80% cloud-free Landsat-8 images from the same period were used to test its performance. We found that compared to nonspatial estimation, use of spatial weights in growth curve estimation improved correlation between observed and predicted NDVI by 75%, MAE by 31% and RMSE by 75%. For cropland, the correlation is improved by 58%, the MAE by 36% and the RMSE by 76%. We conclude that spatially weighted estimation of crop growth curves can be used to fill spatial and temporal gaps in Landsat NDVI for the purpose of within-field monitoring. Our approach is also applicable to other data sources and vegetation indices.

Response of corn (Zea mays L.) to various organic-based fertilizers in marginal upland of Sta. Rita, Samar

2017 ◽  
pp. 31-43
Author(s):  
Berta Ratilla ◽  
Loreme Cagande ◽  
Othello Capuno
Keyword(s):  
Block Design ◽  
Management Strategies ◽  
Chemical Properties ◽  
Organic Fertilizers ◽  
Growth And Yield ◽  
Physical And Chemical Properties ◽  
Total N ◽  
Randomized Complete Block Design ◽  
Physical And Chemical ◽  
And Chemical Properties

Organic farming is one of the management strategies that improve productivity of marginal uplands. The study aimed to: (1) evaluate effects of various organic-based fertilizers on the growth and yield of corn; (2) determine the appropriate combination for optimum yield; and (3) assess changes on the soil physical and chemical properties. Experiment was laid out in Randomized Complete Block Design, with 3 replications and 7 treatments, namely; T0=(0-0-0); T1=1t ha-1 Evans + 45-30-30kg N, P2O5, K2O ha-1; T2=t ha-1 Wellgrow + 45-30-30kg N, P2O5, K2O ha-1; T3=15t ha-1 chicken dung; T4=10t ha-1 chicken dung + 45-30-30kg N, P2O5, K2O ha-1; T5=15t ha-1 Vermicast; and T6=10t ha-1 Vermicast + 45-30-30kg N, P2O5, K2O ha-1. Application of organic-based fertilizers with or without inorganic fertilizers promoted growth of corn than the control. But due to high infestation of corn silk beetle(Monolepta bifasciata Horns), its grain yield was greatly affected. In the second cropping, except for Evans, any of these fertilizers applied alone or combined with 45-30-30kg N, P2O5, K2O ha-1 appeared appropriate in increasing corn earyield. Soil physical and chemical properties changed with addition of organic fertilizers. While bulk density decreased irrespective of treatments, pH, total N, available P and exchangeable K generally increased more with chicken dung application.

Book review

2003 ◽  
Vol 51 (3) ◽  
pp. 369
Author(s):  
Z. Berzsenyi
Keyword(s):  
New York ◽  
Mathematical Models ◽  
Crop Growth ◽  
Growth And Yield ◽  
Madison Avenue

A. R. Overman and R. V. Scholtz III.: Mathematical Models of Crop Growth and Yield. Marcel Dekker, 270 Madison Avenue, New York, NY 10016. 2002. Hardcover, 344 pp., 150.00. ISBN 0-8247-0825-3.

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