Agricultural Scene Understanding
Larry Biehl
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Abstract
Percent of total variation in reflectances, greenness and brightness accounted for by soil moisture level and significant agronomic factors and interactions.. .. . A-31 Mean agronomic characteristics of spring wheat canopies by soil moisture level and planting date. •. .. .... .. . A-32 Percent correct classification of spring wheat, fallow, and pasture using unitemporal information (Williams Co.
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Wheat basal crop coefficients determined by normalized difference vegetation index
Irrigation Science, 2005
Crop coefficient methodologies are widely used to estimate actual crop evapotranspiration (ET c) for determining irrigation scheduling. Generalized crop coefficient curves presented in the literature are limited to providing estimates of ET c for ''optimum'' crop condition within a field, which often need to be modified for local conditions and cultural practices, as well as adjusted for the variations from normal crop and weather conditions that might occur during a given growing season. Consequently, the uncertainties associated with generalized crop coefficients can result in ET c estimates that are significantly different from actual ET c , which could ultimately contribute to poor irrigation water management. Some important crop properties such as percent cover and leaf area index have been modeled with various vegetation indices (VIs), providing a means to quantify real-time crop variations from remotely-sensed VI observations. Limited research has also shown that VIs can be used to estimate the basal crop coefficient (K cb) for several crops, including corn and cotton. The objective of this research was to develop a model for estimating K cb values from observations of the normalized difference vegetation index (NDVI) for spring wheat. The K cb data were derived from back-calculations of the FAO-56 dual crop coefficient procedures using field data obtained during two wheat experiments conducted during 1993-1994 and 1995-1996 in Maricopa, Arizona. The performance of the K cb model for estimating ET c was evaluated using data from a third wheat experiment in 1996-1997, also in Maricopa, Arizona. The K cb was modeled as a function of a normalized quantity for NDVI, using a third-order polynomial regression relationship (r 2 =0.90, n=232). The estimated seasonal ET c for the 1996-1997 season agreed to within À33 mm (À5%) to 18 mm (3%) of measured ET c. However, the mean absolute percent difference between the estimated and measured daily ET c varied from 9% to 10%, which was similar to the 10% variation for K cb that was unexplained by NDVI. The preliminary evaluation suggests that remotely-sensed NDVI observations could provide real-time K cb estimates for determining the actual wheat ET c during the growing season. Communicated by E. Christen
Spring Wheat Yield Model for Limited Moisture Conditions <sup>1</sup>
Agronomy Journal, 1978
Models are useful to predict the effect of one or more of the complex climatic soil, water, or crop variables on yield. Such predictions can be used to make economic evaluation of, for example, the cost and benefit of irrigation or date of planting on yield. The objective of •:his study was to develop a model for spring wheat (Triticutn aestivum L.) which could be used for such purposes and which required only readily available data. The model, a modified form of that developed by Hanks (1974) for corn (lea mays L.), is based on a water balance of irrigation, precipitation, soil water, evapotranspiration, and drainage. Relative dry matter yield is assumed to be directly related to relative seasonal transpiration. Relative grain yield is assumed to be related to the multiple of relative transpiration for each of four growth stages raised to the 0.25 power. The validity of the model was tested in 1975 using field experimental data collected especially for this purpose. Two soft white spring wheat and three hard red spring wheat cultivars were grown under several levels of irrigation. Predicted yields agreed closely with measured yields. An additional test of the validity of the model for other irrigated cultivar trials in 1975, 1974, 1973, and 1972 at the same location, and a dryland trial in 1975 at another location, was made. Good agreement with measured results was found for the 1973, 1974, and 1975 irrigated and the 1975 dryland trial. However, the predicted results for the 1972 irrigated trials were about 20% lower than the measured yields.
EC97-107 Nebraska Proso, Sunflower, Oat and Spring Wheat Variety Tests, 1997
1997
METRIC EQUIVALENTS 1 centimeter = 0.394 inches t hectare = 2.471acres 1 kilogram = 2.205 pounds t hectoliter = 2.838 bushels kg/hl =lb/bux1.287 cm = inchesx2.541 ha=acresx0.405 kg=poundsx0.454 hl=bushelsx0.352 kg/ha = bu/A x62.71(56# bu) DEFINITIONS CWT = hundred weight LSD = A statistic (calculated at the 5olo probability level in this book) used to compare the difference between two entries for significance. lf the difference between two entries is larger than the LSD value at the bottom of each table, it is assumed significant. ns= not significant. The differences between twg entries were not statistically significant. 4 EXTENSION CI RCU LAR 97.107 11 TABLE OF CONTENTS
Crop coefficient (Kc) of winter wheat.pdf
Crop coefficient is one of the most important parameters, needed for estimating crop water requirement using the reference crop method, and thus needed for irrigation scheduling and water allocation. This study determined the crop coefficients of winter wheat (Triticum aestivum) based on field measured actual evapotranspiration data for three years (at Ishurdi, Bangladesh, during 2002-03, 2003-04 and 2004 and reference crop evapotranspiration (ET 0 ) using different methods.
Spectral Vegetation Indices as Nondestructive Tools for Determining Durum Wheat Yield
Agronomy Journal, 2000
of breeding progress have been achieved in different environments. Whereas the genetic gain under high-Remote sensing measurements may be a useful tool for quantifying yielding environments has been particularly successful, crop development and yield. Our objective was to study the potential of using spectral reflectance indices to provide accurate and nonde-in other areas such as the Mediterranean region where structive estimates of physiological traits determining yield in durum durum wheat is one of the main cereal crops, progress wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.]. Twentyhas been much slower (Slafer et al., 1993). Indeed, the five genotypes were grown under rainfed and irrigated conditions in empirical breeding approach has obtained only modest northeastern Spain. Reflectance from the vegetation at different yield increases in this region, where drought during the growth stages was measured and the following spectral indices calculast part of the crop cycle is a major factor in limiting lated: simple ratio (SR), normalized difference vegetation index cereal yield (Ceccarelli and Grando, 1996). (NDVI), and photochemical reflectance index (PRI). Crop dry mass The use of morphological and physiological traits as (CDM), leaf area index (LAI), and green area index (GAI) were indirect selection criteria for grain yield is an alternative measured. All the indices and grain yield were greater under irrigated breeding approach. This has come to be known as anathan rainfed conditions. LAI was the crop growth trait that most closely correlated with the spectral reflectance indices, with SR and lytical breeding (Richards, 1982), and implies a better PRI being the best and the worst indices, respectively, for the assessunderstanding of the factors controlling development, ment of crop growth and yield. In rainfed conditions, the spectral growth, and grain yield (Shorter et al., 1991). In recent reflectance indices measured at any crop stage were positively correyears, many selection criteria based on morphological, lated (P Ͻ 0.05) with LAI and yield. Under irrigation, correlations physiological, and biochemical traits have been sugwere only significant during the second half of the grain filling. The gested (see, for example, in relation to durum wheat:
Variation in harvest index of modern spring barley, oat and wheat cultivars adapted to northern growing conditions
Journal of Agricultural Science, 2008
Increased harvest index (HI) has been one of the principal factors contributing to genetic yield improvements in spring barley (Hordeum vulgare L.), oat (Avena sativa L.) and wheat (Triticum aestivum L.) cultivars. Although high HI demonstrates high-yielding ability when cultivars are compared, it can also indicate challenges to yield formation when comparisons are made across differing growing conditions. The present study was designed to investigate variation in HI among modern cereal cultivars relative to that brought about by a northern environment, to assess whether HI still explains the majority of the differences in grain yield when only modern cereal cultivars are compared, and to monitor key traits contributing to HI. Stability of HI was also investigated with reference to the role of tillers. Twelve experiments (3 years, two locations, two nitrogen fertilizer regimes) were carried out in southern Finland to evaluate 12 two-row spring barley, 10 six-row barley, 10 oat and 11 wheat cultivars. In addition to HI, days to heading and maturity, length of grain filling period, grain yield, test weight and 13 traits characterizing plant stand structure were measured and analysed with principal component analysis (PCA) to detect traits associated with HI and those contributing to stability of HI. Although only modern cereals were studied, differences among cultivars were significant both in mean HI and stability of HI, and HI was associated with short plant stature in all modern cereal species. Also, single grain weight was associated with HI in all species. Differences between, but not within, species in HI were partly attributable to differences in tiller performance. Grain yield was associated closely with HI except in two-row barley. It may be possible to further increase HI of wheat, as it still was relatively low. High HI did, however, not indicate the degree of success in yield determination when environments are compared.
Use of Physically Based Models to Evaluate USDA Soil Moisture Classes
Soil Science Society of America Journal, 2011
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Use of Physically Based Models to Evaluate USDA Soil Moisture Classes Pedology C limate is one of the most important soil-forming factors aff ecting the chemical, physical, and biological processes of soil and, in turn, the properties and use of soils. In this respect, Soil Taxonomy (Soil Survey Staff , 2006) diff ers from other classifi cation systems such as the World Reference Base (IUSS Working Group WRB, 2006) and Référentiel Pédologique (Baize and Girard, 2009) by using climate to classify soils. Th is approach recognizes that many soil characteristics are strongly aff ected by climate and also acknowledges the importance of past climate on soil formation. Th e implementation of climate information in soil classifi cation has some obvious advantages, especially when soil classifi cation outputs must be used for further applications. In fact, the soil name has immediate implications for land use and management. For instance, the use of climate allows distinct classifi cations of similar soils occurring in diff erent climatic zones that require diff erent management (e.g., Vertisols from Texas and Canada). On the other hand, the use of climate in soil classifi cation has some well-known drawbacks, among them (i) the lack of climatic data availability, including their time step, which is a major problem in many parts of the world; and (ii) the classifi cation of soils on the basis of features that are not strictly edaphic properties such as pH, cation exchange capacity (CEC), soil organic matter (SOM), etc.
Assessment of durum wheat yield using visible and near-infrared reflectance spectra of canopies
Field Crops Research, 2005
The estimation of grain yield before harvesting could be a very useful tool for breeding programs and productivity forecasting. Canopy reflectance indices have been used for yield estimation, but with limited success. This work was carried out to study the suitability of the visible and near-infrared reflectance spectrum of the canopy for the assessment of grain yield in a set of durum wheat genotypes. Five field experiments, each one including 25 genotypes, were conducted in low, medium and high productivity environments, with average yields of 2.5, 4.5 and 7 t/ha. Spectral reflectance measurements between 400 and 1000 nm were made at anthesis and milk-grain stages. Partial least squares regression (PLSR) was used in the construction of models that were tested by simple regression between genotype means of predicted and observed grain yields. The empirical models for the estimation of grain yield showed generally stronger and more robust assessment of grain yield than previously assayed spectral indices. For the best model, correlation coefficients between genotype means of predicted and measured yield within each of the five environments ranged from 0.53 to 0.76. We concluded that, although the models did not provide an accurate quantification of grain yield, they could still be used to rank genotypes for breeding purposes. The most reliable ranking of genotypes was attained using measurements made at milk-grain stage on medium to high productivity environments.
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PLANT SCIENCES | RESEARCH ARTICLE Spring wheat response to nitrogen, tillage and cropping system under rainfed condition
2016
The objective of this research work was to assess the existing summer fallow elimination by growing short duration leguminous crop (mungbean) and reduction in number of plows could be a good substitute in recent shift of rainfall pattern. The traditional tillage frequencies (exceeding 4-5 plow + 2 harrows) of the summer fallow land without the addition of commercial fertilizers to wheat are the centuryold practices in the project area. The rainfall efficiency is very low and is certainly related to the low and marginal fertility status. The existing wheat-fallow-wheat (W-F-W) where field remains without crop for five-six months in summer was compared with the proposed wheat-mungbean-wheat (W-Mb-W) cropping system by eliminating the summer fallow. Four tillage systems, i.e. no tillage (NT), conventional tillage (CT), reduced tillage (RT), and maximum tillage (MT), were employed before wheat sowing. Wheat (Triticum aestivum L., cv. Tatara) was sown at the residual moisture of the monsoon rainfall and four levels of N (0, 25, 50, and 75 kg ha −1) were added at the time of wheat sowing. Results show that the wetter year (second year) of the experiment had higher soil water (26.35%), grain yield (2,561 kg ha −1), harvest index (43.5%), and water use efficiency (WUE) (6.1 kg ha −1 mm −1). The existing W-F-W cropping system had more soil water (17%), grain yield (17%), harvest index (1%), WUE (9%), and grain N (23%) than W-Mb-W. CT system had more soil water (13%), grain yield (5%), WUE (2%), harvest index (3%), and grain N (5%) as compared with NT. CT also had more soil water contents (5%), grain yield (3%), WUE
Montazeaud et al. Field Crops Research 2016.pdf
The normalized difference vegetation index (NDVI) continues to provide easy and fast methodologies to characterize wheat genetic resources in response to abiotic stresses. This study identifies ways to maximize green leaf area duration during grain filling and develops NDVI models to predict physiological maturity and different stay −green parameters to increase grain yield of rainfed winter wheat under terminal drought. Three wheat populations were evaluated: one containing 240 landraces from Afghanistan, the second with 250 modern lines and varieties, tested for two years under low rainfall conditions in Turkey, and the third with 291 landraces from Central and Western Asia (grown for one year in the same location). The onset of senescence, maximum "greenness", rate of senescence and residual "greenness" at physiological maturity were estimated using sequential measurements of NDVI and have shown significant correlations with grain yield under low rainfall rainfed conditions. Trade-offs were identified among the different stay −green attributes, e.g. delayed onset of senescence and high maximum "greenness" resulted in accelerated rates of senescence and highest yields and were most evident in the landrace populations. It is concluded, that the use of rate of senescence to select for stay −green must be coupled with other stay −green components, e.g. onset of senescence or maximum "greenness" to avoid the effects of the trade-offs on final grain yield. The NDVI decay curves (using the last three NDVI measurements up to maturity) were used to estimate days to maturity using the NDVI decay during the senescence period and days to heading. A training and testing set (20 and 80% of each population, respectively) were used for calibrations allowing for correlations between predicted and observed maturity of up to r = +0.85 (P < 0.0001). This procedure will facilitate large −scale wheat phenotyping in the future.
Spectral Reflectance Indices as a Potential Indirect Selection Criteria for Wheat Yield under Irrigation
Crop Science, 2006
The objectives of this study were to assess the potential of using spectral reflectance indices (SRI) as an indirect selection tool to differentiate spring wheat (Triticum aestivum L.) genotypes for grain yield under irrigated conditions. This paper demonstrates only the first step in using the SRI as indirect selection criteria by reporting genetic variation for SRI among genotypes, the effect of phenology and year on SRI and their interaction with genotypes, and the correlations between SRI and grain yield and yield components of wheat. Three field experiments-15 CIMMYT globally adapted genotypes (GHIST), 25 random F 3 -derived lines (RLs1), and 36 random F 3 -derived lines RLs2)-were conducted under irrigated conditions at the CIMMYT research station in northwest Mexico in three different years. Five previously developed SRI (photochemical reflectance index [PRI], water index [WI], red normalized difference vegetation index [RNDVI], green normalized difference vegetation index [GNDVI], simple ratio [SR]) and two newly calculated SRI (normalized water index-1 [NWI-1]
Method for estimation of pre-sowing soil moisture in spring crops
Method for estimation of pre-sowing soil moisture in spring crops, 2020
The pre-sowing soil moisture is a determining factor at the beginning of the growing season for spring crops. It participates in the initial stage in determining the time and amount of water needed for irrigation in an irrigation scheduling system. The publication describes a method for evaluating it based on meteorological and soil-physical information. The application of the method is illustrated with data from different locations and soils in the country.
Method for estimation of pre-sowing soil moisture of winter wheat and suitable planting dates
Method for estimation of pre-sowing soil moisture of winter wheat and suitable planting dates, 2021
The pre-sowing soil moisture is a determining factor at the beginning of the growing season for winter wheat. The publication describes a method for its estimation based on meteorological and soilphysical information. The application of the method is illustrated with data from different locations and soils in the country. Also are investigated planting dates of winter wheat grown on the territory of selected USA states, which have similar homoclimates with Bulgaria. A simple solution approach was applied for the determination of suitable planting dates by solving a general fuzzy system of linear equations with mixed fuzzy crisp explanatory variables and fuzzy unknown variable vectors.
EC92-102-A Nebraska Spring Wheat, Oats, Barley, Canola and Crambe Variety Tests 1992
This circular is a progress report of variety trials conducted by personnel of the Agronomy Department and the Northeast and Panhandle Centers and their associated agricultural laboratories. We acknowledge the State Climate Program at the University of Nebraska-Lincoln for providing the climate data used in this report. We also want to thank the Nebraska Agricultural Statistics Service for crop data. em = inches x 2. 54 ha = acres x 0.045 kg = pounds x 0.454 hl = bushels x 0.352
Within-crop variability affecting variable N application to winter wheat
In 2002-2004, the potential of four methods (N-tester, plant inorganic analyses -PIA, aerial multispectral imaging and N-sensor) for variable N application to winter wheat at BBCH 30-32 were examined in selected fields (area 26-56 ha). The largest differences were found between the N-sensor and PIA. Very similar values were observed for digital aerial imagery and the N-sensor. The N-tester measures chlorophyll content in leaves. However, it does not capture the other factors affecting N-rate assessment. PIA assesses nutrient content in plants but it does not show plant interactions in the stand. By contrast, the N-sensor and the multi-spectral camera use canopy reflectance, including interactionsandcompensationrelationshipsamongplants.
Predicting wheat maturity and stay–green parameters by modeling spectral reflectance measurements and their contribution to grain yield under rainfed conditions
Field Crops Research, 2016
The normalized difference vegetation index (NDVI) continues to provide easy and fast methodologies to characterize wheat genetic resources in response to abiotic stresses. This study identifies ways to maximize green leaf area duration during grain filling and develops NDVI models to predict physiological maturity and different stay-green parameters to increase grain yield of rainfed winter wheat under terminal drought. Three wheat populations were evaluated: one containing 240 landraces from Afghanistan, the second with 250 modern lines and varieties, tested for two years under low rainfall conditions in Turkey, and the third with 291 landraces from Central and Western Asia (grown for one year in the same location). The onset of senescence, maximum "greenness", rate of senescence and residual "greenness" at physiological maturity were estimated using sequential measurements of NDVI and have shown significant correlations with grain yield under low rainfall rainfed conditions. Trade-offs were identified among the different stay-green attributes, e.g. delayed onset of senescence and high maximum "greenness" resulted in accelerated rates of senescence and highest yields and were most evident in the landrace populations. It is concluded, that the use of rate of senescence to select for staygreen must be coupled with other stay-green components, e.g. onset of senescence or maximum "greenness" to avoid the effects of the trade-offs on final grain yield. The NDVI decay curves (using the last three NDVI measurements up to maturity) were used to estimate days to maturity using the NDVI decay during the senescence period and days to heading. A training and testing set (20 and 80% of each population, respectively) were used for calibrations allowing for correlations between predicted and observed maturity of up to r=+0.85 (P<0.0001). This procedure will facilitate large-scale wheat phenotyping in the future.
Evaluating Crops for a Flexible Summer Fallow Cropping System
Agronomy Journal, 2006
Substituting a short-season, spring-planted crop for summer fallow when soil water is sufficient at planting might reduce soil degradation without significantly increasing the risk of crop failure. The objectives of this study were to determine the relationship of crop grain or forage yield to plant available soil water at planting. The study was conducted on silt loam soils in 2004 and 2005 at Sidney, NE, and Akron, CO. A range of soil water levels was established with supplemental irrigation before planting. Four crops [spring triticale (X Triticosecale rimpaui Wittm.) for forage, dry pea (Pisum sativum L.) for grain, proso millet (Panicum miliaceum L.) for grain, and foxtail millet (Setaria italica L. Beauv.) for forage] were no-till seeded into corn (Zea mays L.) residue in a split-plot design with four replications per location. Triticale forage yield increased by 229 kg ha 21 for each centimeter of soil water available at planting in 2004. Foxtail millet forage yield and grain yield of proso millet increased by 399 kg ha 21 cm 21 and 148 kg ha 21 cm 21 , respectively, at Akron in 2004. Spring triticale, foxtail millet, and proso millet did not respond to soil water at planting in 2005, when precipitation was above the long-term average. Dry pea did not demonstrate a consistent positive response to soil water availability at planting. Soil water at planting may be a useful indicator of potential yield for selected short-season spring-planted summer crops, particularly when crop production is limited by growing season precipitation.
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