Normalized Difference Vegetation Index as a Tool for Wheat Yield Estimation: A Case Study from Faisalabad, Pakistan

For estimation of grain yield in wheat, Normalized Difference Vegetation Index (NDVI) is considered as a potential screening tool. Field experiments were conducted to scrutinize the response of NDVI to yield behavior of different wheat cultivars and nitrogen fertilization at agronomic research area, University of Agriculture Faisalabad (UAF) during the two years 2008-09 and 2009-10. For recording the value of NDVI, Green seeker (Handheld-505) was used. Split plot design was used as experimental model in, keeping four nitrogen rates (N1= 0 kg ha−1,N2= 55 kg ha−1,N3=110 kg ha−1, andN4= 220 kg ha−1) in main plots and ten wheat cultivars (Bakkhar-2001, Chakwal-50, Chakwal-97, Faisalabad-2008, GA-2002, Inqlab-91, Lasani-2008, Miraj-2008, Sahar-2006, and Shafaq-2006) in subplots with four replications. Impact of nitrogen and difference between cultivars were forecasted through NDVI. The results suggested that nitrogen treatment N4(220 kg ha−1) and cultivar Faisalabad-2008 gave maximum NDVI value (0.85) at grain filling stage among all treatments. The correlation among NDVI at booting, grain filling, and maturity stages with grain yield was positive (R2 = 0.90;R2 = 0.90;R2 = 0.95), respectively. So, booting, grain filling, and maturity can be good depictive stages during mid and later growth stages of wheat crop under agroclimatic conditions of Faisalabad and under similar other wheat growing environments in the country.

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Wheat Yield Estimation with NDVI Values Using a Proximal Sensing Tool

Remote Sensing ◽

10.3390/rs12172749 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2749

Author(s):

Marta Aranguren ◽

Ander Castellón ◽

Ana Aizpurua

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Crop Yields ◽

Wheat Yield ◽

Growing Season ◽

N Fertilization ◽

Wheat Crop ◽

Growth Stages ◽

Climate Conditions ◽

N Status

Nitrogen (N) splitting is critical to achieving high crop yields without having negative effects on the environment. Monitoring crop N status throughout the wheat growing season is key to finding the balance between crop N requirements and fertilizer needs. Three soft winter wheat fertilization trials under rainfed conditions in Mediterranean climate conditions were monitored with a RapidScan CS-45 (Holland Scientific, Lincoln, NE, USA) instrument to determine the normalized difference vegetation index (NDVI) values at the GS30, GS32, GS37, and GS65 growth stages. The threshold NDVI values in the Cezanne variety were 0.7–0.75 at the GS32, GS37, and GS65 growing stages. However, for the GS30 growing stage, a threshold value could not be established precisely. At this stage, N deficiency may not affect wheat yield, as long as the N status increases at GS32 stage and it is maintained thereafter. Following the NDVI dynamic throughout the growing season could help to predict the yields at harvest time. Therefore, the ΣNDVI from GS30 to GS65 explains about 80% of wheat yield variability. Therefore, a given yield could be achieved with different dynamics in wheat NDVI values throughout the growing cycle. The determined ranges of the NDVI values might be used for developing new fertilization strategies that are able to adjust N fertilization to wheat crop needs.

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Influence of meteorological parameters on wheat yield under different sowing conditions

MAUSAM ◽

10.54302/mausam.v73i1.5089 ◽

2022 ◽

Vol 73 (1) ◽

pp. 161-172

Author(s):

ANANTA VASHISTH ◽

DEBASISH ROY ◽

AVINASH GOYAL ◽

P. KRISHNAN

Keyword(s):

Relative Humidity ◽

Soil Temperature ◽

Air Temperature ◽

Field Experiments ◽

Wheat Yield ◽

Weather Condition ◽

Grain Filling ◽

Crop Growth ◽

Leaf Water ◽

Growth Stages

Field experiments were conducted on the research farm of IARI, New Delhi during Rabi 2016-17 and 2017-18. Three varieties of wheat (PBW-723, HD-2967 and HD-3086) were sown on three different dates for generating different weather condition during various phenological stages of crop. Results showed that during early crop growth stages soil moisture had higher value and soil temperature had lower value and with progress of crop growth stage, the moisture in the upper layer decreased and soil temperature increased significantly as compared to the bottom layers. During tillering and jointing stage, air temperature within canopy was more and relative humidity was less while during flowering and grain filling stage, air temperature within canopy was less and relative humidity was more in timely sown crop as compared to late and very late sown crop. Radiation use efficiency and relative leaf water content had significantly higher value while leaf water potential had lower value in timely sown crop followed by late and very late sown crop. Yield had higher value in HD-3086 followed by HD-2967 and PBW-723 in all weather conditions. Canopy air temperature difference had positive value in very late sown crop particularly during flowering and grain-filling stages. This reflects in the yield. Yield was more in timely sown crop as compared to late and very late sown crop.

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The effect of climatic factors on production of spring wheat quantity to quality ratio in southern Finland

Agricultural and Food Science ◽

10.23986/afsci.72929 ◽

1990 ◽

Vol 62 (3) ◽

pp. 227-236 ◽

Cited By ~ 1

Author(s):

Jari Peltonen ◽

Tuomo Karvonen ◽

Erkki Kivi

Keyword(s):

Grain Yield ◽

Spring Wheat ◽

Field Experiments ◽

Climatic Factors ◽

Wheat Yield ◽

Grain Filling ◽

Effect Of Temperature ◽

Total Precipitation ◽

Factors Affecting ◽

Dry Conditions

Interrelationships between climatic factors and spring wheat yield and quality were examined with 21 years field experiments. The formation of gluten was less at dry conditions (total precipitation under 50 mm) and total precipitation exceeded 130—140 mm. The optimum daily temperature for gluten production was some 15—17°C during grain filling. The gluten content decreased if daily minimum and maximum temperatures exceeded 11—12°C and 21—22°C, respectively. The effect of temperature and rainfall were not, however, significant in early maturing varieties. The climatic factors and grain yield did not correlate. Grain yield and protein yield had strong positive relationship, which was perhaps a consequence of supply and utilization of nitrogen. It is concluded that climatic factors affecting yield to quality ration in wheat may be excessive rains before heading and high temperature during grain filling. Interaction between weather and nitrogen are discussed to optimize correct timing of nitrogen fertilization for amount and quality of economic wheat yield.

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Dissecting Bread Wheat Heterosis through the Integration of Agronomic and Physiological Traits

Biology ◽

10.3390/biology10090907 ◽

2021 ◽

Vol 10 (9) ◽

pp. 907

Author(s):

Kevin Gimenez ◽

Pierre Blanc ◽

Odile Argillier ◽

Jean-Baptiste Pierre ◽

Jacques Le Le Gouis ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Agronomic Traits ◽

Wheat Yield ◽

Grain Filling ◽

Kernel Weight ◽

Hybrid Vigor ◽

Delayed Senescence ◽

Yield Increase ◽

Wheat Hybrids

To meet the challenge of feeding almost 10 billion people by 2050, wheat yield has to double by 2050. However, over the past 20 years, yield increase has slowed down and even stagnated in the main producing countries. Following the example of maize, hybrids have been suggested as a solution to overcome yield stagnation in wheat. However, wheat heterosis is still limited and poorly understood. Gaining a better understanding of hybrid vigor holds the key to breed for better varieties. To this aim, we have developed and phenotyped for physiological and agronomic traits an incomplete factorial design consisting of 91 hybrids and their nineteen female and sixteen male parents. Monitoring the plant development with normalized difference vegetation index revealed that 89% of the hybrids including the five higher yielding hybrids had a longer grain filling phase with a delayed senescence that results in larger grain size. This average increase of 7.7% in thousand kernel weight translated to a positive mid-parent heterosis for grain yield for 86% of hybrids. In addition, hybrids displayed a positive grain protein deviation leading to a +4.7% heterosis in protein yield. These results shed light on the physiological bases underlying yield heterosis in wheat, paving new ways to breed for better wheat hybrids.

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Monitoring agricultural drought using geospatial techniques: a case study of Thal region of Punjab, Pakistan

Journal of Water and Climate Change ◽

10.2166/wcc.2020.232 ◽

2020 ◽

Vol 11 (S1) ◽

pp. 203-216 ◽

Cited By ~ 1

Author(s):

Muhammad Amin ◽

Mobushir Riaz Khan ◽

Sher Shah Hassan ◽

Aftab Ahmad Khan ◽

Muhammad Imran ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Wheat Yield ◽

Standardized Precipitation Index ◽

Weather Conditions ◽

Agricultural Drought ◽

Wheat Crop ◽

Drought Risk ◽

Risk Map ◽

Agricultural Risk

Abstract The Thal region of Punjab often experiences dry weather conditions with extreme variability in rainfall on a spatiotemporal scale during Rabi cropping season. The current study assesses the impacts of agricultural drought on wheat crops for 2000–2015. MOD13Q1 and CHIRPS data were used for identifying and assessing variation in agricultural drought patterns and severity. Standardized Precipitation Index (SPI), Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Stress Vegetation Index (STVI) and wheat crop yield anomalies were computed to characterize the gravity of drought across the Thal region. The results indicate that the wheat Rabi cropping seasons of the years 2000–2002 experienced extreme agricultural drought, with a spatial difference in severity level causing low and poor yield, while the years 2011 and 2014 were almost normal among all the years, leaving varied impacts on wheat yield. The combined agricultural risk map was generated by integrating the agricultural and meteorological droughts severity maps. The combined risk map generated using weighted overlay analysis of all the parameters indicate that the total Thal area can be classified into slight, moderate and no drought covering 28.12, 12.76, and 59.12% respectively of the total area. Hence an agricultural risk map would be extremely helpful as a tool to guide the decision-making process for monitoring drought risk on agricultural productivity.

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Yield prediction and nitrogen recommendation in maize using normalized difference vegetation index

Agronomy Journal of Nepal ◽

10.3126/ajn.v3i0.9009 ◽

2013 ◽

Vol 3 ◽

pp. 82-88 ◽

Cited By ~ 1

Author(s):

TB Karki

Keyword(s):

Grain Yield ◽

Growth Stage ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Correlation Coefficients ◽

Growth Stages ◽

Strong Positive Correlation ◽

Positive Correlation ◽

Nutrient Levels ◽

Seed Sowing

A study was carried out using three maize genotypes with three levels of nitrogen (30 kg, 60 kg and 120 kg per hectare) during the summer season of 2010 and 2011with the aim of predicting maize (Zea mays L.) yield through the Normalized difference vegetation index (NDVI). The NDVI was recorded at different times throughout the growing season using a Greenseeker™ handheld sensor. Significant effect of genotypes and nutrient levels on the NDVI was observed at different growth stages of maize. There was positive correlation between the NDVI and grain yield. In the first season, the correlation coefficients were 0.90, 0.92, 0.76 and 0.73, respectively at 15, 45, 75 and 110 days after seeding. In the second season, the correlation coefficients were 0.80, 0.92, 0.77 and 0.75 respectively at 15, 45, 75 and 110 days after seeding. The NDVI based N calculator showed that irrespective of genotypes, yield potentials under farmers' levels of nutrient management were almost half of the recommended doses of nitrogen. The amount of N to be top dressed decreased with increased crop duration. Grain yield varied significantly due to season, genotypes and nutrient levels. NDVI was affected due to season, stages of the crop (DAS), genotypes and nutrient levels. Interaction effects were significant for season x genotype, growth stage x genotype, growth stage x nutrient levels, genotype x nutrient levels and genotype x growth stage x nutrient levels. There was a strong positive correlation between NDVI and grain yields of hybrid maize at 15 and 45 DAS, but this correlation declined thereafter. This means that N top-dressed at or after 75 days of seed sowing will not increase grain yield as significantly as N applied earlier in the season. In contrast, topdressed N was producing significant effects on the open pollinated Rampur Composite even after 75 days of seed sowing. Further confirmation of the finding could be useful for top dressing N in the maize crop. Agronomy Journal of Nepal (Agron JN) Vol. 3. 2013, Page 82-88 DOI: http://dx.doi.org/10.3126/ajn.v3i0.9009

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Using a Portable Active Sensor to Monitor Growth Parameters and Predict Grain Yield of Winter Wheat

Sensors ◽

10.3390/s19051108 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1108 ◽

Cited By ~ 14

Author(s):

Jiayi Zhang ◽

Xia Liu ◽

Yan Liang ◽

Qiang Cao ◽

Yongchao Tian ◽

...

Keyword(s):

Winter Wheat ◽

Grain Yield ◽

Vegetation Index ◽

Field Experiments ◽

Growth Parameters ◽

Leaf Nitrogen ◽

Crop Growth ◽

Nitrogen Accumulation ◽

Wheat Cultivars ◽

Area Index

Rapid and effective acquisition of crop growth information is a crucial step of precision agriculture for making in-season management decisions. Active canopy sensor GreenSeeker (Trimble Navigation Limited, Sunnyvale, CA, USA) is a portable device commonly used for non-destructively obtaining crop growth information. This study intended to expand the applicability of GreenSeeker in monitoring growth status and predicting grain yield of winter wheat (Triticum aestivum L.). Four field experiments with multiple wheat cultivars and N treatments were conducted during 2013–2015 for obtaining canopy normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) synchronized with four agronomic parameters: leaf area index (LAI), leaf dry matter (LDM), leaf nitrogen concentration (LNC), and leaf nitrogen accumulation (LNA). Duration models based on NDVI and RVI were developed to monitor these parameters, which indicated that NDVI and RVI explained 80%, 68–70%, 10–12%, and 67–73% of the variability in LAI, LDM, LNC and LNA, respectively. According to the validation results, the relative root mean square error (RRMSE) were all <0.24 and the relative error (RE) were all <23%. Considering the variation among different wheat cultivars, the newly normalized vegetation indices rNDVI (NDVI vs. the NDVI for the highest N rate) and rRVI (RVI vs. the RVI for the highest N rate) were calculated to predict the relative grain yield (RY, the yield vs. the yield for the highest N rate). rNDVI and rRVI explained 77–85% of the variability in RY, the RRMSEs were both <0.13 and the REs were both <6.3%. The result demonstrates the feasibility of monitoring growth parameters and predicting grain yield of winter wheat with portable GreenSeeker sensor.

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Hyperspectral field reflectance measurements to estimate wheat grain yield and plant height

Scientia Agricola ◽

10.1590/s0103-90162006000200004 ◽

2006 ◽

Vol 63 (2) ◽

pp. 130-138 ◽

Cited By ~ 25

Author(s):

Alexandre Cândido Xavier ◽

Bernardo Friedrich Theodor Rudorff ◽

Mauricio Alves Moreira ◽

Brummer Seda Alvarenga ◽

José Guilherme de Freitas ◽

...

Keyword(s):

Grain Yield ◽

Plant Height ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Narrow Band ◽

Broad Band ◽

Growth Stages ◽

Sensing Applications ◽

Field Reflectance ◽

Reflectance Measurements

Hyperspectral crop reflectance data are useful for several remote sensing applications in agriculture, but there is still a need for studies to define optimal wavebands to estimate crop biophysical parameters. The objective of this work is to analyze the use of narrow and broad band vegetation indices (VI) derived from hyperspectral field reflectance measurements to estimate wheat (Triticum aestivum L.) grain yield and plant height. A field study was conducted during the winter growing season of 2003 in Campinas, São Paulo State, Brazil. Field canopy reflectance measurements were acquired at six wheat growth stages over 80 plots with four wheat cultivars (IAC-362, IAC-364, IAC-370, and IAC-373), five levels of nitrogen fertilizer (0, 30, 60, 90, and 120 kg of N ha-1) and four replicates. The following VI were analyzed: a) hyperspectral or narrow-band VI (1. optimum multiple narrow-band reflectance, OMNBR; 2. narrow-band normalized difference vegetation index, NB_NDVI; 3. first- and second-order derivative of reflectance; and 4. four derivative green vegetation index); and b) broad band VI (simple ratio, SR; normalized difference vegetation index, NDVI; and soil-adjusted vegetation index, SAVI). Hyperspectral indices provided an overall better estimate of biophysical variables when compared to broad band VI. The OMNBR with four bands presented the highest R² values to estimate both grain yield (R² = 0.74; Booting and Heading stages) and plant height (R² = 0.68; Heading stage). Best results to estimate biophysical variables were observed for spectral measurements acquired between Tillering II and Heading stages.

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Prediction of crop productivity and evapotranspiration with two photosynthetic parameter regionalization methods

The Journal of Agricultural Science ◽

10.1017/s0021859612000901 ◽

2012 ◽

Vol 152 (1) ◽

pp. 119-133 ◽

Cited By ~ 3

Author(s):

S. HU ◽

X. MO

Keyword(s):

Remote Sensing ◽

Grain Yield ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Census Data ◽

Wheat Yield ◽

Ecosystem Model ◽

Crop Productivity ◽

Photosynthetic Parameter ◽

Area Index

SUMMARYParameter regionalization is the foundation for the spatial application of an ecosystem model at the canopy level and has been improved greatly by remote sensing (RS). Photosynthetic rate is restricted by the carboxylation rate, which is limited by the activity of the enzyme Rubisco. By including RS normalized difference vegetation index (NDVI) and census data of grain yield at the county level in an ecosystem model (vegetation interface processes (VIP) model), the pattern of photosynthetic parameter Vcmax (maximum catalytic activity of Rubisco) of winter wheat was obtained and then used to simulate the wheat yield and evapotranspiration (ET) in the North China Plain (referred to as the Vcmax method). To evaluate its performance, the simulated yield and ET were compared with those derived by the leaf area index (LAI) method using the retrieved LAI from NDVI to drive the VIP model. The results showed that the Vcmax method performed better than the LAI method in highly productive fields, while the LAI method described the inter-annual variations of yield more favourably in fields with low productivity. Over the study area, average yield (4520 kg/ha) and seasonal ET (360 mm) simulated by the LAI method was slightly lower than those simulated using the Vcmax method (4730 kg/ha for yield and 372 mm for ET). Compared with the census data of yield, the relative root mean square error (RMSE) of grain yield with Vcmax method (0·17) was lower than that of the LAI method (0·20). In conclusion, the physical model with spatial Vcmax pattern from remote sensing is reliable for regional crop productivity prediction.

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Spectral-temporal characterization of wheat cultivars through NDVI obtained by terrestrial sensors

Revista Brasileira de Engenharia Agrícola e Ambiental ◽

10.1590/1807-1929/agriambi.v21n11p769-773 ◽

2017 ◽

Vol 21 (11) ◽

pp. 769-773 ◽

Cited By ~ 6

Author(s):

Carlos E. V. Cattani ◽

Murilo R. Garcia ◽

Erivelto Mercante ◽

Jerry A. Johann ◽

Marcus M. Correa ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Triticum Aestivum L ◽

Growth Stages ◽

Wheat Cultivars ◽

Spectral Signatures ◽

Spectral Bands ◽

Sensing Applications ◽

Spectral Patterns ◽

Temporal Profiles

ABSTRACT Remote sensing applications in agriculture are presented as a very promising reality, but research is still needed for the correct use of spectral data. The objective of this study was to evaluate the spectral-temporal patterns of eleven wheat cultivars (Triticum aestivum L.). The experiment was conducted in Cascavel, PR, in the year 2014. With the help of the GreenSeeker and FieldSpec 4 terrestrial sensors, spectral signatures were determined and the temporal profiles of the Normalized Difference Vegetation Index (NDVI) were created. Statistical differences between wheat cultivars were analysed using analysis of variance (ANOVA) and Scott-Knott test. Grain yields obtained with INSEY (In-Season Estimate of Yield) factors were correlated. NDVI normalized by degree-days accumulated from the Feekes growth stages 2 and 8 showed to be more consistent in the estimation of grain yield, explaining approximately 70% of the variation. At the Feekes stage 10.1, wheat cultivars presented different spectral patterns in the near and medium infrared bands. This suggests that these spectral bands can be used to differentiate wheat cultivars.

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