scholarly journals Soil Water Content and High-Resolution Imagery for Precision Irrigation: Maize Yield

Agronomy ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 174 ◽  
Author(s):  
Alfonso de Lara ◽  
Louis Longchamps ◽  
Raj Khosla
Keyword(s):  
Remote Sensing ◽  
Grain Yield ◽  
Soil Water ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Maize Yield ◽  
Maize Grain Yield ◽  
Use Efficiency ◽  
Maize Grain ◽  
Precision Irrigation

Improvement in water use efficiency of crops is a key component in addressing the increasing global water demand. The time and depth of the soil water monitoring are essential when defining the amount of water to be applied to irrigated crops. Precision irrigation (PI) is a relatively new concept in agriculture, and it provides a vast potential for enhancing water use efficiency, while maintaining or increasing grain yield. Neutron probes (NPs) have consistently been used as a robust and accurate method to estimate soil water content (SWC). Remote sensing derived vegetation indices have been successfully used to estimate variability of Leaf Area Index and biomass, which are related to root water uptake. Crop yield has not been evaluated on a basis of SWC, as explained by NPs in time and at different depths. The objectives of this study were (1) to determine the optimal time and depth of SWC and its relationship to maize grain yield (2) to determine if satellite-derived vegetation indices coupled with SWC could further improve the relationship between maize grain yield and SWC. Soil water and remote sensing data were collected throughout the crop season and analyzed. The results from the automated model selection of SWC readings, used to assess maize yield, consistently selected three dates spread around reproductive growth stages for most depths (p value < 0.05). SWC readings at the 90 cm depth had the highest correlation with maize yield, followed closely by the 120 cm. When coupled with remote sensing data, models improved by adding vegetation indices representing the crop health status at V9, right before tasseling. Thus, SWC monitoring at reproductive stages combined with vegetation indices could be a tool for improving maize irrigation management.

Effect of In-Season Nitrogen Management Strategy on Maize Grain Yield and Nitrogen Use Efficiency

2011 ◽  
Vol 37 (1) ◽  
pp. 152-157 ◽  
Author(s):  
You-Liang YE ◽  
Yu-Fang HUANG ◽  
Chun-Sheng LIU ◽  
Ri-Tao QU ◽  
Hai-Yan SONG ◽  
...  
Keyword(s):  
Grain Yield ◽  
Nitrogen Use Efficiency ◽  
Management Strategy ◽  
Nitrogen Management ◽  
Nitrogen Use ◽  
Maize Grain Yield ◽  
Use Efficiency ◽  
Maize Grain

scholarly journals Improvement of Maize Productivity and N Use Efficiency in a No-Tillage Irrigated Farming System: Effect of Cropping Sequence and Fertilization Management

Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1459
Author(s):  
Heba S. A. Salama ◽  
Ali I. Nawar ◽  
Hassan E. Khalil ◽  
Ahmed M. Shaalan
Keyword(s):  
Grain Yield ◽  
Faba Bean ◽  
Farming System ◽  
No Tillage ◽  
Maize Crop ◽  
Egyptian Clover ◽  
Maize Grain Yield ◽  
Use Efficiency ◽  
Maize Grain ◽  
N Use

The sequence of the preceding crops in a no-tillage farming system, could interact with the integrated use of mineral and organic nitrogen (N) sources in a way that improves the growth and productivity of the terminal maize crop, meanwhile, enhancing its N use efficiency (NUE). In the current study, six legume-cereal crop sequences, including faba bean, soybean, Egyptian clover, wheat, and maize were evaluated along two experimental rotations that ended up by planting the terminal maize crop. In addition, the effects of applying variable mineral nitrogen (MN) rates with and without the incorporation of farmyard manure (FYM) on the productive performance of maize and its NUE were tested. The field experiments were conducted in a no-tillage irrigated farming system in Northern Egypt, a location that is characterized by its arid, Mediterranean climate. Results revealed that increasing the legume component in the evaluated crop sequences, up to 75%, resulted in improved maize ear leaf area, 1000-grain weight, and harvest index, thus, a higher final grain yield, with the inclusion of Egyptian clover was slightly better than faba bean. Comparing the crop sequences with 50% legume contribution uncovered the positive effects of soybean preceding crop on the terminal maize crop. Substituting 25% of the applied MN with FYM resulted in similar maize yields to the application of the equivalent 100% MN rates. The fertilizer treatments significantly interacted with the crop sequences in determining the maize grain yield, where the highest legume crop contribution in the crop sequence (75%) equalized the effects of the different fertilizer treatments on maize grain yield. The integrated use of FYM with MN in maize fertilization improved the NUE compared to the application of MN alone. Comparing fertilization treatments with similar MN content, with and without FYM, revealed that the difference in NUE was attributed to the additional amount of FYM. In similar conditions to the current study, it is recommended to grow faba bean two years before maize, while Egyptian clover could be grown directly preceding maize growth, with frequent inclusion of soybean in the sequence, this could be combined with the application of an average of 200 kg MN ha−1 in addition to FYM.

scholarly journals Associations Between Different Soil Management Practices, Soil Fauna and Maize Yield

2018 ◽  
Vol 10 (9) ◽  
pp. 333 ◽  
Author(s):  
Ana Luiza Privado Martins ◽  
Glécio Machado Siqueira ◽  
Emanoel Gomes de Moura ◽  
Raimunda Alves Silva ◽  
Anágila Janenis Cardoso Silva ◽  
...  
Keyword(s):  
Humic Acid ◽  
Grain Yield ◽  
Management Practices ◽  
Soil Fauna ◽  
Block Design ◽  
Soil Management ◽  
Maize Yield ◽  
Maize Grain Yield ◽  
Wiener Diversity Index ◽  
Maize Grain

Soil fauna play an important role in ecosystems, and in this context, it is important to better understand how the abiotic and biotic drivers of these organisms interact. We hypothesize that soil fauna are affected by different soil management practices, which has an influence on maize grain yields. The aim of this study was to evaluate the structure of soil fauna under different soil management practices and their associations with maize grain yield. The experiment was conducted in Maranhão, Brazil, in an area divided into 24 plots of 4 × 10 m in a randomized block design with six treatments with four replicates (R). Pitfall traps were placed in the area. The treatments were Leucaena leucocephala-Leucaena (L), nitrogen (N), humic acid + nitrogen (HA + N), nitrogen + Leucaena (N + L), humic acid + Leucaena (HA + L) and humic acid + nitrogen + Leucaena (HA + N + L). The soil fauna dominance, abundance, richness, Shannon-Wiener diversity index, Pielou evenness index and maize grain yield were determined. Formicidae was clearly affected by management with Leucaena, while Coleoptera was affected by management with nitrogen. Despite this, Isopoda and Diplura were the only groups associated with the maize yield. Although fauna abundance did not differ among treatments, it was related to the yield. This study confirms that the abundance and some taxa of soil fauna can influence yield and that these organisms can be used to increase agricultural sustainability.

MAIZE GRAIN YIELD RESPONSE TO THE DISTANCE NITROGEN IS PLACED AWAY FROM THE ROW

2012 ◽  
Vol 49 (1) ◽  
pp. 3-18 ◽  
Author(s):  
E. RUTTO ◽  
J. P. VOSSENKEMPER ◽  
J. KELLY ◽  
B. K. CHIM ◽  
W. R. RAUN
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Maize Yield ◽  
Yield Response ◽  
Rainfall Distribution ◽  
Maize Grain Yield ◽  
General Decline ◽  
Study Results ◽  
Maize Grain ◽  
N Rates

SUMMARYCorrect placement of side dress nitrogen (N) fertilizer could increase nitrogen use efficiency (NUE) and maize yield production. Field studies were established to evaluate application of midseason (V8 to V10), variable liquid urea ammonia nitrate (28%), N rates (0, 45, 90 and 134 kg N ha−1) and different application distances (0, 10, 20 and 30 cm) away from the maize row on grain yield and NUE at Haskell and Hennessey in 2009, Efaw in 2010 and Lake Carl Blackwell, Oklahoma in 2009 and 2010. A randomized complete block design with three replications was used throughout the study. Results indicated that maize grain yield in sites with adequate rainfall increased significantly (p < 0.05) with N rate, and poor N response was recorded in sites with low rainfall. Across sites and seasons, varying side dress N application distance away from the maize row did not significantly (p < 0.05) influence maize grain yield and NUE even with no prep-plant applied. Environments with adequate rainfall distribution had better maize grain yields when high side dress N rates (90 and 134 kg N ha−1) were applied 0 to 10 cm, and a higher NUE when 45 kg N ha−1 was applied 0 to 20 cm away from the maize row. For low N rates (45 kg N ha−1), increased maize grain yield and NUE were achieved when side dress N was applied 0 to 20 cm away from the maize row at locations with low rainfall distribution. Across sites and seasons, increasing side dress N to 134 kg N ha−1 contributed to a general decline in mean NUE to as low as 4%, 35%, 10%, 51% at Hennessey, Efaw, LCB (2009) and LCB (2010) respectively.

Management of Cogongrass (Imperata cylindrica) with Velvetbean (Mucuna pruriens var. utilis) and Herbicides

1999 ◽  
Vol 13 (2) ◽  
pp. 201-208 ◽  
Author(s):  
Udensi E. Udensi ◽  
I. Okezie Akobundu ◽  
Albert O. Ayeni ◽  
David Chikoye
Keyword(s):  
Grain Yield ◽  
Field Experiments ◽  
Maize Yield ◽  
Imperata Cylindrica ◽  
Mucuna Pruriens ◽  
Maize Grain Yield ◽  
Maize Grain ◽  
Herbicide Effects ◽  
Density And Biomass ◽  
Annual Weeds

Field experiments were conducted in 1992 to 1993 and in 1995 to 1996 in Ibadan, Nigeria, to assess the effect of velvetbean and herbicides on maize (corn) and cogongrass growth and to assess regrowth of the weed 1 yr after treatment. In 1992 and 1995 cover cropping with velvetbean and imazapyr and glyphosate application reduced cogongrass density as much as the handweeded control. The smothering effect of velvetbean was equivalent to that of glyphosate at 1.8 kg/ha but was less than imazapyr even at the lowest rate of 0.5 kg/ha. Addition of adjuvant did not improve the efficacy of either herbicide. Maize grain yield was higher in velvetbean plots than in fallow plots dominated by cogongrass. Velvetbean and herbicide effects on cogongrass 1 yr later (1993 and 1996) followed a similar trend as observed in the year of application. Annual weed density was highest in glyphosate plots, followed by imazapyr, and least in plots previously seeded to velvetbean. Maize grain yield was higher in herbicide plots (average yield of 3,170 and 1,920 kg/ha in 1993 and 1996, respectively) than in velvetbean plots (2,800 to 1,180 kg/ha in 1993 and 1996, respectively) and handweeded plots (2,890 and 723 kg/ha in 1993 and 1996, respectively). In 1996 the lowest maize yield was in handweeded plots without velvetbean, suggesting that weeding four times suppressed cogongrass density and biomass, but was not sufficient to minimize the subsequent competition from annual weeds. Uncontrolled cogongrass reduced maize yield to zero. These studies suggest that planting velvetbean for cogongrass control may be a better alternative for farmers without the resources to purchase herbicides.

Increased Maize Yields through the Transdisciplinary Process with Site Specific Fertilizer Recommendation in Small Holder Farms in Uasin Gishu County, Kenya

2019 ◽  
pp. 1-10
Author(s):  
Arusey Chebet ◽  
Otinga A. Nekesa ◽  
Wilson Ng’etich ◽  
Ruth Njoroge ◽  
Roland W. Scholz ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Grain Yield ◽  
Maize Yield ◽  
Soil Testing ◽  
Site Specific ◽  
Maize Grain Yield ◽  
Significant Difference ◽  
Fertilizer Recommendations ◽  
Maize Yields ◽  
Maize Grain

The objective of this study was to evaluate the effects of site-specific fertilizer recommendations on maize yield using the transdisciplinary (TD) process. 144 farmers participated in the study for the two seasons. Experiments were laid on the farmers’ fields at four sites (Kapyemit, Kipsomba, Ngenyilel and Ziwa, in Uasin Gishu County) using Randomized Complete Block Design in a 3 x 2 factorial arrangement. Treatments included farmers who participated in the TD process (TD2) and those who did not (TD1) in using the interventions for soil fertility improvement which were farmer own practices (ST1); farmers who applied government recommendations (ST2), and site-specific fertilizer recommendations (ST3) which was based on soil testing results. The Data collected was the dry weights of maize which were measured at the end of the seasons and subjected to Analysis of Variance using Genstat 14th edition. Means separation was done using Fischer’s unprotected Least Significant Difference.. There was a significant effect on maize yields by soil testing and participation in TD process p = 0.01. The mean maize grain yield for season one was 5.43 ton ha-1 while for season two was 5.73 ton ha-1. Control farmers (TD1) maize grain yield of 5.27 ton ha-1, had a significant difference (p = 0.05) from the yield of participating farmers (TD2) who had 5.96 ton ha-1. Maize grain yield was increased by the application of site specific fertilizer recommendations which gave an overall mean of 6.57 ton ha-1 for season one and 6.56 ton ha-1 for season two. Following (ST3) recommendations and participation in the TD process, improved soil nutrient content thus maize yield increased. We recommend soil testing and consequent site-specific fertilizer recommendations for any initiative in managing soil fertility.

scholarly journals Lime, manure and Inorganic Fertilizer Effects on Soil Chemical Properties, Maize Yield and Profitability in Acidic Soils in Central Highlands of Kenya

2021 ◽  
pp. 40-51
Author(s):  
W. Winnie Kimiti ◽  
M. W. Mucheru-Muna ◽  
J. N. Mugwe ◽  
K. F. Ngetich ◽  
M. N. Kiboi ◽  
...  
Keyword(s):  
Grain Yield ◽  
Chemical Properties ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
Inorganic Fertilizer ◽  
Soil Chemical Properties ◽  
Fertilizer Treatment ◽  
Acidic Soils ◽  
Maize Grain Yield ◽  
Maize Grain

In Sub-Saharan Africa (SSA), acidic soil covers 29% of the total area. About 13% of the Kenyan total land area has acidic soils, widely distributed in croplands of the central and western Kenyan regions. The high soil acidity, coupled with soil nutrient depletion, negatively affects crop productivity in the region. We conducted an on-farm experiment to determine the effect of lime, manure, and phosphatic fertilizer application, either solely or combined, on soil chemical properties, maize yield, and profitability in acidic soils of Tharaka Nithi County, Kenya. The treatments were different rates of manure, lime, and P fertilizer. The experiment was designed as a randomized complete block design replicated ten times in farmer’s fields. Soil sampling was done at a depth of 0-20 cm prior to the start of the experiment, after crop harvest of SR2016 and LR2017 seasons. The samples were analyzed in the laboratory following standard methods. Results showed that lime significantly increased soil pH by 10.6% during the SR2016 and by 17.7% during the LR2017. Similarly, treatments with lime reduced exchangeable acidity and increased soil available P. Treatments with inorganic fertilizers had significantly higher maize grain yield in comparison with treatments with the sole application of lime, manure, and lime + manure. Lime + fertilizer + manure treatment gave the highest average maize grain yield (5.1 t ha−1), while control gave the lowest (1.5 t ha−1) during the LR2017 season. Economic returns were low due to the prevailing low rainfall experienced during the study period during the SR2016 season. Lime combined with inorganic fertilizer treatment recorded the highest returns (128.75 USD ha-1) followed by sole inorganic fertilizer (105.94 USD ha-1) during the LR2017 season. The study recommends a combination of both lime and inorganic fertilizer for enhanced maize production and profitability in Tharaka-Nithi County, Kenya.

scholarly journals Determining nitrogen deficiencies for maize using various remote sensing indices

2022 ◽  
Author(s):  
Brayden W. Burns ◽  
V. Steven Green ◽  
Ahmed A. Hashem ◽  
Joseph H. Massey ◽  
Aaron M. Shew ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Grain Yield ◽  
Nitrogen Fertilizer ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Nitrogen Deficiency ◽  
Maize Grain Yield ◽  
Nitrogen Inputs ◽  
Chlorophyll Index ◽  
Maize Grain

AbstractDetermining a precise nitrogen fertilizer requirement for maize in a particular field and year has proven to be a challenge due to the complexity of the nitrogen inputs, transformations and outputs in the nitrogen cycle. Remote sensing of maize nitrogen deficiency may be one way to move nitrogen fertilizer applications closer to the specific nitrogen requirement. Six vegetation indices [normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), red-edge normalized difference vegetation index (RENDVI), triangle greenness index (TGI), normalized area vegetation index (NAVI) and chlorophyll index-green (CIgreen)] were evaluated for their ability to detect nitrogen deficiency and predict grain maize grain yield. Strip trials were established at two locations in Arkansas, USA, with nitrogen rate as the primary treatment. Remote sensing data was collected weekly with an unmanned aerial system (UAS) equipped with a multispectral and thermal sensor. Relationships among index value, nitrogen fertilizer rate and maize growth stage were evaluated. Green NDVI, RENDVI and CIgreen had the strongest relationship with nitrogen fertilizer treatment. Chlorophyll Index-green and GNDVI were the best predictors of maize grain yield early in the growing season when the application of additional nitrogen was still agronomically feasible. However, the logistics of late season nitrogen application must be considered.

scholarly journals LINKING PHOTOSYNTHETIC LIGHT USE EFFICIENCY AND OPTICAL VEGETATION ACTIVE INDICATORS: IMPLICATIONS FOR GROSS PRIMARY PRODUCTION ESTIMATION BY REMOTE SENSING

2020 ◽  
Vol V-3-2020 ◽  
pp. 571-578
Author(s):  
S. Wang ◽  
Z. Li ◽  
Y. Zhang ◽  
D. Yang ◽  
C. Ni
Keyword(s):  
Remote Sensing ◽  
Primary Productivity ◽  
Seasonal Changes ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Canopy Structure ◽  
Remote Sensing Data ◽  
Growing Season ◽  
Light Use Efficiency ◽  
Use Efficiency

Abstract. Over the last 40 years, the light use efficiency (LUE) model has become a popular approach for gross primary productivity (GPP) estimation in the carbon and remote sensing communities. Despite the fact that the LUE model provides a simple but effective way to approximate GPP at ecosystem to global scales from remote sensing data, when implemented in real GPP modelling, however, the practical form of the model can vary. By reviewing different forms of LUE model and their performances at ecosystem to global scales, we conclude that the relationships between LUE and optical vegetation active indicators (OVAIs, including vegetation indices and sun-induced chlorophyll fluorescence-based products) across time and space are key for understanding and applying the LUE model. In this work, the relationships between LUE and OVAIs are investigated at flux-tower scale, using both remotely sensed and simulated datasets. We find that i) LUE-OVAI relationships during the season are highly site-dependent, which is complexed by seasonal changes of leaf pigment concentration, canopy structure, radiation and Vcmax; ii) LUE tends to converge during peak growing season, which enables applying pure OVAI-based LUE models without specifically parameterizing LUE and iii) Chlorophyll-sensitive OVAIs, especially machine-learning-based SIF-like signal, exhibits a potential to represent spatial variability of LUE during the peak growing season.We also show the power of time-series model simulations to improve the understanding of LUE-OVAI relationships at seasonal scale.

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