Aggregating field-scale knowledge into farm-scale models of African smallholder systems: Summary functions to simulate crop production using APSIM

Designing or improving farming systems requires understanding their dynamics so as to predict their behaviour in response to management. Simulation tools can potentially support the process by which farmers and scientists might obtain such an encompassing understanding. The usability of these tools is, however, partially inhibited by the inherent complexity of the interactions at work in farm-scale models. Whereas such models are generally used in isolation, here we present an approach in which a field-scale diagnosis method complements a farm-scale simulation model. This diagnosis method lends itself easily to an intelligible presentation of field-specific knowledge that can be fed to the simulation tool for more encompassing considerations. Our approach is used to support the design of novel management strategies in grassland-based beef systems and proved to be effective when applied to two farms in the French Pyrenees. Thanks to the integrative representation of the various processes, including the management ones, simulation contributed to deeper learning of both scientists and farmers about room for manoeuvre for increasing self-sufficiency for forage. The diagnosis phase enhanced the learning process by providing a simpler framework in which elementary problems at field scale could be considered separately before being examined concurrently at farm scale in the simulation phase.

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Improving Soybean Production Using Light Supplementation at Field-Scale: A Case Study

Journal of Agricultural Studies ◽

10.5296/jas.v9i3.18890 ◽

2021 ◽

Vol 9 (3) ◽

pp. 259

Author(s):

Ernane M Lemes ◽

Breno N R Azevedo ◽

Matheus F I Domiciano ◽

Samuel L Andrade

Keyword(s):

Grain Yield ◽

Plant Height ◽

Crop Production ◽

High Efficiency ◽

Field Scale ◽

Soybean Crop ◽

Illumination System ◽

Progress Curve ◽

Commercial Area ◽

Yield Responses

In modern agriculture, there is a growing need for increasing crop efficiency while minimizing environmental impacts. The use of high-efficiency light supplementation to enhance plant development is limited for high-productive crops at field conditions (outdoor). This study evaluated the soybean plant’s yield responses in an open commercial area (field scale) cultivated under conditions of artificial light supplementation. A commercial irrigated (pivot) area received an illumination system for light supplementation (LS) in its inner pivot spans. About 40 hours of LS were applied to the plants during the soybean crop cycle. The area’s outer pivot spans did not receive light supplementation (nLS). The internode number, the plant height, the pods per plant were evaluated weekly to compute the area under the progress curve (AUPC). The grain yield at harvest was also assessed. The AUPC of the internode number, plant height and pods per plant were positively affected by the LS treatment. The regular soybean cycle (nLS) is about 17 weeks; however, the LS harvest occurred three weeks later. Light supplementation increased soybean grain yield by 57.3% and profitability by 180% when compared to nLS. Although light supplementation at field scale poses a challenge, it is now affordable since sustainable field resistant technologies are now available. The present study is the first known report of light supplementation used to improve soybean crop production at field scale.

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Predicting Wheat Yield at the Field Scale by Combining High-Resolution Sentinel-2 Satellite Imagery and Crop Modelling

Remote Sensing ◽

10.3390/rs12061024 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1024 ◽

Cited By ~ 6

Author(s):

Yan Zhao ◽

Andries B Potgieter ◽

Miao Zhang ◽

Bingfang Wu ◽

Graeme L Hammer

Keyword(s):

High Resolution ◽

Crop Production ◽

Vegetation Index ◽

Wheat Yield ◽

Crop Model ◽

Stress Index ◽

Yield Prediction ◽

Field Scale ◽

Crop Water Stress Index ◽

Sentinel 2

Accurate prediction of crop yield at the field scale is critical to addressing crop production challenges and reducing the impacts of climate variability and change. Recently released Sentinel-2 (S2) satellite data with a return cycle of five days and a high resolution at 13 spectral bands allows close observation of crop phenology and crop physiological attributes at field scale during crop growth. Here, we test the potential for indices derived from S2 data to estimate dryland wheat yields at the field scale and the potential for enhanced predictability by incorporating a modelled crop water stress index (SI). Observations from 103 study fields over the 2016 and 2017 cropping seasons across Northeastern Australia were used. Vegetation indices derived from S2 showed moderately high accuracy in yield prediction and explained over 70% of the yield variability. Specifically, the red edge chlorophyll index (CI; chlorophyll) (R2 = 0.76, RMSE = 0.88 t/ha) and the optimized soil-adjusted vegetation index (OSAVI; structural) (R2 = 0.74, RMSE = 0.91 t/ha) showed the best correlation with field yields. Furthermore, combining the crop model-derived SI with both structural and chlorophyll indices significantly enhanced predictability. The best model with combined OSAVI, CI and SI generated a much higher correlation, with R2 = 0.91 and RMSE = 0.54 t/ha. When validating the models on an independent set of fields, this model also showed high correlation (R2 = 0.93, RMSE = 0.64 t/ha). This study demonstrates the potential of combining S2-derived indices and crop model-derived indices to construct an enhanced yield prediction model suitable for fields in diversified climate conditions.

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Silica fertilization improved wheat performance and increased phosphorus concentrations during drought at the field scale

Scientific Reports ◽

10.1038/s41598-021-00464-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jörg Schaller ◽

Eric Scherwietes ◽

Lukas Gerber ◽

Shrijana Vaidya ◽

Danuta Kaczorek ◽

...

Keyword(s):

Soil Moisture ◽

Crop Production ◽

Terrestrial Ecosystem ◽

Fertilizer Application ◽

Plant Performance ◽

Phosphorus Concentration ◽

Phosphorus Fertilizer ◽

Field Scale ◽

Promising Tool ◽

The Future

AbstractDrought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.

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Carbon stocks of a Rhodic Ferralsol under no-tillage in Southern Brazil: spatial variability at a farm scale

Soil Research ◽

10.1071/sr08140 ◽

2009 ◽

Vol 47 (3) ◽

pp. 253

Author(s):

P. L. O. A. Machado ◽

A. C. C. Bernardi ◽

L. I. Ortiz Valencia ◽

M. S. P. Meirelles ◽

C. A. Silva ◽

...

Keyword(s):

Organic Carbon ◽

Spatial Variability ◽

Crop Production ◽

Winter Season ◽

Triticum Aestivum L ◽

Soil Mass ◽

No Tillage ◽

Farm Scale ◽

Glycine Max L ◽

Grid Nodes

The objective of this study was to determine, at a farm level, the spatial variability of organic carbon stock (CS) at different depths on a field of 1 soil type in long-term (13-year) crop production under no-tillage. The crop rotation comprised soybean [Glycine max (L.) Merr.] alternating with maize (Zea mays L.) in the summer season. For the winter season, wheat (Triticum aestivum L.) was cropped in rotation with black oat (Avena sativa L.), a cover crop. The 12.5-ha field was sampled at a density of 6.25 samples/ha. Within the coarse grid, 2 dense grids with 20-, 10-, and 5-m spacing were established. Soil samples were collected at all grid nodes and analysed for soil organic carbon and bulk density. The CS at 0–0.05, 0.05–0.10, and 0.10–0.20 m was corrected for equal soil mass. Geostatistics was used for the estimation of spatial distribution of CS at 3 soil depths. We found that CS variation was low to medium (CV 6.7–19.4%). The variograms of CS at all depths were best fitted by spherical models and showed ranges of 120 m, except at 0–0.05 m (range 109 m). At 0–0.20 m depth, CS was 15.2–24.5 t/ha (CV 8.2%, range 120 m). The use of geostatistics reveals a powerful tool for the spatial estimation of CS at depth of a Rhodic Ferralsol under no-tillage, and demonstrated CS variation on a 12.5-ha area, even though soil and crop management were the same for >10 years.

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Estimating UK perennial energy crop supply using farm-scale models with spatially disaggregated data

GCB Bioenergy ◽

10.1111/gcbb.12121 ◽

2013 ◽

Vol 6 (2) ◽

pp. 142-155 ◽

Cited By ~ 26

Author(s):

Peter Alexander ◽

Dominic Moran ◽

Pete Smith ◽

Astley Hastings ◽

Shifeng Wang ◽

...

Keyword(s):

Energy Crop ◽

Scale Models ◽

Farm Scale ◽

Disaggregated Data

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Farm-scale models built with farmers converting and converted to organic farming

Agronomy for Sustainable Development ◽

10.1007/s13593-012-0125-6 ◽

2012 ◽

Vol 33 (3) ◽

pp. 609-619

Author(s):

Lucie Gouttenoire ◽

Sylvie Cournut ◽

Stéphane Ingrand

Keyword(s):

Organic Farming ◽

Scale Models ◽

Farm Scale

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Evaluating the capabilities of watershed-scale models in estimating sediment yield at field-scale

Journal of Environmental Management ◽

10.1016/j.jenvman.2013.05.018 ◽

2013 ◽

Vol 127 ◽

pp. 228-236 ◽

Cited By ~ 15

Author(s):

Andrew R. Sommerlot ◽

A. Pouyan Nejadhashemi ◽

Sean A. Woznicki ◽

Subhasis Giri ◽

Michael D. Prohaska

Keyword(s):

Sediment Yield ◽

Watershed Scale ◽

Field Scale ◽

Scale Models

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Improving Soybean Production Under Light Supplementation at Field - A Case Study

10.21203/rs.3.rs-111347/v1 ◽

2020 ◽

Author(s):

Ernane Lemes ◽

Breno Azevedo ◽

Matheus Domiciano ◽

Samuel Andrade

Keyword(s):

Plant Height ◽

Crop Production ◽

High Efficiency ◽

Light Regulation ◽

Soybean Plant ◽

Field Scale ◽

Soybean Crop ◽

Progress Curve ◽

Commercial Area ◽

Yield Responses

Abstract In modern agriculture, there is a growing need for cropping efficiency e low environmental impacts. Diverse technologies are becoming available in a recent wave of modernization and integration of knowledge. The use of high-efficiency light supplementation to plant development is scarce to high-productive crops at field conditions (outdoor). The objectives of this study were to evaluate soybean plant and yield responses in an open commercial area (field scale) cultivated with artificial light supplementation. A commercial irrigated (pivot) area received an illumination system for light supplementation (LS) in the inner pivot spans. The light applied was a composition of blue, green and red bands. The outer pivot spans did not receive light supplementation (nLS). About 40 hours of LS were applied to the plants during the soybean crop cycle. Internode number, plant height, pods per plant were weekly evaluated to compose the area under the progress curve (AUPC). The grain yield was also evaluated at harvest. Analysis of variance and test of averages were used to evaluate the data. The AUPC of the internode number, plant height and pods per plant were 15.6, 23.3 and 25.3% higher than for the LS treatment. The regular soybean cycle (nLS) was about 17 weeks; however, the harvest of the LS treatment happened three weeks later. The grain productivity of the nLS was about 4,500 kg ha-1 (75 bags), and of the LS treatment was about 7,080 kg ha-1 (118 bags) - 57.3% superior. Light supplementation at field scale is a challenge; however, affordable and field resistant technologies are now accessible. The present study is the first report of light supplementation used to improve soybean crop production at field scale. The possibility of using light regulation as an additional technique for increasing yields and sustainable production are also discussed.

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Nitrate-N in the Soil Profiles of Long-term Field Experiments

Agrokémia és Talajtan ◽

10.1556/agrokem.51.2002.1-2.17 ◽

2002 ◽

Vol 51 (1-2) ◽

pp. 139-146 ◽

Cited By ~ 1

Author(s):

É. Bircsák ◽

Tamás Németh

Keyword(s):

Crop Production ◽

Field Experiments ◽

N Fertilization ◽

Point Of View ◽

Soil Profiles ◽

Mineral N ◽

N Content ◽

Farm Scale ◽

Additional Costs

Long-term N fertilization experiments were established with identical treatments at two different growing areas in Hungary: one on a calcareous sandy soil (Őrbottyán) and the other on a calcareous chernozem soil (Nagyhörcsök). The aim was to create differences in mineral-N content in the soil profiles in order to determine their N supplying capacity and to establish whether the accumulated nitrate may be regarded as a supply index for crop production. The results showed that under certain environmental conditions N may accumulate in the soil profile in the form of nitrate, resulting from N fertilization in previous years, to such an extent that it must be taken into consideration when determining the fertilizer rates to be applied. This is important not only from the point of view of economical management and environment protection, but also for reaching better yield quality. The calculations can be reliably performed if they are based on the measurement and calibration of the soil's mineral-N content. The environmental importance of such calibration experiments is that by estimating the utilization of N from the mineral-N pool, the additional costs incurred due to over-fertilization can be eliminated, and at the same time the potential danger of NO 3 leaching to the groundwater can be reduced. Extrapolation of the experimental results to farm scale can lead to both economical and environmental achievements.

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