Systematic literature review of implementations of precision agriculture

Cisternas, Isabel; Velásquez, Ignacio; Caro, Ángélica; Rodríguez, Alfonso Sánchez

doi:10.1016/j.compag.2020.105626

Cited by 195 publications

(105 citation statements)

References 30 publications

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“…In this study, we leveraged the potential of ATR-FTIR spectroscopy to investigate the effects of different tillage methods and nitrogen fertilization levels on the biochemical composition of durum wheat leaves and caryopses. In fact, a deeper knowledge of plant composition and needs, in relation with the crop phenological stage, could be used to provide the correct type, amount and spatial position of fertilizer using site-specific management (SSM) technology, which is the most popular precision agriculture application [32]. The use of SSM can provide several positive effects such as balancing and stabilizing soil nutrients, producing better economic income for the farmer and improving the soil fertility and sustainability indicators [33].…”

Section: Discussionmentioning

confidence: 99%

A Spectroscopic Approach to Evaluate the Effects of Different Soil Tillage Methods and Nitrogen Fertilization Levels on the Biochemical Composition of Durum Wheat (Triticum turgidum subsp. durum) Leaves and Caryopses

et al. 2021

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The agricultural sector is required to produce food at the same pace as population growth, while accounting for pollution and costs. For this reason, conservative agricultural practices have been employed worldwide. Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy has the ability to provide a snapshot of the macromolecular composition of a sample in a timely and cost-effective way and it has been widely applied in the field of agriculture to assess food quality. The aim of this study was to exploit ATR-FTIR spectroscopy to assess the impact of different soil tillage methods (conventional tillage, CT; minimum tillage, MT, and no tillage, NT) and nitrogen fertilization levels (0, 90 and 180 kg N ha−1) on the macromolecular composition of leaves and caryopses of durum wheat (Triticum turgidum subsp. durum). The analysis of the spectral data revealed that the quality of durum wheat, in terms of protein content, grown on soil with no tillage was not reduced. Indeed, with regards to caryopses, the different tillage methods influenced only the lipid and hemicellulose content, whereas the macromolecular composition of leaves was sensitive to tillage methods mostly during the early stage of growth. Moreover, no relevant effects were found in leaves and caryopses when different fertilizer concentrations were used. These results provide important knowledge supporting the adoption of both no-tillage soil treatments and reduced fertilization dosage for the development of durum wheat management strategies and support the use of spectroscopy for conservative agriculture practices.

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Section: Discussionmentioning

confidence: 99%

A Spectroscopic Approach to Evaluate the Effects of Different Soil Tillage Methods and Nitrogen Fertilization Levels on the Biochemical Composition of Durum Wheat (Triticum turgidum subsp. durum) Leaves and Caryopses

et al. 2021

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“…Advancements in remote sensing platforms, including the use of UASs equipped with multispectral sensors, now allow for within-field yield estimation, which in turn can be managed to improve overall farm productivity [4,5]. Sensors onboard UASs are typically passive sensors, i.e., sensors that capture electromagnetic energy emanating from an independent source and reflecting from of a crop/soil (depending on field coverage driven by growth stage of the crop).…”

Section: Introductionmentioning

confidence: 99%

Corn Grain Yield Prediction and Mapping from Unmanned Aerial System (UAS) Multispectral Imagery

et al. 2021

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Harvester-mounted yield monitor sensors are expensive and require calibration and data cleaning. Therefore, we evaluated six vegetation indices (VI) from unmanned aerial system (Quantix™ Mapper) imagery for corn (Zea mays L.) yield prediction. A field trial was conducted with N sidedress treatments applied at four growth stages (V4, V6, V8, or V10) compared against zero-N and N-rich controls. Normalized difference vegetation index (NDVI) and enhanced vegetation index 2 (EVI2), based on flights at R4, resulted in the most accurate yield estimations, as long as sidedressing was performed before V6. Yield estimations based on earlier flights were less accurate. Estimations were most accurate when imagery from both N-rich and zero-N control plots were included, but elimination of the zero-N data only slightly reduced the accuracy. Use of a ratio approach (VITrt/VIN-rich and YieldTrt/YieldN-rich) enables the extension of findings across fields and only slightly reduced the model performance. Finally, a smaller plot size (9 or 75 m2 compared to 150 m2) resulted in a slightly reduced model performance. We concluded that accurate yield estimates can be obtained using NDVI and EVI2, as long as there is an N-rich strip in the field, sidedressing is performed prior to V6, and sensing takes place at R3 or R4.

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“…New land use techniques such as precision agriculture [81], i.e., any form of agriculture that changes conventions by utilizing new technologies, are expected in the future. As Stafford [82] suggests, precision agriculture has the potential to reduce environmental impacts by providing better crop and land management while increasing economic returns, thus providing a stronger market.…”

Section: Discussionmentioning

confidence: 99%

Modelling Future Agricultural Mechanisation of Major Crops in China: An Assessment of Energy Demand, Land Use and Emissions

et al. 2020

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Agricultural direct energy use is responsible for about 1–2% of global emissions and is the major emitting sector for methane (2.9 GtCO2eq y−1) and nitrous oxide (2.3 GtCO2eq y−1). In the last century, farm mechanisation has brought higher productivity levels and lower land demands at the expense of an increase in fossil energy and agrochemicals use. The expected increase in certain food and bioenergy crops and the uncertain mitigation options available for non-CO2 emissions make of vital importance the assessment of the use of energy and the related emissions attributable to this sector. The aim of this paper is to present a simulation framework able to forecast energy demand, technological diffusion, required investment and land use change of specific agricultural crops. MUSE-Ag & LU, a novel energy systems-oriented agricultural and land use model, has been used for this purpose. As case study, four main crops (maize, soybean, wheat and rice) have been modelled in mainland China. Besides conventional direct energy use, the model considers inputs such as fertiliser and labour demand. Outputs suggest that the modernisation of agricultural processes in China could have the capacity to reduce by 2050 on-farm emissions intensity from 0.024 to 0.016 GtCO2eq PJcrop−1 (−35.6%), requiring a necessary total investment of approximately 319.4 billion 2017$US.

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Systematic literature review of implementations of precision agriculture

Cited by 195 publications

References 30 publications

A Spectroscopic Approach to Evaluate the Effects of Different Soil Tillage Methods and Nitrogen Fertilization Levels on the Biochemical Composition of Durum Wheat (Triticum turgidum subsp. durum) Leaves and Caryopses

A Spectroscopic Approach to Evaluate the Effects of Different Soil Tillage Methods and Nitrogen Fertilization Levels on the Biochemical Composition of Durum Wheat (Triticum turgidum subsp. durum) Leaves and Caryopses

Corn Grain Yield Prediction and Mapping from Unmanned Aerial System (UAS) Multispectral Imagery

Modelling Future Agricultural Mechanisation of Major Crops in China: An Assessment of Energy Demand, Land Use and Emissions

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