Analyzing Effects of Crops on SMAP Satellite-based Soil Moisture using a Rainfall-Runoff Model in the U.S. Corn Belt

L-band microwave satellite missions provide soil moisture information potentially useful for streamflow and hence flood predictions. However, these observations are also sensitive to the presence of vegetation that makes satellite soil moisture estimations prone to errors. In this study, the authors evaluate satellite soil moisture estimations from SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture Ocean Salinity), and two distributed hydrologic models with measurements from in~situ sensors in the Corn Belt state of Iowa, a region dominated by annual row crops of corn and soybean. First, the authors compare model and satellite soil moisture products across Iowa using in~situ data for more than 30 stations. Then, they compare satellite soil moisture products with state-wide model-based fields to identify regions of low and high agreement. Finally, the authors analyze and explain the resulting spatial patterns with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation indices and SMAP vegetation optical depth. The results indicate that satellite soil moisture estimations are drier than those provided by the hydrologic model and the spatial bias depends on the intensity of row-crop agriculture. The work highlights the importance of developing a revised SMAP algorithm for regions of intensive row-crop agriculture to increase SMAP utility in the real-time streamflow predictions.

Analysis of Weed Growth in Rabi Crop Agriculture Using Deep Convolutional Neural Networks

Weed interference for the duration of crop establishment is a severe difficulty for wheat in North India [22.9734 ° N, 78.6569 ° E]. In situ far-flung detection for precision herbicide application minimizes the danger of both crop damage and herbicide input. This research paper focuses on the comparative study of crop growth and its effect at three different places in Madhya Pradesh [24.5840° N, 81.5020° E] India[20.5937° N, 78.9629° E]. These weed species included Pigweed (Amaranthaceae ), Goosefoot [Chenopodiaceae], Wild oat species (Poaceae), livid amaranth (Amaranthus blitum L.), Fathen[Chenopodiaceae (L.) Wild.], and Bermuda grass (Poaceae L.) a significant weed for rabi crop production in India with sensitivity to clopyralid, is the best available put up broadleaf herbicide. The intention of the Takes a look to assess the accuracy of four different CNNs architectures to locate the weed images of the Rabi crop of the family of various Rabi crops growing in competition with Rabi crops at 3 sites in Madhya Pradesh. Four CNNs have been compared, including object detection-primarily based ResNet-50, image classification-based VGGNet-16, Inception v4 and EfficientNet-B7 the EfficientNet-B7 networks have been trained to hit upon both leaves or canopies Everlasting of weeds. Image classification the use of ResNet-50 and VGGNet-16 was largely unsuccessful all through validation with whole pics (Fl-score < 0.04). CNN training elevated the usage of cropped photographs Eternal Broad Fall detection at some stage invalidation for VGGNet (F1-score = 0.77) and ResNet-50 (F1-Score = 0.62). The rabi crop weed leaf-trained inception V4 and EfficientNet-B7 achieved the highest F1-Score (0.94) and F1 Score (0.96) respectively, The aim of leaf-based EfficientNet-B7 extended false positives, even though such errors could be won over with extra training images for network desensitization training. Photograph-based faraway sensing rabi crop will become the most viable CNN test for weeds in competition with the EfficientNet-B7 crop.

Optimizing Beef Cow-Calf Grazing across Missouri with an Emphasis on Protecting Ecosystem Services

Soil health is an emerging paradigm for which much research in row crop agriculture has been undertaken. Research involving grazing lands and soil health has not been as active, a feature partially attributed to (i) greater erosional rates in cropland, (ii) loss of soil organic matter and reduced soil structure attributed to annual tillage practices, (iii) cash flow from cropland is easier to visualize than the value-added nature of grazing lands, and (iv) there exists more competitive grant funding sources for croplands. Grazing lands do require soil quality augmentation and investment in soil health to optimize their ecosystem services potential. This manuscript, with an emphasis on beef cattle grazing in the central USA, attempts to survey the literature to (i) identify the influence of grazing on important ecosystem services provided by Mollisols and Alfisols, (ii) develop a listing of soil indicators that may be selected to quantify and credential soil quality, and (iii) develop guidelines that align soil indicators and changes in grazing management to support the restoration of ecosystem services.

535 Rethinking Grand Challenges within Sustainable Animal Production

Dietary policies are rapidly evolving, as the urgencies related to public health and sustainability of the food system are becoming more tangible and menacing. Increasingly, such policies bring up the need for a protein transition. This implies that society should consume less “animal protein,” while the protein gap should be filled with legumes and nuts, a series of so-called “plant-based alternatives” (i.e., imitations of animal source foods), bioreactor foods (e.g., lab-grown meat), and other sources of protein (e.g., algae and insects). The risk of such an approach, when taken too far, is that it tends to generate a simplistic categorization of the food system, whereby animal source foods (red meat in particular) are seen as intrinsically harmful and the non-animal replacements as mostly beneficial. This division is further fuelled by societal dynamics that are generated by vested interests, ideologies, societal anxieties, virtue signalling, white-hat bias, and scapegoating. Although there are obviously clear challenges that need to be urgently addressed within the livestock sector (as for most other parts of the food system, including various types of crop agriculture), we should not be blinded by such an irrational binary division. Moreover, the proposed solutions would come with their own issues (water-intensive crops with high chemical inputs, ultra-processed imitation foods, the negative effects of pasture land conversion on biodiversity and carbon deposits, concerns related to food security and food sovereignty, etc.) Instead, production and consumption practices need to be carefully evaluated based on a holistic assessment, and not through the myopic use of reductionist metrics that can easily be manipulated to reify preconceived points of view. The problems at hand are multidimensional, requiring proper contextualization. From a nutritional point of view, for instance, protein comes with substantial variability related to digestibility and amino acid profiles. Also, animal source foods offer much more than “protein” alone, including several key micronutrients and bio-active compounds that are often more difficult to obtain from plants. Within the area of sustainability, the entire climate change discussion would also benefit from a more inclusive assessment, thereby avoiding all-too static interpretations (ignoring the role of progress and technological development), negligence of true nutritional value when comparing very different foods (e.g., when using such metrics as CO2-eq/kg or CO2-eq/kcal), the use of global aggregates for local discussions, simplification of global warming kinetics (cf., the GWP100 vs. GWP* debate), and so forth. Taken together, Grand Challenges should aim primordially at the achievement of adequate essential nutrition within specific dietary contexts that need to be more broadly assessed (also including lifestyle, cardiometabolic health status, culture, food preferences, purchase power, etc.) and that should be generated within the constraints of a sustainable agricultural operating space. Some red lines may indeed need to be drawn by policy makers (e.g., halting of deforestation or water pollution), whereas some other practices may need to be optimized (veterinary care, nutrient cycles, emissions, etc.) or promoted (carbon sequestration, improvement of soil health and biodiversity, etc.), but it would be a fatal mistake to consider animal agriculture as a monolithic entity that needs to be severely restricted or even dismantled. Taking livestock out of the equation would undermine our only hope on a healthy and sustainable food system. They are essential for the upcycling of otherwise inedible materials (forage, waste and side streams, etc.) into the high-quality foods that are needed to combat malnutrition globally, the valorisation of marginal lands that are otherwise unproductive, the sequestration of carbon and the (re)generation of soil health, the provision of crucial ecosystem services and landscape management, the generation of livelihoods, and the (all-too often underestimated) treasuring of our various cultural legacies. Instead, an improved integration of animal and crop agriculture should be central in any Grand Challenge. This should be done based on the best available science, but also by being prudent about the potential black swans further down the road. Complex systems always kick back in unpredictable manners, especially if they are radically altered through hurried top-down approaches.

Greek Fish Farming: Measuring Profitability and Efficiency of the Sector at the peak of Economic Crisis

Fish farming play important role in providing food and income in many EU countries, either as a stand-alone activity or in association with crop agriculture and livestock rearing. Fish farming is widespread in Greece and differs only with respect to species, production systems and volumes. Moreover, the Greek economic crisis has heavily affected the fish farming sector and challenges the competitiveness of farms. The objective of the current paper is the examination of the profitability and efficiency of the Greek fish farming industry during the most crucial years of Greek economic crisis by measuring firm’s performance using a panel data set of companies. The research is based on financial data of sixty-eight aquaculture firms for the period 2010-2015. The empirical results indicate that firms share of total sales has a positive impact on profitability, while an alternative proxy, the total assets is negatively linked to efficiency. Firm's profitability is positively affected by liquidity, working capital management, productivity and industry’s growth and negatively by financial and operating leverage. Firms Efficiency is determined positively by profitability and ability to repay its debt obligations and negatively by capital intensity, operating leverage and size

Application Technology in the use of Correctives in Corn Culture

Corn is one of the most cultivated cereals in the world and is used for various purposes and its production is linked to its economic importance, requiring the use of means and methods that enable the increase of its production and one of them is the correction of the ground. The objective of this work is to carry out a brief literature review on the application technology in the use of correctives in the corn crop, highlighting the benefits of its use and the need for its use in the crop. The present study was developed based on a literature review and relevant research on the technology of application of correctives in corn crop, highlighting the benefits of its use and the need for its use in corn crop. Agriculture went through a long development, improving its production system and application technology came with one of the alternatives helping to maintain and improve soil quality, enabling the application of correctives in the soil with greater efficiency. The need for soil correction has to do with the relationship between the plant and the soil, highlighting the acidity, which in many cases is a problem for the cultivation of crops. The use of correctives to correct soil acidity brings many benefits to the physical and chemical characteristics of the soil, reduces fertilizer losses caused by leaching, provides calcium and magnesium to the soil adjusting the soil profile so that plants can benefit from available nutrients. Thus, application technology is essential for the corn crop and for the entire production system, even more in the application of correctives, as acidity is one of the causes of yield limitations. Thus, application technology favors soil correction, ensuring the benefits provided by proper application, becoming a means of increasing crop productivity and corn as well, due to the various productive aspects provided by the correct application in the soil.

Exploring the Potential of SMAP Soil Moisture for Improving Real-time Streamflow Prediction in the U.S. Corn Belt

L-band microwave satellite missions provide soil moisture information potentially useful for streamflow and hence flood predictions. However, these observations are also sensitive to the presence of vegetation that makes satellite soil moisture estimations prone to errors. In this study, the authors evaluate satellite soil moisture estimations from SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture Ocean Salinity), and two distributed hydrologic models with measurements from in~situ sensors in the Corn Belt state of Iowa, a region dominated by annual row crops of corn and soybean. First, the authors compare model and satellite soil moisture products across Iowa using in~situ data for more than 30 stations. Then, they compare satellite soil moisture products with state-wide model-based fields to identify regions of low and high agreement. Finally, the authors analyze and explain the resulting spatial patterns with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation indices and SMAP vegetation optical depth. The results indicate that satellite soil moisture estimations are drier than those provided by the hydrologic model and the spatial bias depends on the intensity of row-crop agriculture. The work highlights the importance of developing a revised SMAP algorithm for regions of intensive row-crop agriculture to increase SMAP utility in the real-time streamflow predictions.

Exploring the Potential of SMAP Soil Moisture for Improving Real-time Streamflow Prediction in the U.S. Corn Belt

L-band microwave satellite missions provide soil moisture information potentially useful for streamflow and hence flood predictions. However, these observations are also sensitive to the presence of vegetation that makes satellite soil moisture estimations prone to errors. In this study, the authors evaluate satellite soil moisture estimations from SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture Ocean Salinity), and two distributed hydrologic models with measurements from in~situ sensors in the Corn Belt state of Iowa, a region dominated by annual row crops of corn and soybean. First, the authors compare model and satellite soil moisture products across Iowa using in~situ data for more than 30 stations. Then, they compare satellite soil moisture products with state-wide model-based fields to identify regions of low and high agreement. Finally, the authors analyze and explain the resulting spatial patterns with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation indices and SMAP vegetation optical depth. The results indicate that satellite soil moisture estimations are drier than those provided by the hydrologic model and the spatial bias depends on the intensity of row-crop agriculture. The work highlights the importance of developing a revised SMAP algorithm for regions of intensive row-crop agriculture to increase SMAP utility in the real-time streamflow predictions.

Economics of autonomous equipment for arable farms

By collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous equipment profitable it is unlikely to be widely adopted. The objective of this study was to identify the potential economic implications of autonomous crop equipment for arable agriculture using a grain-oilseed farm in the United Kingdom as an example. The study is possible because the Hands Free Hectare (HFH) demonstration project at Harper Adams University has produced grain with autonomous equipment since 2017. That practical experience showed the technical feasibility of autonomous grain production and provides parameters for farm-level linear programming (LP) to estimate farm management opportunities when autonomous equipment is available. The study shows that arable crop production with autonomous equipment is technically and economically feasible, allowing medium size farms to approach minimum per unit production cost levels. The ability to achieve minimum production costs at relatively modest farm size means that the pressure to “get big or get out” will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of autonomous equipment to achieve minimum production costs even on small, irregularly shaped fields will improve environmental performance of crop agriculture by reducing pressure to remove hedges, fell infield trees and enlarge fields.

Priming of Marine Macrophytes for Enhanced Restoration Success and Food Security in Future Oceans

Marine macrophytes, including seagrasses and macroalgae, form the basis of diverse and productive coastal ecosystems that deliver important ecosystem services. Moreover, western countries increasingly recognize macroalgae, traditionally cultivated in Asia, as targets for a new bio-economy that can be both economically profitable and environmentally sustainable. However, seagrass meadows and macroalgal forests are threatened by a variety of anthropogenic stressors. Most notably, rising temperatures and marine heatwaves are already devastating these ecosystems around the globe, and are likely to compromise profitability and production security of macroalgal farming in the near future. Recent studies show that seagrass and macroalgae can become less susceptible to heat events once they have been primed with heat stress. Priming is a common technique in crop agriculture in which plants acquire a stress memory that enhances performance under a second stress exposure. Molecular mechanisms underlying thermal priming are likely to include epigenetic mechanisms that switch state and permanently trigger stress-preventive genes after the first stress exposure. Priming may have considerable potential for both ecosystem restoration and macroalgae farming to immediately improve performance and stress resistance and, thus, to enhance restoration success and production security under environmental challenges. However, priming methodology cannot be simply transferred from terrestrial crops to marine macrophytes. We present first insights into the formation of stress memories in both seagrasses and macroalgae, and research gaps that need to be filled before priming can be established as new bio-engineering technique in these ecologically and economically important marine primary producers.