Agricultural Research最新文献

This rice-centric review briefly revisits Flor's seminal hypothesis on plant resistance and principles of plant immunity to examine novel genetic strategies for managing disease resistance. We review the key resistance genes, both old and new, highlighting their functionalities. Broad-spectrum resistance and its durability focus on delaying or weakening the arms race between the host and the pathogen. Knowledge gained through integrated biochemical and molecular approaches in dissecting the nature of disease resistance facilitates a better understanding of host–pathogen interactions. This reveals the possibility of undertaking gene modification without disrupting the balance between normal growth and immunity. In addition, it has led to the discovery of valuable and novel, naturally occurring alleles for use in improving crop resistance to diseases. Recent advances in the fundamental molecular understanding of disease resistance, focusing on rice physiology and biochemistry, could aid in developing new strategies to enhance the durability of disease resistance through genome editing and breeding techniques, equipping farmers with robust cultivars for sustainable rice production.

The rise in global mean temperature is the main cause of the increase in frequency and intensity of extreme weather events. In Brazil, the main sources of greenhouse gas (GHG) emissions are land use change and the agricultural sector, with emphasis on beef production. In this study, our objective was to examine the contribution of beef production to environmental impacts and evaluate the potential for mitigating these effects to address environmental concerns. We conducted a systematized review of agricultural production impacts on the environment, specifically deforestation and GHG emissions, and debated the solutions available to mitigate these impacts by focusing on alternatives for livestock production. The search resulted in 54 articles, of which 43 were selected and divided into categories according to topic similarities. Beef production, especially in the extensive system, widely contributes to GHG emissions, specifically due to enteric fermentation and manure left on the pasture, and deforestation for pasture opening. The solutions to mitigate these impacts permeate several areas, such as political and structural modifications, and changes in the agricultural production model. Of the intensification strategies discussed, we highlight pasture restoration, rotational grazing and diet supplementation as the most promising approaches. Our study makes an important contribution to the discourse on sustainability in beef production by recognizing and addressing the multifaceted challenges inherent in achieving sustainability.

This review paper discusses the potential and limitations of polymer composites for smart nitrogen (N) supply to meet the needs of agricultural crops. Unlike most conventional fertilizers, nano-clay polymer composites (NCPCs) offer a slow-release mechanism that enhances nitrogen use efficiency and reduces its loss to the environment. NCPCs are normally synthesized using solution blending, melt blending and in situ polymerization. Solution blending offers a better clay dispersion in the polymer matrix than melt blending owing to its low viscosity and strong stirring force. NCPCs have been characterized by several techniques, including equilibrium water absorbency, Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction and nutrient release kinetics. The potential benefits of using these composites are highlighted, including improved nitrogen use efficiency and reduced environmental impacts, as are their prospects for widespread use in agriculture and mitigation of the adverse environmental effects from conventional fertilizers. In addition, the limitations of NCPC technology, such as cost, scalability and potential negative environmental effects, are also investigated. The paper provides a wide perspective on the NCPC technology, including the regulatory environment and policy, industry trends and commercialization potential. NCPCs offer many benefits to increase nitrogen use efficiency and reduce pollution affecting water quality, air quality and climate. The main current barrier to overcome is to reduce production costs, so that farmers may also benefit financially from the higher nitrogen use efficiency and associated reduced amounts of nitrogen wasted to the environment.

Flavonoids are a type of antioxidants widely used to treat various human diseases. Apart from guava fruits, flavonoids are also found in the leaves. Determining the leaf flavonoid content generally involves chemical analysis, which is time-consuming and costly. This study aimed to estimate quickly the flavonoid and nitrogen contents in fresh and extracted leaves using two different phenomena: (gas and vision) captured by an e-nose (equipped with nine different MQ sensors) and a SPAD-502 chlorophyll meter. This study also determined the relationship between flavonoids and nitrogen in guava plants and the selection of leaf variations, which contained the maximum levels of these compounds. A total of nine machine learning algorithms were applied to evaluate the data obtained from both the e-nose and SPAD-502 m as ten input features. The results showed that: (1) using ten input features obtained from fresh leaf samples provided better accuracy in classifying and estimating both flavonoid and nitrogen contents rather than using feature important ranking and extracted guava leaves. An artificial neural network—multilayer perceptron (ANN MLP) is a machine learning algorithm that provided maximum accuracy in classifying and estimating flavonoid and nitrogen contents with coefficient determination (R²) ranging between 0.76 and 0.96; (2) laboratory analysis did not indicate a positive relationship between flavonoid and nitrogen contents in guava leaves; and (3) selection of leaf numbers 1–5 was appropriate to ascertain flavonoid content in the optimum–high range, while the leaf number 3 from shoots that have opened completely to estimate the N status can be selected.

Ignoring quality standards in dairy and food industry can lead to financial and health problems in the face of today's strict legislation and growing customer awareness. The nutrient dense nature, perishability and wide popularity of dairy-based foods make them prone to adulteration and compromise in quality. High-performing systems at every stage of the production chain in dairy industry have become more prevalent in the food sector as a lookout for solutions. Dielectric spectroscopy is a high-performing sensor-based technology which is gaining popularity because of their ability to monitor, analyse and diagnose fault of various agricultural, food and dairy products. This paper attempts to fully explore basic principle of dielectric spectroscopy, the various factors influencing the dielectric parameters of milk and dairy products, and the findings of studies in which dielectric spectroscopy was used for quality assessment and monitoring of dairy processing. A summary of current research in this area is presented along with some comments on recent developments to provide a collection of recent data in order to make experimental data available as a valuable reference for more studies and applications.

The Ghout is a traditional agrosystem classified among the Globally Important Agricultural Heritage Systems by the FAO. This Saharan artificial ecosystem was created through manual digging of the soil to approach the level of groundwater; date palm trees are planted at about 1 m depth and benefit from water without irrigation. The Ghout, composed of three stratum (palm trees, fruit trees and shrubs, and herbaceous plants), had remarkable floristic and faunal biodiversity. Since the 1980s, this agricultural system has been persistently degraded due to anthropogenic origins in the municipality of El Oued, mainly as a result of urban expansion and fluctuations in the water table level. Until the early 2000s, the phenomenon of rising water levels caused the drowning of palm trees and the disappearance of Ghouts; this was the consequence of the lack of an effective sewage system. However, since the 2010s, the lowering of groundwater levels to a depth exceeding 9 m has led to the drying up of Ghouts; it is due to the high demand for irrigation water. In addition, other factors have contributed to the disappearance of this innovative system, such as the inheritance and amortization of gardens leading to low production, which has resulted in the abandonment of these areas and the lack of interest from the youth to work in this heritage. The degradation of agrobiodiversity and varietal diversity of the date palm are among the characteristics recorded during the last decade, where the two cultivars Deglet Nour and Ghars dominate the Ghouts. Despite these drawbacks, in recent years, the emergence of digging the Ghouts has been recorded in the northeast and southwest of the province of El Oued.

Modern technologies in the agricultural sector present tremendous opportunities to increased farm profitability and productivity. To achieve this, it is necessary to identify suitable solutions and ways to meet agricultural needs and requirements. This may be done by increasing production and finding rapid solutions for common issues that arise in production and have an impact on the agricultural economy. Drone usage for precision agriculture has grown dramatically in the recent years. Since drones can collect data specific to a certain site and assess crop health, they are helpful in precision agriculture. Drone technology helps in preserving soil fertility, reduces overuse of water and pesticides and herbicides, increases productivity and enhances quality, while also assisting in the efficient use of human labour. Aerial seeding and spraying are two uses of drone technology that can help to overcome manpower and cost constraints associated with manual labour. Even though there are some constraints of using drones, drone market will grow as their new applications are realized. This paper provides an extensive overview of the types, construction and applications of drones in agriculture. It also points out the potential advantages of drones in this field and calls for cooperation to overcome obstacles and realize the full potential of precision farming on a worldwide scale.

In the current context of decline in soil fertility, soil degradation and climate change, the use of mycorrhizal inoculum is one of the alternatives for sustainable agriculture. This study aims to determine the best combination of Arbuscular Mycorrhizal Fungi (AMF) biostimulant and mineral fertilizer (NPK + Urea) to improve maize production and the nutritional status of maize plants on ferruginous soils. The experimental design was a completely randomized block of seventeen treatments repeated three times in Savè/Benin. Growth parameters were assessed at 60 days after sowing, while grain yield, physical characteristics and nutritional status were assessed after harvest. After a hierarchical classification of the results, we obtained a group of high-performing and statistically homogeneous treatments composed of T10 to T16. These treatments induced an average height of 185.81 ± 1.16 cm, a crown diameter of 2.20 ± 0.02 cm; a leaf area of 469.82 ± 2.11 cm2 and a grain yield of 2.98 ± 0.11 t/ha. Treatment T10 improved plant nutrition in terms of nitrogen, phosphorus and potassium follow up T1 and T11. High 1000-grain weights were recorded with the treatments T10 and T11. The hardness of maize grain produced with the biostimulant decreased as root mycorrhization increased. It appears from the results that the application of the biostimulant based on arbuscular mycorrhizal fungi improved the parameters evaluated. In addition, the application of the biostimulant based on arbuscular mycorrhizal fungi improved the parameters evaluated. But this research deserves to be handled in the field in order to lead to an economic profitability study.

Digital soil mapping is an innovative and highly efficient technique that extracts valuable insights about soil by analyzing a combination of soil and environmental factors. A recent study conducted in Tamil Nadu demonstrated the accuracy and effectiveness of digital soil mapping in predicting soil properties both qualitatively and quantitatively. Around 440 points of soil database were generated through soil survey and from existing soil resources and the environmental variables were derived from satellite based remote sensing data. Thirty three covariates of soil and environment factors were generated and used as input in the See5 algorithm for predicting the texture class at surface and subsurface level. Out of 33 covariates, 25 and 24 covariates were effectively used for prediction of soil texture with an overall accuracy of 75 and 71.7 per cent and kappa coefficient of 0.65 and 0.58 at surface and subsurface class, respectively. The tangential curvature, profile curvature, geology, geomorphology and land use land cover classification were effectively used for surface soil texture prediction while the maximal curvature and geology were found to have high influence in predicting subsurface soil texture. Cubist model was used for quantitative prediction of sand and clay content using 200 point observations as training data and 160 as validation data. Two rule sets were generated to predict sand and clay separately revealing that green band was highly essential for prediction of sand content followed by red band, NIR band and SWIR band, while geology was the important variable for prediction of clay content. The prediction had an estimation error of 11.9% for sand and 8.6% for clay fraction indicating that the digital soil mapping is an efficient method to derive qualitative and quantitative information about soil properties, making it a promising tool for soil scientists and researchers.

The energy use and emissions from direct fossil fuel combustion on-farms to power farm machinery was critically reviewed. Approximately, 15% of agricultural production costs on-farm are energy-related. A potential solution to more sustainable energy use is a shift toward biofuels from renewable resources. The reduction of greenhouse gas emissions through the substitution of diesel oil with biodiesel depends on the feedstock, the inter-esterification process, the storage period, and ambient conditions. In modern tractors, increased fuel use efficiency (or reduced fuel consumption) has been achieved by power/load matching and the use of variable transmission. Engine management systems that are capable of continuously communicating with the engine and transmission to make appropriate adjustments based on inputs received from the tractor allow for quick and precise responses to changing conditions. As a result, maximum efficiency and productivity can be obtained from the tractor operating similarly to the traditional ‘gear-up and throttle-back’ methods of a proficient operator. The future for autonomous tractors is promising, though not new. Electric-powered tractors are near to commercialization or are already commercially available. Hybrid electric driven tractors present some advantages in terms of increased energy use efficiency and functionalities. Increased efficiency can lead to a reduction in diesel fuel consumption and hence, a concurrent decrease in CO₂ emission. Where the local electricity supply has a low-carbon emission factor, this can also result in significant emission reductions. Small light-weight robotic equipment can potentially perform functions currently undertaken by tractor-drawn and other heavy equipment with high-fuel consumption, provided field operating capacity was not compromised. However, the size and weight limitations inherent in current harvesting and transport technology mean that soil compaction will still be a problem with robotic units. The robotic operation of medium-scale equipment within a precision-controlled traffic farming environment should offer more feasible and energy-efficient alternatives.