Conservation management in dryland agriculture preserves water, improves soil health and yields. To comprehend the complex interactions of conservation management and environmental factors in a rainfed forage system of the US Great Plains, distinguish the superior influence of conservation over conventional management, and have a different perspective from simulation modeling, machine learning (ML)

Intensive agricultural practices to meet the current world food demand are the main cause of degradation of soil health and environmental pollution. In traditional agriculture, synthetic fertilizers are used which can impact soil health and result in environmental pollution. So, agricultural production in a sustainable way becomes a current issue. Different agricultural inputs may improve soil health

The increasing availability of remote sensing (RS) data and the advancement of computation abilities, combined with the demands for enhancing crop production, encourages the creation of a framework in which crop growth simulation can be updated sequentially to serve as a yield predictor and be part of a decision support system. However, crop model outputs and RS data must be linked via a radiative

The study aim was to analyze and interpret long-term trends in temperature and olive reproductive features, including full flowering dates and daily pollen concentrations, in central Italy. A 40-year database (1982–2022) of pollen and temperature records was utilized. Temperature changes significantly affect spring phenology and olive trees, sensitive to climate change, exhibit earlier flowering in

Long-term chemical fertilizer use poses sustainability challenges for achieving optimal crop yields and may even diminish yields and fertilizer use efficiency. Sustainable and environmentally friendly agricultural practices must address these challenges by reducing fertilizer application. Biochar emerges as a promising solution, with significant potential for enhancing soil fertility and crop yields

Soybean [Glycine max (L.) Merr.] is one of the major crops worldwide. Identification of environmental factors that improve both yield and N2-fixation remain of high importance.

Powdery mildew disease threatens wheat production worldwide, and early detection is of great significance for disease control and maximizing yield and quality. To improve early remote sensing detection of wheat powdery mildew, solar-induced chlorophyll fluorescence (SIF) parameters were extracted using three-band Fraunhofer line discrimination (3FLD) and reflectance index approaches, and vegetation

The dwarfing gene Rht15 can significantly reduce plant height and improve lodging resistance, but has some negative effects on yield traits. Rht15 is a gibberellin-responsive (GAR) dwarfing gene that causes dwarfism by blocking the Gibberellin (GA) synthesis pathway in plants, and application of exogenous GA3 can increase the plant height phenotype. The aim of this study was to investigate whether

Oat is a functional resource in food processing, medical, and cosmetic industries. The aim of this study was to compare the influence of agronomic factors and physiological and climatic parameters on the grain yield of hulled and hulless oat. The following variables were evaluated in a three-year experiment: (i) agronomic factors – nitrogen fertilization, plant protection, and oat morphotypes, (ii)

Timely access to crop above-ground biomass (AGB) information is crucial for estimating crop yields and managing water and fertilizer efficiently. Unmanned aerial vehicle (UAV) imagery offers promising avenues for AGB estimation due to its high efficiency and flexibility. However, the accuracy of these estimations can be influenced by various factors, including crop growth stages, the spectral resolution

Global solar radiation has been decreasing, posing a great threat to food security by reducing photo-assimilation and disrupting carbon (C) partitioning in crops like maize. However, practical countermeasures to cope with source-sink balance in periodic shading stress are lacking. Here, we first simulated shading stresses with different degrees and occurring periods on field maize for two years. Results

Understanding the effects of climate change on cotton fiber quality will reduce the risks to production caused by global warming. Machine learning algorithms are effective for forecasting climate impacts on crops. However, the impact of climate change on cotton fiber quality is unclear. Hence, a hybrid machine learning-enabled approach, the Bayesian model average (BMA) method with multiple machine

The effects of temperature changes on rice (Oryza sativa L.) yield and its components have been widely documented. However, most existing studies are based on small-scale, short-term field experiments, with few assessing these effects on a large scale or over long periods. Here, the calibrated Crop Environment Resource Synthesis (CERES)-Rice model was used for numerical simulations over six climate

The growth poses of citrus on trees are diverse. To ensure minimal loss during citrus harvesting, accurately estimating the pose of citrus is particularly important. To solve this problem, this research developed a real-time citrus pose estimation system based on neural networks and point cloud processing algorithms. Specifically, this method uses neural networks to identify citrus. After constructing

A well-designed drainage system can alleviate soil salinity and waterlogging, leading to increased crop yield if the drainage does not cause a water shortage late in the growing season. We conducted three field experiments with sunflower across two dry seasons (Experiment I in 2019–20, and II and III in 2020–21) in a tropical landscape to examine the effectiveness of shallow drains and mulch in overcoming

European agriculture policies emphasize the importance of agricultural sustainability, focusing on increase of biodiversity through crop diversification. In Mediterranean dryland cropping systems, the introduction of crops in rotation with cereals is challenged by scarce precipitation and high evapotranspiration. In this scenario, camelina (Camelina sativa (L.) Crantz), a low-input annual oleaginous

Accurate identification of crop growth stages is a crucial basis for implementing effective cultivation management. With the development of deep learning techniques in image understanding, research on intelligent real-time recognition of crop growth stages based on RGB images has garnered significant attention. However, the small differences and high similarity in crop morphological characteristics

In China’s Loess Plateau, plastic mulch (PM) is an effective agronomic practice for dryland maize (Zea mays L.) to increase grain yield (GY) and water use efficiency (WUE) under water-limited conditions. However, there is dearth of quantitative data on how PM affects field water use step by step, subsequently increasing GY and WUE. The study aimed to identify which changes in the field water use pathway

To promote the efficient utilization of groundwater and improve nitrogen fertilizer effectiveness, a reasonable range of nitrogen application rates and irrigation water temperature was investigated. A field experiment was conducted in Xinjiang, China, in 2022 and 2023, involving four irrigation water temperature levels (T0: 15 °C, T1: 20 °C, T2: 25 °C, and T3: 30 °C) and three nitrogen application

In the current study, the uncertainties of wheat modeling using gridded soil and weather datasets were analyzed under dry farming and irrigated conditions. In this regard, the performance of the CSM-CERES-Wheat model forced with different weather-soil data combinations was studied in some dryland regions in Iran based on normalized Root Mean Square Error (nRMSE), Kling-Gupta Efficiency (KGE), and Percent

Tomatoes, globally cultivated and economically significant, play an essential role in both commerce and diet. However, the frequent occurrence of diseases severely affects both yield and quality, posing substantial challenges to agricultural production worldwide. In China, where tomato cultivation is carried out on a large scale, disease prevention and identification are increasingly critical for enhancing

Enhancing nitrogen (N) use efficiency (NUE) is crucial for the sustainable production of potatoes (Solanum tuberosum L.). The aims of this study were to assess i) the genotypic variation of the main components of NUE (N utilization efficiency (NUTE) and N recovery efficiency (NRE)), ii) the association between these components, related traits, and cultivars, and iii) the usefulness of N nutrition index

Photoperiod manipulation using supplemental lighting enables double-season production of hops (Humulus lupulus L.) under subtropical climatic conditions. In Florida, United States, the spring growing season (Spring) is from February to June, and the fall growing season (Fall) is from June to November. To develop the optimum trellis for this unique hop production system, we examined the effects of two

Manure substitution shows promise for nitrogen (N) management, food security, energy balance and environmental costs reduction. However, there is limited research on this practice in the Huanghuaihai Plain. This study aimed to investigate the energy use efficiency, economic benefits, carbon and nitrogen footprint under two types of N fertilizer (U, urea and M, organic manure), two application rates

The frequency of abiotic stress impairing wheat root growth and yield production has been increasing with global warming. Diverse root traits have been widely targeted to improve wheat adaptivity to different abiotic stress, but most research has been conducted under controlled environments with a single stress factor, hindering transferability to fields conditions with multiple stresses. It is essential

Conventional breeding of ideotypes for target environments is quite challenging because of the genotype by environment interaction and the nature of the genetic complexity for economic traits. Simulation of the adaptive capacity of existing and new germplasms using crop model and genetic information can efficiently assist in determining the potential of well-adapted genotypes for target environments

The Jyndevad field experiment, initiated in 1942 on a coarse sand soil in South of Denmark, explores the effect of four liming levels (0, 4, 8 and 12 Mg lime ha−1). These were in 1944 combined with two levels of mineral phosphorus (P) fertilizer (0 and 15.6 kg P ha−1 year−1), with or without a high initial dose of 156 kg mineral P ha−1. This study assesses interactions between liming and P fertilization

High temperature is known to reduce crop yield, while increased nitrogen (N) application will increase crop grain and protein yields to a certain extent. However, there are few studies on the effects of different N application treatments on crop yield and protein under climate warming in different wheat-maize rotation cultivation sites. Therefore, by utilizing the APSIM model, we investigated crop

Enhancing resilience of agroecosystems of Mediterranean area is a challenge that involves both researchers and different stakeholders and, in this context, increasing crop diversity by redesigning agricultural systems can be considered among the most important tools. Therefore, the response of agroecological practices to climate change effects was tested in a long-term experiment on organic horticultural

Straw return has been found to benefit soil fertility and crop yield, however, by which it affects microbial communities to mediate soil factors driving crop yields under maize continuous cropping systems in dryland areas is still unclear. To fill this gap, a 6-year field experiment was established with five straw return amounts (T0, T1, T2, T3, and T4, representing 0, 3000, 6000, 9000, and 12,000 kg ha−1

The use of remote sensing technologies to monitor the nitrogen nutrient status of crops is gradually becoming a more sensible choice, as traditional methods are time-consuming, labor-intensive, and destructive. However, most predictive models utilizing remote sensing data are statistical rather than mechanistic, making them difficult to extend at interannual and regional scales. This study explored

Sustainable agriculture systems incorporate important stabilizing mechanisms, such as mulching, for increasing yield and improving soil health. However, the synergistic effects of different long-term mulching practices on soybean yield stability and soil health remain unexplored. In this study, we conducted a 13-year long-term investigation to evaluate the impacts of various mulching methods—no mulching

Soil waterlogging in many arable regions of the world challenge the quantum and quality of crop production. While previous studies have assessed the impact of waterlogging on crop yields, understanding of how waterlogging implicates with crop quality remains in its infancy. Here, we conduct a systematic literature review and meta-analysis to assess how waterlogging influences grain quality. We also

Automatically identifying key physiological factors in plants, such as leaf relative humidity (LRH), chlorophyll content (Chl), and nitrogen levels (N), is vital for effective aeroponic management and improving growth, yield, quality, and sustainability. Meta-learning (MetaL) solutions utilize data fusion and intelligent processing, ensuring fast and consistent outcomes. This paper aims to develop

Improving crop yield and stability is crucial for sustainable food production, which is predominantly influenced by climate. Nutrient management mitigates the negative impacts of climate change on yield stability, but little is known about the explanatory capability of climate variables (especially canopy, soil, and nighttime temperatures) and soil nutrient interactions for yield anomalies. This study

Plant N nutrition and preharvest stem nonstructural carbohydrates (NSCs) greatly influence ratoon crop yield in a riceratoon-rice system. However, their physiological relationships haven’t been unraveled. We designed this study to test whether greater rice regeneration ability due to preharvest N application is accompanied by increased stem reserves, or whether plant N nutrition and stem reserves independently

The baking industry requires a high level of uniformity in flour quality to meet its demands. Cereal production and nutritional traits are tightly conditioned by genotype and environmental factors. In the current study, the impact of temperature and rainfall on yield and end-use quality of two bread wheat (Triticum aestivum L.) cultivars (Camargo and Marcopolo) was analysed under field conditions.

This study presents the development and evaluation of machine learning models for detecting leaf spot disease in brinjal crops using spectral sensor data. The spectral reflectance of diseased and healthy tissues was recorded across nine wavelength bands (F1: 415 nm, F2: 445 nm, F3: 480 nm, F4: 515 nm, F5: 555 nm, F6: 590 nm, F7: 630 nm, F8: 680 nm, and F9: NIR-750 nm). The data revealed distinct spectral

Lodging is a critical factor in reducing sugarcane yields worldwide, mainly due to the selection of highly productive varieties. Understanding the response of yield and lodging to the combined effects of climate, sugarcane traits, and varieties has become a priority under climate change. The aim of this study was to better understand the influence of plant characteristics, climate, and soil conditions

Fine tuning crop development is a major breeding avenue to increase crop yield and for adaptation to climate change. We used an ecophysiological model that integrates our current understanding of the physiology of wheat phenology to predict the development and anthesis date of 91 recombinant inbreed lines (RILs) of durum wheat with genotypic parameters controlling vernalization requirement, photoperiod

Canola (Brassica napus L.) and carinata (Brassica carinata A. Braun) are two oilseed crops that have seen a surge in demand in recent years. However, current yields achieved by farmers are inconsistent and significantly lower than those achieved in research experiments. Therefore, a better understanding of the trade-off between yield components is crucial to help breeders develop new high-yielding

Crop yield is directly influenced by the storage and stabilisation of soil organic carbon (SOC), which is determined by the hydrophobicity of soil humic acid (HA). Changes in soil HA hydrophobicity, humic substances, SOC and crop yield were compared after the application of different amounts of straw returns in the field, and the contribution of straw application in enhancing HA hydrophobicity was

Arbuscular mycorrhizal fungus (AMF) can mediate physiological adaptation of higher plants to drought stress, including wheat. Yet, it is unclear how AMF affects reproductive output via mediating crop physiological vitality at the evolutionary scale. To clarify this issue, a growth environment-controlled experiment was conducted using four primitive wheat genotypes and four modern ones with or without

Agricultural management practices that reduce greenhouse gas (GHG) emissions have been identified as effective mitigation strategies. However, research on carbon emissions from major crops in Northeast China focuses on national and provincial data, overlooking city-scale variability and uncertainties, which prevents fine-scale assessment of crop emissions reduction potential. To address this, a life

Soybeans are of great importance to the global economy, but the cultivation as monoculture has shown several negative environmental implications in the long-term. Long-term studies demonstrate the cumulative effects of rotations on soil variables, but few studies have considered changes during consecutive years in a time series of soybean as a monoculture. The inclusion of cereals and cover crops in

Freezing injury may cause irreversible damage to wheat (Triticum aestivum L) tissues and can significantly reduce yield and quality. Therefore, quick and non-destructively estimating the degree of frost damage for formulating anti-freezing protection strategies and preventing frost damage is very crucial. In this study, we obtained hyperspectral images of wheat leaves for accurate identification of

Real-time or pre-symptomatic wheat scab (WS) detection is inevitable for precision agriculture to secure yield and quality at the critical grain formation stage. For this, feature selection (FS) techniques and machine learning (ML) have demonstrated their capabilities. However, for the same type and size of dataset, all FS and ML techniques behave differently due to their diverse primary constituents

Nitrogen (N) is an essential macronutrient for plant growth. As a widespread source of plant-available N, ammonia synthesis via the Haber-Bosch process has proven an extremely valuable commodity in farming systems since the middle of the twentieth century. However, its heavy reliance on ever-shrinking fossil fuel reserves and its sizeable carbon footprint have fostered the exploration of alternative

Precise prediction of agricultural production output is crucial for farmers, policymakers, and the Farming-related industry. This article introduces a novel methodology to crop yield forecasting using a capsular neural network equipped with Conv-LSTM and attention mechanism. Our model combines the strengths of 3DCNN, and Conv-LSTM, which can capture the temporal dependencies and 3D features of crop

Climate change and rising atmospheric CO2 levels are critical factors influencing agricultural productivity, particularly in Morocco, where cereal crops are essential for food security. The primary objective of this study is to evaluate the combined effects of atmospheric CO2 variations and climatic changes on cereal yields up to 2099 using the CARAIB dynamic vegetation model. This evaluation is driven

Grazing and precipitation are pivotal factors influencing the productivity and biodiversity of grassland ecosystems, largely through their effects on the growth and reproduction of dominant species. Approximately 50 % of terrestrial ecosystems are concurrently affected by grazing and precipitation addition (PA), yet the interactive effects of these factors remain underexplored. To elucidate the combined

Computer vision-based precision weed control offers a promising avenue for reducing herbicide input and the associated costs of weed management. However, the substantial investments in time and labor required for the collection and annotation of weed image data pose challenges to develop effective deep learning models. The limitation also stems from the challenges in achieving accurate and reliable

Accurate estimation of soil moisture content (SMC) is essential for optimizing irrigation schedules and identifying drought-tolerant varieties. The integration of unmanned aerial vehicles (UAVs) with advanced sensors provides a novel method for monitoring SMC with high flexibility, resolution, and performance. This study utilized UAVs to capture RGB, multispectral, and thermal imagery of alfalfa (Medicago

Soil magnesium (Mg) deficiency is a common problem in many crop plants including rapeseed (Brassica napus L.), resulting in significant impairments in seed yield and quality. However, precise application approaches and technologies used for Mg fertilization are still not well established for rapeseed plants grown under field conditions. A better understanding and characterization of the relationship

Agricultural and livestock production cover more than a third of the Earth's land surface and are crucial to food supply. Soil extracellular enzymes play an important role in the transformation of elements and compounds in soil, particularly acid (ACP) and alkaline (ALP) phosphatases (both, APases). These enzymes have a vital role in releasing phosphorus (P) from organic matter. However, the effect

The disposal of biodegradable materials, particularly fruits and vegetables, has emerged as a critical environmental concern. Recycling the components of such wastes is paramount to preserving the natural environment. Incorporating biochar-based fertilizer (BCF) in agricultural practices can boost soil nutrient levels. Nevertheless, the effects of BCF derived from fruit and vegetable wastes on crops

This research paper presents a comprehensive scientometric analysis of English articles from the Scopus database regarding the topic of cover crop management from 1956 to March 2024. Through the analysis of the annual production trend, total production, a co-occurrence network of keywords, co-authorship networks, and co-citation networks, the data was mapped and visualized using VOSviewer and Bibliometrix

To ensure the sustainable use of phosphorus (P) fertilizers it is necessary to develop P management strategies that maximize crop yield while minimizing P leaching. Current P management practices, based on single agronomic soil P tests such as Olsen P (POLSEN), do not consider the P sorption capacity allowing one to predict soil P dynamics in response to long-term P inputs and related impacts on crop