Search Results (8,320)

The application of slow-release nitrogen fertilizer not only economizes labor input, but also decreases the frequency of use of mechanical intakes, with significant implications in advancing modern intensive agricultural production. Whether slow-release nitrogen fertilizer application can influence the association between microbial diversity and soil multifunctionality remains controversial. This study analyzed the spatial variances of soil environmental factors, soil multifunctionality, and their correlations with bacterial and fungal communities under five nitrogen application rates. The key factors influencing the dominant microbial species and community structures at different spatial locations were determined by the slow-release nitrogen fertilizer application rate, and the driving factors and dominant species of soil multifunctionality were identified. In contrast to the control group, moderate slow-release nitrogen fertilizer application enhanced soil multifunctionality and ameliorated the resilience of microbial diversity loss at diverse spatial locations resulting from irrational nitrogen fertilizer application. The resilience of the fungal community to disturbances caused by fertilization was lower than that of the bacterial community. Bacterial diversity exhibited a significant correlation with soil multifunctionality, and the soil multifunctionality intensity under 240 kg ha⁻¹ treatment increased by 159.01% compared to the CK. The main dominant bacterial communities and the dominant fungal community Ascomycota affected soil multifunctionality through slow-release nitrogen fertilizer application. Structural equation modeling and random forest analysis demonstrated that bacterial community diversity, particularly in bulk soil and the rhizosphere, community composition, and soil nitrogen form are the primary driving factors of soil multifunctionality. Results indicated that the microbial niche alterations induced by slow-release nitrogen fertilizer application positively affect soil multifunctionality. Full article

Heavy metal pollution is one of the most devastating abiotic factors, significantly damaging crops and human health. One of the serious problems it causes is a rise in cadmium (Cd) toxicity. Cd is a highly toxic metal with a negative biological role, and it enters plants via the soil–plant system. Cd stress induces a series of disorders in plants’ morphological, physiological, and biochemical processes and initiates the inhibition of seed germination, ultimately resulting in reduced growth. Fiber crops such as kenaf, jute, hemp, cotton, and flax have high industrial importance and often face the issue of Cd toxicity. Various techniques have been introduced to counter the rising threats of Cd toxicity, including reducing Cd content in the soil, mitigating the effects of Cd stress, and genetic improvements in plant tolerance against this stress. For decades, plant breeders have been trying to develop Cd-tolerant fiber crops through the identification and transformation of novel genes. Still, the complex mechanism of Cd tolerance has hindered the progress of genetic breeding. These crops are ideal candidates for the phytoremediation of heavy metals in contaminated soils. Hence, increased Cd uptake, accumulation, and translocation in below-ground parts (roots) and above-ground parts (shoots, leaves, and stems) can help clean agricultural lands for safe use for food crops. Earlier studies indicated that reducing Cd uptake, detoxification, reducing the effects of Cd stress, and developing plant tolerance to these stresses through the identification of novel genes are fruitful approaches. This review aims to highlight the role of some conventional and molecular techniques in reducing the threats of Cd stress in some key fiber crops. Molecular techniques mainly involve QTL mapping and GWAS. However, more focus has been given to the use of transcriptome and TFs analysis to explore the potential genomic regions involved in Cd tolerance in these crops. This review will serve as a source of valuable genetic information on key fiber crops, allowing for further in-depth analyses of Cd tolerance to identify the critical genes for molecular breeding, like genetic engineering and CRISPR/Cas9. Full article

Climate change significantly threatens crops, mainly through drought stress, affecting barley, which is essential for food and feed globally. Ten barley cultivars were evaluated under normal and drought stress conditions during the 2019/20 and 2020/21 seasons, focusing on traits such as days to heading and maturity, plant height, number of spikes m⁻², spike length, 1000-kernel weight, and biological and grain yield. Drought stress significantly reduced most of these traits. The genotypes showed significant differences in their responses to irrigation treatments, with the interaction between seasons and cultivars also being significant for most traits. The grain yield and 1000-kernel weight were among the least affected traits under drought stress, respectively. Notably, Giza138 and Giza126 showed strong drought tolerance, suitable for drought-resilient breeding. In season one, Giza126, Giza134, and Giza138 yielded 13%, 9%, and 11%, respectively, while Giza135 and Giza129 showed higher reductions at 31% and 39%. In season two, Giza126, Giza134, and Giza138 had reductions of 14%, 10%, and 13%, respectively, while Giza135 and Giza129 again exhibited higher reductions at 31% and 38%. These cultivars also showed strong performance across various stress tolerance indices, including the MP, YSI, STI, GMP, and YI. Giza 134 demonstrated the lowest values for the SDI and TOL, indicating superior drought stress tolerance. On the other hand, Giza 129 and Giza 135 were the most sensitive to drought stress, experiencing significant reductions across critical traits, including 6.1% in days to heading, 18.37% in plant height, 28.21% in number of kernel spikes⁻¹, 38.45% in grain yield, and 34.91% in biological yield. In contrast, Giza 138 and Giza 2000 showed better resilience, with lower reductions in the 1000-kernel weight (6.41%) and grain yield (10.61%), making them more suitable for drought-prone conditions. Giza 126 and Giza 132 also exhibited lower sensitivity, with minimal reductions in days to heading (2%) and maturity (2.4%), suggesting potential adaptability to water-limited environments. Giza 126 maintained the highest root lengths and had the highest stomatal conductance. Giza 138 consistently had the highest chlorophyll content, with SPAD values decreasing to 79% under drought. Despite leading in shoot length, Giza 135 decreased to 42.59% under drought stress. In conclusion, Giza 126 and Giza 138 showed adaptability to water-limited conditions with minimal impact on phenological traits. Giza 126 had the longest roots and highest stomatal conductance, while Giza 138 consistently maintained a high chlorophyll content. Together, they and Giza 134 are valuable for breeding programs to improve barley drought tolerance. Full article

The effects of integrated nutrient-management (INM) practices on soil quality are essential for sustaining agro-ecosystem productivity. The soil quality index (SQI) serves as a tool to assess the physical, chemical, and biological potential of soils as influenced by various edaphic and agronomic practices. A multiyear (2018–2021) field experiment was performed at the University Organic Research Farm, Narendrapur, West Bengal, India, to investigate the influence of integrated and sole applications of different conventional fertilizers, organic (e.g., vermicompost), and natural farming inputs (e.g., Dhrava Jeevamrit and Ghana Jeevamrit) on SQIs and crop productivity of rice–mustard–green gram-based cropping systems. A total of 12 parameters were selected for the assessment of SQI, amongst which only four, namely pH, organic carbon %, total actinomycetes, and bulk density, were retained for the minimum data set based on principal component analysis (PCA). In this study, the maximum SQI value (0.901) of the experimental soil was recorded in the INM practice of 25% organic and 25% inorganic nutrient inputs, and the rest with natural farming inputs, which augments the SQI by 24% compared to the 100% inorganic nutrient treatment. Amongst the different soil parameters, the highest contribution was from the pH (35.18%), followed by organic carbon % (26.77%), total actinomycetes (10.95%), and bulk density (6.98%). The yields in different cropping systems varied year-wise across treatments. Notably, the highest yield in rainy rice was estimated in the 100% organic treatment, followed by INM practices in the subsequent years, and finally, the combination of organic and natural inputs in the final year. In the case of mustard, the combination of organic and natural inputs resulted in the highest productivity in the initial and last years of study, while the 100% organic treatment resulted in higher productivity in subsequent years. Green gram showed a dynamic shift in yield between the 100% organic and integrated treatments over the years. Further, a strong correlation was also established between the soil physico-chemical parameters and the SQI. Overall, this study concludes that the natural and organic input-based INM practice enhances the soil quality and crop productivity of the rice–mustard–green gram cropping system under the coastal saline zone. Full article

Biostimulants include a wide array of microorganisms and substances that can exert beneficial effects on plant development and growth, often enhancing nutrient uptake and improving tolerance against abiotic and biotic stress. Depending on their composition and time of application, these products can influence plant physiology directly as growth regulators or indirectly through environmental condition changes in the rhizosphere, such as nutrient and water availability. This review evaluated 48 case studies from 39 papers to summarize the effects of biostimulant application on fruit and tuber yields and on the quality of processing tomato and potato in open field conditions. For potato, PGPR bacteria were the main studied biostimulant, whereas the low number of studies on processing tomato did not permit us to delineate a trend. The yield and quality were greatly influenced by cultivars and biostimulant composition, application method, period, and dose. For processing tomato, a positive effect of the biostimulant application on the marketable yield was reported in 79% of the case studies, whereas for potato, the effect was reported in only 47%. Few studies, on processing tomato and potato, also reported data for quality parameters with contrasting results. The variability of crop response to biostimulant application in open field conditions highlights the need for more comprehensive studies. Such studies should focus on diverse cultivars, deeply understand the interaction of biostimulant application with agronomic management (e.g., irrigation and fertilization), and evaluate yield and quality parameters. This approach is crucial to fully understand the potential and limitations of biostimulant applications in agriculture, particularly regarding their role in sustainable crop production. Full article

The use of legumes in rotation is beneficial and is of great importance in sustainable agricultural production in line with the assumptions of the European Green Deal. The aim of the presented research was to evaluate the cultivation of red clover as an undersown crop for spring barley and as a forecrop for winter wheat on the yield and quality of spring barley and winter wheat. To achieve this goal, two long-term static experiments set up in 1955 were used, in which diversified mineral and organic fertilization were used in two rotations: rotation without red clover (sugar beet–spring barley–winter rapeseed–winter wheat) and rotation with red clover (sugar beet–spring barley with undersown red clover–red clover–winter wheat). The obtained results indicate that the Norfolk rotation with red clover, as well as varied fertilization and years of research, influence the yield of plants. The highest grain yields of spring barley (5.7 t ha⁻¹) were ensured by mineral fertilization (NPK) and mineral fertilization in combination with manure (½NPK + ½FM). However, the highest yields of winter wheat grain (6.4 t ha⁻¹) were recorded in the treatments with exclusive mineral fertilization (NPK), significantly lower yields in the treatments where mineral fertilizers were used in combination with manure (5.7 t ha⁻¹) (½NPK + ½FM) and only manure (5.1 t ha⁻¹) (FM). The lowest yields of both cereals were found on soil that had not been fertilized since 1955 (0). The grain yield of spring barley was not significantly differentiated by the sowing method and was similar for spring barley grown with and without undersown red clover. Including legumes in the rotation had a positive effect on the yield of winter wheat. Fertilization had the greatest impact on the protein content in cereal grains. The use of mineral fertilization (NPK) and mineral fertilization in combination with manure (½NPK + ½FM) ensured the highest protein content in the grain of spring barley and winter wheat. Mineral fertilization (NPK) increased the protein content in spring barley grain by 2.9 percentage points compared to the unfertilized treatment (0) and by 2.1 percentage points compared to exclusive manure fertilization (FM), and in winter wheat grain by 2.3 and 1.4 percentage points, respectively. The cultivation of red clover in the rotation also had a positive effect on the protein content in spring barley and winter wheat grains. Full article

Indonesian stingless bee honey (SBH) of Geniotrigona thoracica is popular and traded at an expensive price. Brown rice syrup (RS) is frequently used as a cheap adulterant for an economically motivated adulteration (EMA) in SBH. In this study, authentic Indonesian Geniotrigona thoracica SBH of Acacia mangium (n = 100), adulterated SBH (n = 120), fake SBH (n = 100), and RS (n = 200) were prepared. In short, 2 mL of each sample was dropped directly into an innovative sample holder without any sample preparation including no dilution. Fluorescence intensity was acquired using a fluorescence spectrometer. This portable instrument is equipped with a 365 nm LED lamp as the fixed excitation source. Principal component analysis (PCA) was calculated for the smoothed spectral data. The results showed that the authentic SBH and non-SBH (adulterated SBH, fake SBH, and RS) samples could be well separated using the smoothed spectral data. The cumulative percentage variance of the first two PCs, 98.4749% and 98.4425%, was obtained for calibration and validation, respectively. The highest prediction accuracy was 99.5% and was obtained using principal component analysis–linear discriminant analysis (PCA-LDA). The best partial least square (PLS) calibration was obtained using the combined interval with R²_cal = 0.898 and R²_val = 0.874 for calibration and validation, respectively. In the prediction, the developed model could predict the adulteration level in the adulterated honey samples with an acceptable ratio of prediction to deviation (RPD) = 2.282, and range error ratio (RER) = 6.612. Full article

Effective lettuce cultivation requires precise monitoring of growth characteristics, quality assessment, and optimal harvest timing. In a recent study, a deep learning model based on multimodal data fusion was developed to estimate lettuce phenotypic traits accurately. A dual-modal network combining RGB and depth images was designed using an open lettuce dataset. The network incorporated both a feature correction module and a feature fusion module, significantly enhancing the performance in object detection, segmentation, and trait estimation. The model demonstrated high accuracy in estimating key traits, including fresh weight (fw), dry weight (dw), plant height (h), canopy diameter (d), and leaf area (la), achieving an R² of 0.9732 for fresh weight. Robustness and accuracy were further validated through 5-fold cross-validation, offering a promising approach for future crop phenotyping. Full article

Carbon dioxide flux emissions (CFE) from agricultural areas exhibit spatial and temporal variability, and the best time of collar fixation to the soil prior to the collection of CO₂ flux, or even its existence as a factor, is unclear. The objective of this study was to evaluate the effect of the fixation time of collars that support the soil-gas flux chamber based on the influence of CFE on different pasture management practices: control (traditional pasture management practice) (CON), chisel (CHI), fertilized (FER), burned (BUR), integrated crop-livestock (iCL), and plowing and harrowing (PH). A field study was conducted on the clayey soil of Udults. The evaluations were performed monthly by fixing the PVC collars 30 d and 30 min prior to each CFE measurement. Although a linear trend in CFE was observed within each pasture management practice between the two collar-fixation times, collar fixation performed 30 min prior led to an overestimation of CFE by approximately 32.7% compared with 30 d of collar fixation. Thus, CFE were higher (p ≤ 0.10) in the MC, when compared to the FC, when the CON, BUR, and iCL managements were evaluated. Overall, fixing the collar 30 d prior to field data collection can improve the quality of the data, making the results more representative of actual field conditions. Full article

Integrating advanced technologies such as artificial intelligence (AI) with traditional agricultural practices has changed how activities are developed in agriculture, with the aim of automating manual processes and improving the efficiency and quality of farming decisions. With the advent of deep learning models such as convolutional neural network (CNN) and You Only Look Once (YOLO), many studies have emerged given the need to develop solutions to problems and take advantage of all the potential that this technology has to offer. This systematic literature review aims to present an in-depth investigation of the application of AI in supporting the management of weeds, plant nutrition, water, pests, and diseases. This systematic review was conducted using the PRISMA methodology and guidelines. Data from different papers indicated that the main research interests comprise five groups: (a) type of agronomic problems; (b) type of sensor; (c) dataset treatment; (d) evaluation metrics and quantification; and (e) AI technique. The inclusion (I) and exclusion (E) criteria adopted in this study included: (I1) articles that obtained AI techniques for agricultural analysis; (I2) complete articles written in English; (I3) articles from specialized scientific journals; (E1) articles that did not describe the type of agrarian analysis used; (E2) articles that did not specify the AI technique used and that were incomplete or abstract; (E3) articles that did not present substantial experimental results. The articles were searched on the official pages of the main scientific bases: ACM, IEEE, ScienceDirect, MDPI, and Web of Science. The papers were categorized and grouped to show the main contributions of the literature to support agricultural decisions using AI. This study found that AI methods perform better in supporting weed detection, classification of plant diseases, and estimation of agricultural yield in crops when using images captured by Unmanned Aerial Vehicles (UAVs). Furthermore, CNN and YOLO, as well as their variations, present the best results for all groups presented. This review also points out the limitations and potential challenges when working with deep machine learning models, aiming to contribute to knowledge systematization and to benefit researchers and professionals regarding AI applications in mitigating agronomic problems. Full article

The wheat–maize rotation system in the North China Plain (NCP) has a large amount of crop straw. However, improper crop straw management and blind fertilization lead to nutrient imbalance and accelerated nutrient loss from the soil, ultimately leading to nutrient deficiency affecting the wheat–maize rotation system. In order to explore the effects of nutrient deficiency on the yield and nutrient use efficiency of wheat and maize, the experiment was conducted in a randomized complete block design consisting of five treatments with three replicates for each treatment: (1) a potassium fertilizer deficiency and appropriate nitrogen and phosphate fertilizer treatment (NP); (2) a phosphate fertilizer deficiency and appropriate nitrogen and potassium fertilizer treatment (NK); (3) a nitrogen fertilizer deficiency and appropriate phosphate and potassium fertilizer treatment (PK); (4) an adequate nitrogen, phosphorus, and potassium fertilizer treatment (NPK); and (5) a no-fertilizer treatment (CK). The results showed that, compared with CK, the yields of wheat and maize treated with NPK were increased by 21.5% and 27.5%, respectively, and the accumulation of the dry matter of the wheat and maize was increased by 42.5% and 57.3%. In all the deficiency treatments, the NK treatment performed better in terms of yield compared to the NP and PK treatments, while the NP treatment demonstrated a greater increase in dry matter accumulation. The NPK treatment significantly improved the nitrogen use efficiency (NUE) and nitrogen harvest index (NHI) of the wheat and maize, which resulted in higher nitrogen accumulation in the NPK treatment, and the NP treatment was the best among the other nutrient deficiency treatments. The inorganic nitrogen content showed a similar trend. In conclusion, nutrient deficiency can severely restrict crop growth. Nitrogen deficiency can significantly reduce crop yields. Phosphorus deficiency had a greater impact than potassium deficiency in terms of nutrient absorption and accumulation. Therefore, nitrogen fertilizer application should be emphasized in crop rotation systems, with moderate increases in phosphorus fertilizer application. This practice can effectively improve the nutrient deficiency under the wheat and maize rotation system in the NCP and complete a rational fertilization system. Full article

Accurate dew point estimation is crucial for measuring water condensation in various fields such as environmental studies, agronomy, or water harvesting, among others. Despite the numerous models and equations developed over time, including empirical and machine learning approaches, they often involve trade-offs between accuracy, simplicity, and computational cost. A major limitation of the current approaches is the lack of balance among these three factors, limiting their practical applications under diverse conditions. This research addresses these key challenges by developing a new, streamlined equation for dew point estimation. Using the Magnus–Tetens equation, deemed as the most reliable equation, as a benchmark, and by applying a process of non-linear regression fitting and parametric optimization, a new equation was derived. The results demonstrate high accuracy with a streamlined implementation, validated through extensive data and computational simulations. This study highlights the importance of accurate dew point modeling, especially under variable environmental conditions, provides a reliable solution to existing limitations, paving the way for enhanced efficiency in related processes and research endeavors, and offers researchers and practitioners a practical tool for more effective modeling of water condensation phenomena. Full article

Selenium (Se) is an essential trace element that has various beneficial effects for human healthy. However, the effects of different Se forms and concentrations on growth and development, photosynthetic characteristics and antioxidant capacity are still unclear with regard to the dual grain-and-feed dual-use of ratoon rice (RR). In this study, three concentrations of three different Se forms were applied to RR using the foliar spraying method, and the results showed that Se treatment can increase the Se content of rice grain and straw. All the Se treatments improved the photosynthetic indexes and activities of antioxidant enzymes. The Se and trace elements contents, and the percentages of organic Se and protein Se of brown rice were found to be similar in all three Se forms. A higher organic Se content was found in the grain by spraying sodium selenite and Se-Met, in which the resistant starch (RS) content was increased with the increase in amylose content in grains. The main Se species in the grain was SeMet and the SeMeCys was found only with SeMet treatments. The grain quality showed that all three Se forms increased the consistency of gelatinization. Our study indicated that exogenous Se could improve the nutritional quality of both grain and straw by improving photosynthetic traits and antioxidant enzyme activities, especially sodium selenite and Se-Met. These results underscore the potential of foliar biofortification to enhance the functional component contents of RR grains and provide an insight into the Se enrichment of ratoon rice. Full article

Green tea kombucha (GTK) has emerged as a promising probiotic fermented beverage. Few studies have investigated its effect on human health, mainly focusing on intestinal health, microbiota composition, and metabolomics. The present study is a pioneer in investigating the effect of GTK consumption in individuals with excess body weight. This is a randomized controlled trial, lasting ten weeks, with two groups placed under an energy-restricted diet: control (CG, n = 29), kombucha (KG, n = 30; 200 mL/d). Biological samples and questionnaires were collected before and after the intervention. Microbiota analysis used an amplification of the V4 region of 16S rRNA. Serum untargeted metabolomics used HPLC-TOF mass spectrometry. Intestinal permeability considered the urine excretion of lactulose and mannitol, plasma zonulin, and LPS-binding protein. After the intervention, no differences related to intestinal permeability and microbiota were found between groups, but only the CG had increased fecal pH, lactulose/mannitol ratio, and zonulin. In addition to this, the KG reported lower gastrointestinal symptoms related to motility compared to the CG, and discriminant metabolites (e.g., diethyl malonate) were found strictly in the KG. GTK did not significantly improve gut microbiota and intestinal permeability. However, GTK ameliorated gastrointestinal symptoms and positively influenced the serum metabolome, which may contribute to enhancing the metabolic health of individuals with excess body weight. Full article

Volatile compounds are important components of the flavor quality of Chinese chives, but the distribution of flavor components in different organs of Chinese chives is still unclear. In this experiment, two Chinese chive varieties, ‘Fu Jiu Bao F1’ and ‘Jiu Xing 22’, were taken as test materials, and the contents of volatile compounds in different stages and organs of Chinese chive were determined by HS-SPME/GC-MS technology. A total of 70 and 85 volatile organic compounds (VOCs) were detected in various organs of two varieties at the commodity harvesting stage and physiological maturity stage, respectively. The total volatile compound content of Fu Jiu Bao F1 in the stage of commodity harvesting was higher than that of the physiological maturity stage, but Jiu Xing 22 showed the opposite trend. The organ distribution pattern of total volatile compounds in Fu Jiu Bao F1 and Jiu Xing 22 at the commodity harvesting stage was consistent, as follows: leaf > pseudostem > root. However, at the physiological maturity stage, the distribution pattern of Fu Jiu Bao F1 was different from that of Jiu Xing 22. Further, sulfur-containing compounds at different stages showed different organic distributions. Comprehensive analysis indicated that organic-common and organic-specific compounds varied from different cultivars and growth stages of Chinese chive, and organ differences in VOC distribution were greater than the varieties’ differences based on PCA analysis. The results of this study clarify the composition and organ distribution of volatile compounds in Chinese chive and provide a direction for the study of Chinese chive flavor quality. Full article