Modern techniques that enable high-precision and rapid identification/elimination of wheat seeds infected by Fusarium head blight (FHB) can help to prevent human and animal health risks while improving agricultural sustainability. Robust pattern-recognition methods, such as deep learning, can achieve higher precision in detecting infected seeds using more accessible solutions, such as ordinary RGB cameras. This study used different deep-learning approaches based on RGB images, combining hyperparameter optimization, and fine-tuning strategies with different pretrained convolutional neural networks (convnets) to discriminate wheat seeds of the TBIO Toruk cultivar infected by FHB. The models achieved an accuracy of 97% using a low-complexity design architecture with hyperparameter optimization and 99% accuracy in detecting FHB in seeds. These findings suggest the potential of low-cost imaging technology and deep-learning models for the accurate classification of wheat seeds infected by FHB. However, FHB symptoms are genotype-dependent, and therefore the accuracy of the detection method may vary depending on phenotypic variations among wheat cultivars. Full article

Soil mulching is one of the common measures applied in organic agricultural production which could replace plastic films and protect the environment. In order to fully evaluate the effects of different straw mulching thicknesses on soil health, maize straw was mulched with the thicknesses of 0 cm (CK), 2 cm, 4 cm and 6 cm on soil surface to assess the effects on soil temperature (ST) and moisture (SM), soil pH, soil organic carbon (SOC), total nitrogen (TN), C/N, soil aggregates and soil bulk density (SBD) in a temperate organic vineyard. We found that straw mulching had a significant regulating effect, with soil moisture being elevated with increasing mulching thickness by 5.8%, 9.0% and 11.1% compared with CK. The soil SOC content increased by 3.0%, 2.4% and 2.3%. Although soil pH and C/N significantly (p < 0.05) increased, they fluctuated with increasing mulch thickness. Straw mulching also increased the content of >2 mm soil particle size and elevated the mean weight diameter (MWD) and geometric mean diameter (GMD). The increasing mulching thickness prolonged the effect on the stability of soil aggregates. The 4 cm maize straw mulching thickness has the best effect for ecologically and environmentally managing warm-temperate organic vineyards so it may have a great application prospect on a global scale. Full article

Selecting the appropriate tyre configuration and settings for heavy farm vehicles is important to ensure that soil compaction and power loss in rolling resistance are minimised and traction is optimised. This study investigated the effect of front-wheel assist (FWA, ≈75 kN) and four-wheel drive (4 WD, ≈100 kN) tractors fitted with different tyre configurations (single, dual), tyre sizes and inflation pressures on soil strength (a proxy for soil compaction), and rolling resistance. Single-pass tests were performed on a Typic Argiudoll (≈23% clay, bulk density: 1305 kg m⁻³) managed under permanent no-tillage. Results showed that average power losses in rolling resistance were 7.5 kN and 5 kN for the 4 WD and FWA tractors, respectively. The average rut depth increased by approximately 1.4 times after a pass of the 4 WD compared with the FWA tractor. The soil cone index (0–600 mm depth) increased from 2023 kPa (before traffic) to 2188 and 2435 kPa after single passes of the FWA and 4WD tractors, respectively (p < 0.05). At the centreline of the tyre rut, dual tyres reduced the soil cone index a little compared with single tyres, but they significantly increased the volume of soil over which soil strength, and therefore soil compaction, was increased. For both tractors (regardless of tyre configuration or settings), soil strength increased to the full measured depth (600 mm), but relative changes before vs. after traffic became progressively smaller with increased soil depth. The power loss in rolling resistance was consistently greater with the heavier tractor, and rut depth was directly related to tyre inflation pressure. Full article

Non-destructive acquisition and accurate real-time assessment of nitrogen (N) nutritional status are crucial for nitrogen management and yield prediction in maize production. The objective of this study was to develop a method for estimating the nitrogen nutrient index (NNI) of maize using in situ leaf spectroscopy. Field trials with six nitrogen fertilizer levels (0, 75, 150, 225, 300, and 375 kg N ha⁻¹) were performed using eight summer maize cultivars. The leaf reflectance spectrum was acquired at different growth stages, with simultaneous measurements of leaf nitrogen content (LNC) and leaf dry matter (LDW). The competitive adaptive reweighted sampling (CARS) algorithm was used to screen the raw spectrum’s effective bands related to the NNI during the maize critical growth period (from the 12th fully expanded leaf stage to the milk ripening stage). Three machine learning methods—partial least squares (PLS), artificial neural networks (ANN), and support vector machines (SVM)—were used to validate the NNI estimation model. These methods indicated that the NNI first increased and then decreased (from the 12th fully expanded leaf stage to the milk ripening stage) and was positively correlated with nitrogen application. The results showed that combining effective bands and PLS (CARS-PLS) achieved the best model for NNI estimation, which yielded the highest coefficient of determination (R²_val), 0.925, and the lowest root mean square error (RMSE_val), 0.068, followed by the CARS-SVM model (R²_val, 0.895; RMSE_val, 0.081), and the CARS-ANN model (R²_val, 0.814; RMSE_val, 0.108), which performed the worst. The CARS-PLS model was used to successfully predict the variation in the NNI among cultivars and different growth stages. The estimated R² of eight cultivars by the NNI was between 0.86 and 0.97; the estimated R² of the NNI at different growth stages was between 0.92 and 0.94. The overall results indicated that the CARS-PLS allows for rapid, accurate, and non-destructive estimation of the NNI during maize growth, providing an efficient tool for accurately monitoring nitrogen nutrition. Full article

Testing the reliability of the threshing unit is difficult and thus often neglected before the harvesting season, which can result in breakdown maintenance during peak harvesting time in difficult-to-access areas for sensor mounting. In this paper, the vibration analysis of the threshing condition of the combine harvester was performed by introducing the bracket for inaccessible locations. The Adash A4900 Vibrio M analyzer (Adash spol. s.r.o., Ostrava, Czech Republic) was used for a vibration signal measurement and the DDS Adash software was used for signal processing. The demodulated fast Fourier transform (FFT) root mean square (RMS) (500 Hz–16 kHz) method was used to evaluate the bearing condition and DDS Adash Fault Source Identification Tool (FASIT) technology was used to evaluate other mechanical conditions such as the looseness, misalignment, and unbalance of the threshing unit of the Massey Ferguson series of combine harvesters. Modal and random vibration analyses were performed on the bracket and components and compared to prevent the resonance phenomenon using the Ansys Software (Ansys, Inc., Canonsburg, PA, USA). The constrained modal analysis of the threshing drum was performed to observe the deformation. Decent results were obtained from the method used. The method was again validated by the tangential threshing test bench and successfully determined the bearing fault condition. The method used is an uncomplicated and effective way of performing the bearing analysis of the tangential unit of the combine harvester. Full article

Aiming to solve the problems of the poor uniformity of seed flow discharge and serious damage of traditional straight grooved wheels to improve the performance of air-assisted maize high-speed precision seed metering devices, a staggering symmetrical spiral grooved feeding wheel with maize seeds was designed. To explore the influence of the spiral groove inclination angle and the length of the staggered symmetrical spiral groove feed wheel on the uniformity of seed flow discharge, the spiral groove length l and the spiral groove inclination angle ρ were used as the experimental factors, and the variation coefficient of the increase in seed, a full-factor simulation test was carried out for the test indicators, and it was found that both the inclination angle and the length of the spiral groove have an influence on the uniformity of seed flow discharge, and the influence of the inclination angle of the groove is more significant. Comparing the force of a single seed in the traditional straight grooved wheel and that of the spiral feeding wheel, it is found that the staggered symmetrical spiral grooved feeding wheel can reduce the damage of seed fertilizer. Through a bench test, the spiral groove length was found to be 50 mm, and the groove inclination angles are 30°, 45° and 90°. The test results show the variation trend and simulation results of the fluctuating coefficient of variation of the seed flow discharge in the bench test. The trend of change is basically the same. The inclination angle of the spiral groove is 45° and the uniformity of seed flow discharge is the best when the groove length is 50 mm, indicating that this structure can effectively improve the uniformity of material discharge, and the variation coefficient of seed flow discharge fluctuation is 3.12% and the seed breakage rate is 0.69%. Through the seeding performance test, it is verified that the staggered symmetrical spiral grooved feeding wheel can improve the seeding performance of the pneumatic high-speed precision metering device. When the metering device runs smoothly, the qualified rate reaches more than 90%, and the leakage rate is reduced to 0%. Therefore, the results of this study can provide a reference for research on uniform seeding, drill seeding and the uniform application of granular fertilizer. Full article

Agriculture is an important resource for the global economy, while plant disease causes devastating yield loss. To control plant disease, every country around the world spends trillions of dollars on disease management. Some of the recent solutions are based on the utilization of computer vision techniques in plant science which helps to monitor crop industries such as tomato, maize, grape, citrus, potato and cassava, and other crops. The attention-based CNN network has become effective in plant disease prediction. However, existing approaches are less precise in detecting minute-scale disease in the leaves. Our proposed Channel–Spatial segmentation network will help to determine the disease in the leaf, and it consists of two main stages: (a) channel attention discriminates diseased and healthy parts as well as channel-focused features, and (b) spatial attention consumes channel-focused features and highlights the diseased part for the final prediction process. This investigation forms a channel and spatial attention in a sequential way to identify diseased and healthy leaves. Finally, identified leaf diseases are divided into Mild, Medium, Severe, and Healthy. Our model successfully predicts the diseased leaves with the highest accuracy of 99.76%. Our research study shows evaluation metrics, comparison studies, and expert analysis to comprehend the network performance. This concludes that the Channel–Spatial segmentation network can be used effectively to diagnose different disease degrees based on a combination of image processing and statistical calculation. Full article

Nitrogen fertilizer application is conditioned closely by the amount of rainfall and its distribution. The current study aims at studying the effect of nitrogen (N) application rate on grain yield (GY), grain protein content (GPC), and nitrogen use efficiency (NUE) of durum wheat under Algerian semiarid conditions. Field trials were conducted during two contrasting and successive growing seasons (a dry year = 2016–2017 and a wet year = 2017–2018) on a local variety named Bousselam. A randomized complete block design (RCBD) was used with four replicates. Seven gradual treatments of fertilizer rate were studied: T1 = 0 unity of nitrogen (UN), T2 = 100 UN, T3 = 110 UN, T4 = 120 UN, T5 = 130 UN, T6 = 140 UN, and T7 = 150 UN. Results showed a significant difference between the dry and wet years. Only the GPC was higher in the dry year compared to the wet year having a difference of 2.94%. However, all other studied parameters were higher in the wet year, which resulted in a yield difference of 4.38 t ha⁻¹. In addition, a significant effect of N rate on GY, thousand grain weight (TGW), and GPC was observed. A considerable difference between 120 UN and 150 UN was not noted in both years of study. Furthermore, the agronomic efficiency (AE) increased significantly with rainfall amount achieving a difference of 16.2 kg·kgN⁻¹ between years. Finally, the results showed that using a high N amount led to a decrease in AE. Based on GY, apparent recovery efficiency (ARE), agronomic efficiency (AE), and marginal rate return (MRR) recorded in both years, the nitrogen application rate of 120 UN is recommended to be applied to wheat crops in Algerian semiarid conditions. Full article

The interaction between plant roots and rhizobacterium communities plays a crucial role in sustainable agriculture. We aimed to assess the effects of Sphingobium yanoikuyae SJTF8 on rice seed germination and development, as well as to observe the effects of different concentrations of S. yanoikuyae SJTF8 on the root systems of rice seedlings. The bacteria are best known for their role in the bioremediation and biodegradation of pollutants, and thus far, there is research that supports their agricultural prospects. The experiment comprised five different S. yanoikuyae SJTF8 concentrations: SP-y 8 (10⁸ CFU/mL); SP-y 7 (10⁷ CFU/mL); SP-y 6 (10⁶ CFU/mL); SP-y 5 (10⁵ CFU/mL); SP-y 4 (10⁴ CFU/mL). We used sterilized water as the control treatment. The bacteria triggered the synthesis of IAA, while the seedling root lengths substantially increased on the 12th day after germination. The high application concentrations of S. yanoikuyae SJTF8 resulted in higher IAA production (with the SP-y 7 and SP-y 8 concentrations ranging from 151,029 pg/mL to 168,033 pg/mL). We found that the appropriate concentrations of S. yanoikuyae SJTF8 when applied as an inoculant were SP-y 7 and SP-y 6, based on the increased root growth and biomass production. The bacteria were also able to solubilize phosphorous. The growth response from the rice seedlings when inoculated with S. yanoikuyae SJTF8 presents the potential of the bacteria as a growth promotor. Its application in rice cultivation could be a sustainable approach to rice production. Full article

Climate change has wide-reaching consequences for agriculture by altering both the yield and nutritional composition of grains. This poses a significant challenge for the poultry industry which relies on large quantities of high-quality feed grains to support meat and egg production. The existing literature shows that elevated atmospheric carbon dioxide concentrations (eCO₂), heat and drought overall reduce grain yield and quality. However, these results are inconsistent, with some studies reporting small or large decreases and others even indicating potential improvements. These variations may occur because many studies only investigate one climate factor at a time, without considering interactions between factors. Additionally, most studies investigate just one grain type, rather than comparing grains and their morphophysiological differences. The present review offers a novel approach by investigating how eCO₂, heat and drought interactively affect both the yield and nutritional composition of four key animal feed grains: wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), maize (Zea mays L.) and sorghum (Sorghum bicolour L. Moench). The photosynthetic pathway is a key determinant of a plant’s response to climate factors, so this review compares grains with both C₃ photosynthesis (wheat and barley) and C₄ photosynthesis (maize and sorghum). The present review found that eCO₂ may promote starch synthesis in C₃ grains of wheat and barley, thereby improving grain yield but diluting protein, lipid, vitamin and mineral concentrations. This potential yield improvement is further counteracted by heat and drought which limit the photosynthetic rate. Unlike wheat and barley, C₄ photosynthesis is not CO₂-limited, so neither the yield nor the nutritional quality of maize and sorghum are significantly affected by eCO₂. On the other hand, heat stress and drought reduce photosynthesis in maize and sorghum and may offer minimal increases in nutrient concentrations. This review highlights that while eCO₂ may increase the yield of wheat and barley grains, this effect (i) dilutes nutrient concentration, (ii) is counteracted by heat and drought, and (iii) does not benefit C₄ grains maize and sorghum. An additional novel insight is offered by discussing how the impacts of climate change on animal feed production may be mitigated using alternative crop management practices, plant breeding, feed processing and enzyme supplementation. Full article

Brazil is among the world’s leading food producers and exporters. The opportunity arose to examine and analyse dynamics of spatiotemporal of major agricultural crop and animal commodities within Brazil. An investigation was carried out on shifts in distribution density across Brazil’s different agricultural production regions between 1990 and 2015. This focused mainly on the midwest region, Brazil’s main agricultural frontier in the 21st century. This process enabled an analysis of the potential areas for maintenance and expansion of food supply chains and confirmed an increase in agricultural production in country’s central region. Geographical transformations were noted in the midwest region’s interior and its frontier with the Amazon biome. Over the study period, geographical midpoints of some key agricultural commodities (e.g., soybean, maize) and beef cattle production shifted towards the midwest’s interior, whereas milk, poultry, and pork production shifted southward. A vital issue in discussing contemporary rural areas, agricultural food production is tied to the quality of life, food supply, distribution, and consumption, as well as social, economic, and spatial inequalities. The development of science and technology applied to agriculture has implications regarding production growth and innovation targeted toward guaranteeing sustainable long-term production. Full article

Rice (Oryza sativa L.) is the main staple food of more than 50% of the world’s population. However, global production may need to increase by more than 70% before 2050 to meet global food requirements despite increasing challenges due to environmental degradation, a changing climate, and extreme weather events. Rice production in Ecuador, mainly concentrated in lowland tropical plains, declined in recent years. In this paper, we aim to calibrate and validate Kobayashi’s ‘Very Simple Model’ (VSM) and, using downscaled corrected climate data, to quantify the potential impact of climate change on rice yields for Ecuador’s two main rice-growing provinces. The negative impact is expected to be highest (up to −67%; 2946 tons) under the Representative Concentration Pathway (RCP) 8.5, with a lower impact under RCP 2.6 (−36%; 1650 tons) yield reduction in the Guayas province. A positive impact on yield is predicted for Los Ríos Province (up to 9%; 161 tons) under RCP 8.5. These different impacts indicate the utility of fine-scale analyses using simple models to make predictions that are relevant to regional production scenarios. Our prediction of possible changes in rice productivity can help policymakers define a variety of requirements to meet the demands of a changing climate. Full article

Manure application influences ammonia (NH₃) and greenhouse gas emissions; however, few studies have quantified the effects of manure application methods and timing on NH₃, nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) fluxes simultaneously. We evaluated surface-applied liquid manure application with disk incorporation versus injection on NH₃, N₂O, CO₂, and CH₄ fluxes in central Wisconsin corn silage (Zea mays L.) plots during pre-plant (PP) and sidedress (SD) application windows from 2009 to 2011. Manure treatments were PP injection (PP-Inject) and injection at sidedress time (SD-Inject) to growing corn, along with two incorporation times for PP surface application (within 24 h—PP-1-hr; within 3 days—PP-3-day). Mean NH₃ emissions were 95% lower for injected treatments compared to surface application in both years, with larger losses for PP-3-day and SD-Surf. While N₂O fluxes were generally low, larger increases after manure application were associated with injection and triggered by soil moisture/temperature changes. Mean CO₂ and CH₄ were unaffected by manure treatments and influenced more by weather. Overall, injection conserved more available soil N while contributing to modest N₂O emission, suggesting manure injection may offer greater agri-environmental benefits on the whole over surface application. Full article

Ozon is considered an environmentally friendly, low-cost antimicrobial treatment and an effective alternative to chemical pesticides. Ozonated water in the form of droplets and mist has been used in two concentrations (4 and 2 mg/L) against three biomasses (10², 10⁴, and 10⁶ CFU/mL) of phytopathogenic bacteria Erwinia amylovora, Pseudomonas syringae, and Agrobacterium tumefaciens and fungus Botrytis cinerea that infest a wide range of crops worldwide and pose a threat to global food production. Regardless of concentration, ozone dissolved in water showed a pronounced inhibitory effect on phytopathogenic bacteria when applied in the form of droplets. However, the effect was only detected when the bacterial load was not higher than 10⁴ CFU/mL, indicating the necessity to treat the crops and plant materials when the bacterial load is still manageable. Unlike bacterial phytopathogens, B. cinerea was the most susceptible to treatment with aqueous ozone, regardless of the applied biomass, ozone concentration, or type of application. Total removal of high biomass of B. cinerea was achieved even with the lowest ozonated water concentration thus underlying the power of ozone in treating this particular fungal contamination. Full article

Stahlianthus thorelii Gagnep is a plant belonging to the family Zingiberaceae, widely distributed in Asian countries like China, Thailand, India and Vietnam. In traditional oriental medicine, this plant is usually used to treat hemorrhage, heavy menstruation, poor digestion, rheumatism and bone/joint pain (tuberous roots). This research article presents the results of in vitro growth experiments on S.thorelii Gagnep using tubers as explants. The samples are grown in MS media enriched with BAP growth stimulant concentrations of 5.0 mg L⁻¹ and a kinetin concentration of 4.0 mg L⁻¹, yielding 5.55 ± 0.59 and 5.48 ± 0.87 shoots/explants, respectively. Once the plants reached a height of 3.0–4.0 cm, we inoculated 2.0–3.0 leaves with a MS rapid proliferation medium treated with BAP or NAA growth agents alone or in combination. The most shoots (7.54 ± 0.79 shoots/explants) were produced by the medium enhanced with 3.0 mg L⁻¹ BAP and 0.5 mg L⁻¹ NAA after 8 weeks of cultivation. The greatest root/shoot induction of 26.17 ± 1.5 was achieved with the medium that had been treated with 0.5 mg L⁻¹ NAA and 0.5 mg L⁻¹ IBA, which was prepared using the MS media that was administered alone or in combination with NAA and IBA for in vitro shoot rooting. Highest percentage of survival (100%) was observed when tissue cultured plantlets were acclimatized in soil:sand:compost (1:1:1). Full article