Agronomy, Volume 14, Issue 5 (May 2024) – 89 articles

To explore how endophytic microbial compositions in amaranth roots are influenced by various fertilization methods and to determine whether these microbes are associated with amaranthin formation, we conducted an analysis of the endophytic microbial community structure. The roots of amaranth plants subjected to different fertilization treatments—conventional fertilization without potassium (NP), conventional fertilization without phosphorus (NK), conventional fertilization without nitrogen (PK), and balanced fertilization (NPK)—were examined. The results showed that the proportions of Streptomyces, Actinospica, and Burkholderia-Caballeronia-Paraburkholderia in the amaranth roots under the balanced fertilization (NPK) treatment were all greater than those in the amaranth roots under the nitrogen (PK), phosphorus (NK), and potassium (NP) deficiency fertilization treatments. In contrast, the proportions of Phenylobacterium, Acrocalymma, Neocosmospora, Fusarium, Acidovorax, Gibellulopsis, Cladosporium, Dactylonectria, and Gibberella in the amaranth roots under the nutrient deficiency fertilization (NP, NK, and PK) treatments were higher than those in the amaranth roots under the balanced fertilization treatment. Additionally, a significantly positive correlation was found between Streptomyces and the amaranthin content. Furthermore, Acrocalymma, Neocosmospora, and Fusarium exhibited significantly negative correlations with the amaranthin content. The above results suggested that endophytes could easily colonize in amaranth roots as beneficial microorganisms under balanced fertilization conditions. In other words, the balanced fertilization (N, P and K fertilizers are 188.0, 53.0 and 50.0 kg·hm⁻², respectively) could recruit more beneficial endogenous microorganisms in amaranth roots for improving their growth and quality. Full article

An extensive, publicly available dataset is presented—the LAR Broccoli dataset—which contains 20,000 manually annotated images of broccoli heads captured from a moving tractor at an organic farm in the UK. The dataset contains images of the same row of broccoli heads recorded at 30 frames per second (fps) with three different cameras. Two off-the-shelf, relatively low-cost depth-sensing cameras were used, with the tractor moving at a speed of around 1 km/h, in addition to a webcam, with the tractor moving twice as fast. The utility of the dataset is demonstrated in four ways. First, three different state-of-the-art detector models were trained on the dataset, achieving an overall mean Average Precision (mAP) score of over 95% for the best-performing detector. The results validate the utility of the dataset for the standard task of in-field broccoli head recognition. Second, experiments with transfer learning were conducted, initialised with a smaller pre-trained broccoli detection model, and refined with the LAR Broccoli dataset. Third, we assessed the advantages of transfer learning not only using mAP but also according to time and space requirements for training models, which provides a proxy metric for energy efficiency, a practical consideration for real-world model training. Fourth, the cross-camera generalisation among the three camera systems was compared. The results highlight that testing and training detector models using different camera systems can lead to reduced performance, unless the training set also includes some images captured in the same manner as those in the test set. Full article

The Chinese Loess Plateau has undergone extensive revegetation to restore degraded land and enhance carbon sequestration. However, soil organic carbon (SOC) sequestrated in the soil profiles of deep-rooted plants has not been fully studied. Here, we investigated the SOC within a 0–23 m profile in farmlands and apple orchards converted from farmlands with different ages (A5, <5 years; A10, ~10 years; A15, ~15 years; A20, >20 years) and the controlling factors on three loess tablelands (Changwu, Qingyang, and Luochuan). The results show that SOC stocks among farmlands and orchards showed no significant difference (p = 0.88); however, SOC stocks showed a trend with tree ages, i.e., a decrease for A5 and A10 but an increase for A15 and A20. For the vertical variability, the SOC stock was the highest within 0–1 m, regardless of the standing age; however, the SOC stock in this layer only accounted for 8.8% of the total SOC stock (97.93 ± 9.18 kg m⁻²). Climate accounted for 82% of the variations and controlled the changes in SOC in the 0–1 m range, while soil texture dominated the SOC in the soil below 1 m, accounting for 57% of the SOC variations. The variations in SOC in the thick, unsaturated zones provide implications for future land use management and the sustainability of apple orchards in arid regions. Full article

Bioconversion in biorefineries is a way to valorize residues from agriculture and food processing. Pretreatment is an important step in the bioconversion of lignocellulosic materials, including crop residues. This Special Issue includes nine articles on several pretreatment and bioconversion approaches applied to different agricultural residues and food-processing by-products. The materials addressed in this collection cover straw from wheat, rye, and miscanthus, olive tree pruning residue, almond shells and husks, avocado waste, sweet sorghum bagasse, soybean meal, and residues of non-edible oilseeds. Full article

Cowpea is one of the most popular dry-land legumes cultivated for food and forage in arid and semi-arid areas. Genetic diversity for global germplasm can be organized into core collections providing optimum resources to serve breeding requirements. Here, we present diversity analysis and genome-wide association study (GWAS) results for part of the cowpea core collection of the United States Department of Agriculture (USDA) along with breeding line controls. Included in the analysis were a total of 373 accessions analyzed with 6880 Single Nucleotide Polymorphism (SNP) markers from Genotyping by Sequencing (GBS). Population structure differentiated accessions into two groups irrespective of geographical origin and formed three clusters based on taxa upon phylogenetic analysis. A total of 56 SNPs were significantly associated to nine traits including pod length (25 Quantitative Trait Nucleotides, QTNs), seed anti-oxidant content (7 QTNs), dry pod color (7 QTNs), plant maturity (5 QTNs), flower color (5 QTNs), seed weight (4 QTNs), tolerance to low phosphate (1 QTN), growth habit (1 QTN), and response to rock phosphate (1 QTN) using Bayesian-information, Linkage-disequilibrium Iteratively Nested Keyway (BLINK), and Fixed and random model Circulating Probability Unification (FarmCPU) association models. Key genes related to all significant SNPs were identified based on annotations of the cowpea reference genome, including a flavonoid gene controlling flower color (Vigun08g040200.1), a root nodulation regulator for tolerance to low phosphate (Vigun11g168000.1), and numerous genes involved in signaling, biosynthesis, metabolite transport, and abiotic stress. Our results highlight the importance of maintaining public phenotyping databases at USDA and strengthening collaborations for data collection in cowpea to maximize research impacts. Full article

Organic soil amendments are a sustainable option for modifying soil structure and improving plant performance in the face of abiotic stressors such as drought and soil salinity. Of these amendments, biochar and compost have the added benefits of carbon sequestration and waste recycling. Establishment studies were conducted on tall fescue (Festuca arundinacea Schreb.) (syn., Schedonorus arundinaceus (Schreb.) Dumort and Lolium arundinaceum (Scop.) Holub) to assess the potential inhibition of establishment by compost and biochar products. Both green waste and biosolid compost impaired establishment rates, while biochar did not. In the field study, the green waste treatments were slower to reach 50% coverage than the untreated control or when biochar was added to the soil, but all treatments reached 75% and final coverage at a similar rate. Field application of compost had a positive effect on final root length and volume but a negative effect on tall fescue roots in the greenhouse. The negative effect of higher salts and volatiles in the biosolids compost was reduced when biosolids and biochar were incorporated into the soil simultaneously. This work represents one of the only large-scale field studies on turfgrass establishment comparing the impact of biochar and compost products on turfgrass establishment. Full article

Wind machines based on the air disturbance method are progressively employed to mitigate frost damage within the agricultural machinery frost protection. These devices are utilized during radiative frost nights to disrupt near-surface thermal inversion through air mixing. Despite this application, the fundamental mechanisms underlying these mixing processes are not well comprehended. In this research, numerical simulations were conducted using COMSOL Multiphysics software version 6.0 to simulate the flow and heat transfer processes between the thermal airflow and both the tea canopy and stems. The results indicated that due to obstruction from the canopy cross-section, the airflow velocity on the contact surface rapidly increased. As the airflow further progressed, the high-speed region of the airflow gradually approached the canopy surface. Turbulent kinetic energy increased initially on the windward side of the canopy cross-section and near the top interface. On the windward side of the canopy, due to the initial impact of the thermal airflow, rapid heating occurred, resulting in a noticeable temperature difference between the windward and leeward sides within a short period. In the interaction between airflow and stems, with increasing airflow velocity, fluctuations and the shedding of wake occurred on the leeward side of the stems. The maximum sensible heat flux at the windward vertex of the stem increased significantly with airflow velocity. At an airflow velocity of 2.0 m/s, the maximum heat flux value was 2.37 times that of an airflow velocity of 1.0 m/s. This research utilized simulation methods to study the interaction between airflow and tea canopy and stems in frost protection, laying the foundation for further research on the energy distribution in tea ecosystem under the disturbance of airflow for frost protection. Full article

Fig types such as “Smyrna” and “San Pedro” require pollination (called caprification in fig cultivation) to produce a commercial crop, based on the crop and pollination characteristics of figs. Caprification is the process of hanging caprifig (male fig) fruits on female fig trees to ensure the transfer of pollen from the female fig to the caprifig by a wasp (Blastophaga psenes) that lives within the caprifig. It is necessary to extend the caprification period by using caprifig genotypes that ripen at different times, as female fig fruits ripen gradually. However, as caprifigs may not be continuously available for pollinating female figs, storing suitable caprifigs is necessary. The aim of this study was to assess changes in Blastophaga psenes, the duration of Blastophaga’s exit, and the viability of pollen from caprifigs of different genotypes (16 08 05, 16 08 09, 16 08 10, 16 09 10, and 16 ZF 08) stored for caprification. These stored caprifig genotypes were subsequently used for pollination three times at 8-day intervals, after which their impact on the set and quality of the edible fig fruits was evaluated. According to the average data, at the end of storage, the least B.psenes loss was obtained from the 16 08 05 (61.03%) genotype, and the highest was obtained from the 16 09 10 (67.00%) genotype. Pollen germination tended to increase with the storage of caprifig fruits, but this increase was not linear. After storage, the 16 08 09 and 16 09 10 genotypes exhibited greater pollen germination. The highest fruit set and quality were obtained when the 16 08 09 and 16 09 10 genotypes were used as pollen sources. Furthermore, since the 16 08 10 genotype is the latest ripening caprifig genotype, it has been determined that it can pollinate late-ripening “Bursa Siyahı” fruits. Principal component and path analysis demonstrated that pollen viability and germination rate were crucial in selecting caprifig genotypes for fruit set and quality. Full article

Poppy is a minor agronomic field crop that is cultivated under a UN license. It is known for its alkaloids and seeds, and, rarely, for the latter’s use in ethnomedicine. Changing climate conditions could lead to the need for alternate areas for poppy cultivation in Türkiye. This experiment was conducted in Ankara, which is not a poppy production area. The morphological characteristics and oil characteristics of 19 Turkish poppy genotypes were determined over two years. According to the results, the emergence time was between 10 and 22 days, the flowering time ranged from 197 to 214 days, while the harvest maturation time was between 250 and 269 days. The plant height varied from 75.8 to 97.5 cm, the weight of 1000 seeds ranged from 305.0 to 428.0 mg, and the weight of the seeds per plant was between 2.95 and 5.78 g. Furthermore, the yield ranged from 100.7 to 202.3 kg da⁻¹, the fat content was between 38.8 and 44.1%, and the protein content ranged from 15.9 to 18.4%. The linoleic acid content ranged from 66.77% to 75.60%, the oleic acid content ranged from 10.78% to 19.46%, and the palmitic acid content ranged from 8.38% to 9.90%. The highest yield in Ankara was obtained from the Çelikoğlu cultivar. Full article

Berberis amurensis var. latifolia Nakai is a plant native to the Ulleung Island in Korea. In this study, we aimed to identify seed dormancy-breaking and germination requirements of this species using water imbibition experiments, gibberellic acid (GA₃) treatment (0, 10, 100, or 1000 mg/L), cold stratification (0, 2, 4, 8, or 12 weeks at 5 °C), move-along experiments, and phenological studies. In the water imbibition experiment, the seed weight increased by more than 120% after 24 h. Analysis of the internal morphological characteristics of the seeds revealed that the embryo in freshly matured seeds was fully grown and did not grow thereafter. The final germination percentages after 12 weeks of cold stratification at 5 °C were 49 ± 6.4% and 63 ± 3.4% under light and dark conditions, respectively. In move-along and phenological studies, a longer cold stratification treatment period resulted in a higher germination percentage; however, the warm stratification treatment did not affect germination significantly. The GA₃ treatment had little effect on seed germination. Therefore, we concluded that B. amurensis var. latifolia seeds have intermediate physiological dormancy, and pre-treatment with cold stratification for 12 weeks and incubation in the dark are required for effective seed propagation. Full article

Hydrothermal carbonization (HTC) has emerged as a pivotal technology in the battle against climate change and fosters circular economies. Operating within a unique reaction environment characterized by water as a solvent and moderate temperatures at self-generated pressures, HTC efficiently converts biomass residues into valuable bio-based products. Despite HTC’s potential—from the management of challenging biomass wastes to the synthesis of advanced carbons and the implementation of biorefineries—it encounters hurdles transitioning from academic exploration to industrial implementation. Gaps persist, from a general comprehension of reaction intricacies to the difficulty of large-scale integration with wastewater treatments, to the management of process water, to the absence of standardized assessment techniques for HTC products. Addressing these challenges demands collaboration to bridge the many scientific sectors touched by HTC. Thus, this article reviews the current state of some hot topics considered crucial for HTC development: It emphasizes the role of HTC as a cornerstone for waste management and biorefineries, highlighting potentialities and challenges for its development. In particular, it surveys fundamental research aspects, delving into reaction pathways, predictive models, analytical techniques, and HTC modifications while exploring HTC’s crucial technological applications and challenges, with a peculiar focus on combined HTC, wastewater integration, and plant energy efficiency. Full article

The reason for this examination is today’s wide usage of chlorophyll a fluorescence (ChlF) among researchers worldwide to measure photosynthetic efficiency. Although the instructions of the ChlF measuring device clearly emphasize the need for methodology adjustments, depending on the specific plant species, many researchers use the usual 30 min of dark adaptation before measurement. Namely, before any ChlF measurement, it is necessary to determine the specific duration of the leaf adaptation to the conditions of darkness of each plant tissue. Because of the numerous uses of the ChlF measurements, we decided to conduct this research to determine whether the appearance of the curves and parameter values depend on the time of sunflower leaf tissue adaptation to dark conditions. Therefore, this research aimed to examine the optimal adaptation time of sunflower tissue to dark conditions to obtain timely precise measurements and credible appearance of ChlF transient curves as well as accurate parameter values. The research was carried out on the sunflower hybrid Luka with 0, 15, 30, 45, 60, 75 and 90 min of dark adaptation in the vegetative, budding and flowering stages in the field conditions. According to the analyzed transient curves and parameters, it was determined that sunflower leaves should be kept in dark conditions for at least 15 min before the measurement of ChlF, which leads to the complete oxidation of PSII and the electron transport chain prior to a saturating pulse of light. Full article

Soil salinization is one of the main hazards affecting the sustainable development of agriculture in the Hetao Irrigation District (HID) of Inner Mongolia. To grasp the water and salt transport patterns and spatial–temporal distribution characteristics of the HID at the regional scale, the improved Soil and Water Assessment Tool with a salinity module (SWAT-Salt) model was used to establish the distributed water and salt transport model for the watershed in this study. The results demonstrated that the modified model could more accurately represent the process of water and salt changes in the HID. The coefficient of determination (R²) in the simulation of streamflow and discharge salt loading was 0.83 and 0.86, respectively, and the Nash–Sutcliffe efficiency (NSE) was 0.80 and 0.74, respectively. Based on this, different hydrological processes (surface runoff, lateral flow, groundwater, soil seepage) as well as spatial–temporal distribution characteristics of water salinity in groundwater and soil were analyzed in the HID. Differences in groundwater and soil salinity in different land uses and soil types were also compared. Of these, surface runoff and lateral flow salt discharge loading are concentrated in the southwestern portion of the basin, while groundwater salt discharge loading is concentrated in the eastern as well as southwestern portions of the basin. The salt discharge loading from groundwater accounts for about 98.7% of the total salt discharge loading from all hydrological pathways and is the major contributing part of salt discharge from the irrigation area. Soil salinity increases gradually from west to east. Groundwater salinity (2946 mg/L) and soil water electrical conductivity (0.309 dS/m) were minimized in the cropland. Meanwhile, rational allocation of irrigation water can appropriately increase the amount of salt discharge loading. In conclusion, the model could provide a reference for the investigation of soil salinization and water–salt management measures in irrigation areas. Full article

Aminopyralid (2-pyridine carboxylic acid, 4-amino-3, 6-dichloro-2-pyridine carboxylic acid) is an auxin herbicide that has been used widely to control broadleaf weeds in pasture and hay fields. With no post-application withdrawal time, aminopyralid absorbed into forage material can contaminate compost feed stocks such as hay, grass bedding material, and manure. Composts derived from such feed stocks raises concerns about after-effect injuries to sensitive crops by residual aminopyralids. Biochar (BC) additive may affect the composting process and immobilizes organic pollutants. This study examined the effect of composting dairy manure/sawdust 1:1 mixture containing 10 ppb (wet) of aminopyralid with 0%, 2%, 4%, and 10% (w/w) BC levels on chemical and biological characteristics of compost, residual aminopyralid concentration, and intensity of plant injury to tomato (Lycopersicon esculentum L.) plants after composting in 140 L plastic rotary drum reactors for two 6-month cycles. Biochar addition decreased organic matter degradation and intensified reduction in residual aminopyralid levels in a dose-dependent manner. Composting with BC concentrated more N, P, and K, caused mild plant injuries, and increased the above ground biomass compared to the no BC incorporation. Addition of BC for composting aminopyralid-contaminated dairy manure can increase the phyto safety level of compost while enhancing the key fertilizer values. Full article

Maize/peanut intercropping is practiced widely to increase land productivity and considered a sustainable way for using and saving resources through peanut’s complementary N source via biological N₂ fixation. Our study aims to understand how maize/peanut intercropping affects the nodulation of peanuts under water-limiting conditions and different nitrogen inputs. A two-year micro-plot experiment in 2015–2016 and a two-year field experiment in 2017–2018 were conducted to quantify nodulation in maize/peanut intercropping and sole peanut cropping under four N fertilization rates (N-free, low, medium, and high N) in rain-fed water-limited conditions. In the micro-plot experiment, intercropped peanuts increased nodule biomass compared to sole peanuts. The nodule number of intercropped peanuts was 51.6% (p = 0.001) higher than that of sole cropped peanuts, while nodule weights did not differ at high N fertilization rates and were lower in the no-N fertilization control. However, the results were different in the field experiment. Both the nodule number and single weight of the sole cropped peanut were 48.7% (p = 0.020) and 58.9% (p = 0.014) higher than that of the intercropped peanut. The ratio of the nodule weight to aboveground dry matter at the beginning peg in the dry year of 2017 was lower in intercropping than sole cropping, especially at low N fertilization rates. The potential increase in nodulation found in a well-controlled micro-plot environment might be limited by strong water and light competitions in field conditions. The results could contribute to the understanding of interspecific interactions in cereal/legume intercropping. Full article

Water availability is a limiting factor for plant production, especially in Brazilian semi-arid regions. The main aim of the study was to investigate the physiological effects of drought during the fruiting stage of watermelon cultivation. A completely randomized block design with four replications and six treatments varied by the number of lateral drip tapes (1 or 2) and the duration of drought stress (0, 4, and 8 days) was used. The following parameters were evaluated: relative chlorophyll content, relative leaf water content, electrolyte leakage, CO₂ assimilation (A), stomatal conductance (g_s), internal CO₂ concentration, leaf temperature, transpiration (E), water use efficiency (WUE), carboxylation efficiency (CE), yield, thickness, diameter, length, and fruit °brix, at 4 and 8 days of drought. Drought negatively affected photosynthesis, particularly in treatments with a single dripper and 4 days of drought, resulting in reductions of up to 60% in A, 68% in g_s, 44% in E, 58% in WUE, and 59% in CE, but did not have a significant effect on watermelon yield after 4 or 8 days of irrigation. It was concluded that drought influences the physiological responses of watermelon plants, mainly in reducing photosynthesis, but does not drastically affect fruit productivity in short periods of stress. Full article

The premixtures flufenacet plus diflufenican and flufenacet plus diflufenican plus metribuzin are two herbicides recently registered in Greece for weed control in bread wheat and barley with application early post-emergence to the crop (1st–3rd leaf growth stage). To evaluate the selectivity of these new herbicides, pot experiments were conducted by applying flufenacet plus diflufenican at 240 + 120 g ai ha⁻¹ and flufenacet plus diflufenican plus metribuzin at 119.7 + 119.7 + 44.8 g ai ha⁻¹ to bread wheat and barley, at 1st (BBCH-11), 2nd (BBCH-12) and 3rd (BBCH-13) leaf growth stage. The efficacy of the herbicides at the above-mentioned rates in pre-emergence application was also tested on three ALS/ACCase herbicide-resistant populations of Lolium rigidum L. in comparison with the pre-emergence herbicides prosulfocarb and chlorotoluron plus diflufenican at 3200 g ai ha⁻¹ and 1380 + 92 g ai ha⁻¹, respectively. The results revealed decreased selectivity of both premixtures when applied at BBCH-11 for both winter cereals, with flufenacet plus diflufenican being less selective compared to flufenacet plus diflufenican plus metribuzin. Both herbicides highly controlled the three herbicide-resistant L. rigidum populations. The results indicated that both premixtures are effective chemical options for the management of herbicide resistant L. rigidum. To ensure crop safety and optimize efficacy, application at BBCH-12 is recommended. Full article

Late leaf spot (LLS) is an important disease of peanut, causing global yield losses. Developing resistant varieties through breeding is crucial for yield stability, especially for smallholder farmers. However, traditional phenotyping methods used for resistance selection are laborious and subjective. Remote sensing offers an accurate, objective, and efficient alternative for phenotyping for resistance. The objectives of this study were to compare between regression and classification for breeding, and to identify the best models and indices to be used for selection. We evaluated 223 genotypes in three environments: Serere in 2020, and Nakabango and Nyankpala in 2021. Phenotypic data were collected using visual scores and two handheld sensors: a red–green–blue (RGB) camera and GreenSeeker. RGB indices derived from the images, along with the normalized difference vegetation index (NDVI), were used to model LLS resistance using statistical and machine learning methods. Both regression and classification methods were also evaluated for selection. Random Forest (RF), the artificial neural network (ANN), and k-nearest neighbors (KNNs) were the top-performing algorithms for both regression and classification. The ANN (R²: 0.81, RMSE: 22%) was the best regression algorithm, while the RF was the best classification algorithm for both binary (90%) and multiclass (78% and 73% accuracy) classification. The classification accuracy of the models decreased with the increase in classification classes. NDVI, crop senescence index (CSI), hue, and greenness index were strongly associated with LLS and useful for selection. Our study demonstrates that the integration of remote sensing and machine learning can enhance selection for LLS-resistant genotypes, aiding plant breeders in managing large populations effectively. Full article

Many croplands in the tropics of China have been converted over the last decades into areca nut plantations due to their high economic returns. This land-use transition was accompanied by changes in agricultural practices such as soil moisture regimes and fertilizer inputs, which may affect soil organic carbon (SOC) and its fractions, especially in tropical soils with low fertility and high nitrogen loss. Yet, how the time since land-use transition from rice paddy cultivation to areca nut plantations affects soil carbon dynamics and their underlying mechanisms in the tropics of China remains elusive. Here, areca nut plantation soils with different ages (2, 5, 10, 14, and 17 years) and paddy fields in the tropical region of China were investigated. The study result indicates that the contents of dissolved organic carbon (DOC), particulate organic carbon (POC), easily oxidized organic carbon (EOC), light organic carbon (LFOC), and microbial biomass carbon (MBC) decreased significantly with increased time since land-use transition from rice paddy cultivation to areca nut plantations. Similarly, the ratios of DOC/SOC, MBC/SOC, POC/SOC, LFOC/SOC, and EOC/SOC decreased significantly with increased time since land-use transition. Compared with the paddy soil, the carbon pool management index decreased by 36.6–76.7% under the areca nut plantations, concluding that increasing the time since land-use transition from rice paddy cultivation to areca nut plantations with high application rates of chemical fertilizers resulted in reduced soil active carbon fractions and SOC supply capacity. Therefore, agricultural practices such as the use of organic fertilizers should be applied to improve the soil’s ability to supply organic carbon in managed plantation ecosystems in the tropics of China. Full article

This study investigates the growth dynamics and heavy metal immobilization in Sudan grass cultivated on substrates composed of electrolytic manganese residue (EMR), phosphogypsum, and chili straw biochar. Pot experiments revealed that a substrate with phosphogypsum constituting 75% of the mix hinders Sudan grass seed germination. Compared with sole EMR utilization, the composite substrates notably enhanced plant growth, evidenced by increases in plant height and fresh weight. The integration of these substrates led to a significant elevation in total chlorophyll content (up to 54.39%) and a reduction in malondialdehyde (MDA) levels (up to 21.66%), indicating improved photosynthetic activity and lower oxidative stress. The addition of biochar reduced the content of Zn, Cd, and Mn in the roots of Sudan grass by up to 25.92%, 20.00%, and 43.17%, respectively; and reduced the content of Pb, Mn, and Cr in the shoot by up to 33.72%, 17.53%, and 26.32%, respectively. Fuzzy membership function analysis identified the optimal substrate composition as 75% EMR and 25% phosphogypsum, with 5% chili straw biochar, based on overall performance metrics. This study adopts the concept of “to treat waste with waste”. The approach is to fully consider the fertility characteristics of EMR, phosphogypsum, and biochar, underscoring the potential for utilizing waste-derived materials in cultivating Sudan grass and offering a sustainable approach to plant growth and heavy metal management. Full article

Improving crop yield and resource utilization efficiency is essential for agricultural productivity. In the Huang-Huai-Hai maize region of China, optimizing planting density, nitrogen (N) application, and fertilization methods are key strategies for enhancing maize yield and N use efficiency. However, traditional approaches have often hindered these improvements. To address this issue, we conducted a study in Baoding, Hebei, from 2022 to 2023, focusing on planting density, the N application rate, and the fertilization method on grain yield, N use efficiency, water use efficiency (WUE), and economic benefits. The trial involved two planting densities: 6.0 × 10⁴ plants ha⁻¹ (D1, typical local density) and 9.0 × 10⁴ plants ha⁻¹ (D2). Five N application rates were tested: 0 (N0), 120 kg ha⁻¹ (N1), 180 kg ha⁻¹ (N2), 240 kg ha⁻¹ (N3), and 300 kg ha⁻¹ (N4). The control treatment (D1N4) utilized the local planting density and traditional fertilization methods. Our findings revealed a positive correlation between the maize yield and N application rate, with the maximum yields (13.78–13.88 t ha⁻¹), high WUE (24.42–29.85 kg m⁻³), agronomic efficiency of N (AE_N) (18.11–19.00 kg kg⁻¹), and economic benefits (2.44 × 10⁴–2.47 × 10⁴ CNY ha⁻¹) observed with D2N3 and surface drip fertilization. This was significantly higher than the yield and resource efficiency of traditional fertilization methods and saved fertilizer and production costs. Therefore, adopting surface drip fertilization, adjusting planting density, and optimizing N application rates proved effective in enhancing maize yield and resource utilization efficiency in the Huang-Huai-Hai maize region. Full article

Pests in pastures have compromised the production of biomass for feeding livestock herds. Many strategies have been applied to sustainably solve this problem. One viable and innovative technique is the delivery of entomopathogenic fungi through endophytes. Therefore, this study aimed to (i) evaluate the endophytic capacity of two entomopathogenic fungi, Fusarium multiceps UFMGCB 11443 and Metarhizium anisopliae UFMGCB 11444, in Urochloa brizantha [(Hochst. ex A. Rich.) Stapf] (Poaceae) cultivar ‘Marundu’) via foliar inoculation or seed treatment, and (ii) measure their efficiency in controlling Mahanarva spectabilis Distant, 1909 (Hemiptera: Cercopidae) in U. brizantha. In the greenhouse, the fungi colonized the tissues of U. brizantha plants when inoculated via foliar spraying or seed treatment. The fungi F. multiceps and M. anisopliae caused 88% and 97.1% epizootic effects via seed inoculation, respectively, and 100% epizootic effects via foliar inoculation. In the field, the lowest fungal dose of 0.5 kg/ha had the same effect as a fourfold greater dose, with a >86% decrease in insect pest infestation observed. In summary, the fungi F. multiceps and M. anisopliae have endophytic effects and can effectively control M. spectabilis in U. brizantha pastures. Full article

Organic amendment is an effective method to reclaim salt-affected soil. However, in coastal land with shallow saline groundwater, it is limited known about the mechanism of organic amendment on soil desalinization. Thus, to examine the effect of topsoil organic matter content on soil water/salt transport and distribution, two-year field observations in Bohai coastal land, North China, and soil column experiments simulating salt accumulation and salt leaching were conducted, respectively. There were different organic fertilizer amendment rates in 0–20 cm topsoil, 0% (CK), 50% (OA 0.5), and 100% (OA 1.0) (w/w) for soil column experiments. Field observation showed that after organic amendment (OA), the soil’s physical structure was improved, and less of the increase in topsoil salt content was observed, with more salt accumulated in deep soil layers during the dry season. In addition, OA greatly promoted salt leaching during the rainy seasons. The results of the soil column tests further indicated that OA treatments significantly inhibited soil evaporation, with less salt accumulated in the topsoil. Although there was no difference in soil water distribution between the CK and OA 0.5 treatment, the topsoil EC for the OA 0.5 treatment was significantly lower than that for CK. During soil water infiltration, the OA 0.5 and OA 1.0 treatments significantly increased the infiltration rates, enhanced the wetting front, and promoted salt leaching to deeper soil layers, compared with CK. The improvement of soil organic amounts could make the soil more self-resistant to the coastal salinization. The findings of this study provide some insights into soil water/salt regulation in heterogeneous soil masses and on the permanent management of coastal saline farmland. Full article

Information technology and statistical modeling have made significant contributions to smart agriculture. Machine vision and hyperspectral technologies, with their non-destructive and real-time capabilities, have been extensively utilized in the non-destructive diagnosis and quality monitoring of crops and seeds, becoming essential tools in traditional agriculture. This work applies these techniques to address the color classification of rapeseed, which is of great significance in the field of rapeseed growth diagnosis research. To bridge the gap between machine vision and hyperspectral technology, a framework is developed that includes seed color calibration, spectral feature extraction and fusion, and the recognition modeling of three seed colors using four machine learning methods. Three categories of rapeseed coat colors are calibrated based on visual perception and vector-square distance methods. A fast-weighted visibility graph method is employed to map the spectral reflectance sequences to complex networks, and five global network attributes are extracted to fuse the full-band reflectance as model input. The experimental results demonstrate that the classification recognition rate of the fused feature reaches 0.943 under the XGBoost model, confirming the effectiveness of the network features as a complement to the spectral reflectance. The high recognition accuracy and simple operation process of the framework support the further application of hyperspectral technology to analyze the quality of rapeseed. Full article

Wheat (Triticum aestivum L.) is one of the most important food crops worldwide and provides the staple food for 40% of the world’s population. Increasing wheat production has become an important goal to ensure global food security. The grain yield of wheat is a complex trait that is usually influenced by multiple agronomically important traits. Thus, the genetic dissection and discovery of quantitative trait loci (QTL) of wheat-yield-related traits are very important to develop high-yield cultivars to improve wheat production. To analyze the genetic basis and discover genes controlling important agronomic traits in wheat, a recombinant inbred lines (RILs) population consisting of 180 RILs derived from a cross between Xinong822 (XN822) and Yannong999 (YN999), two well-adapted cultivars, was used to map QTL for plant height (PH), spike number per spike (SNS), spike length (SL), grain number per spike (GNS), spike number per plant (SN), 1000- grain weight (TGW), grain length (GL), grain width (GW), length/width of grain (GL/GW), perimeter of grain (Peri), and surface area of grains (Sur) in three environments. A total of 64 QTL were detected and distributed on all wheat chromosomes except 3A and 5A. The identified QTL individually explained 2.24–38.24% of the phenotypic variation, with LOD scores ranging from 2.5 to 29. Nine of these QTL were detected in multiple environments, and seven QTL were associated with more than one trait. Additionally, Kompetitive Allele Specific PCR (KASP) assays for five major QTL QSns-1A.2 (PVE = 6.82), QPh-2D.1 (PVE = 37.81), QSl-2D (PVE = 38.24), QTgw-4B (PVE = 8.78), and QGns-4D (PVE = 13.54) were developed and validated in the population. The identified QTL and linked markers are highly valuable in improving wheat yield through marker-assisted breeding, and the large-effect QTL can be fine-mapped for further QTL cloning of yield-related traits in wheat. Full article

Water scarcity is a global problem. Deficit irrigation (DI) reduces evapotranspiration, improving water efficiency in agriculture. Reference evapotranspiration ${(ET}_0)$ is an important factor in determining DI. ${ET}_0$ forecasting predicts field water consumption and enables proactive irrigation decisions, offering guidance for water resource management. However, implementation of ${ET}_0$ forecasting faces challenges due to complex calculations and extensive meteorological data requirements. This project aims to develop a machine learning system for ${ET}_0$ forecasting. The project involves studying ${ET}_0$ methods and identifying required meteorological parameters. Historical meteorological data and weather forecasts were obtained from meteorological websites and analyzed for accuracy after preprocessing. A machine learning-based model was created to forecast reference crop evapotranspiration. The model’s input parameters were selected through path analysis before it was optimized using Bayesian optimization to reduce overfitting and improve accuracy. Three forecasting models were developed: one based on historical meteorological data, one based on weather forecasts, and one that corrects the weather forecasts. All three models achieved good accuracy, with root mean square errors ranging from 0.52 to 0.81 mm/day. Among them, the model based on weather forecast had the highest accuracy; the RMSE six days before the forecast period was between 0.52 and 0.75 mm/day, and the RMSE on the seventh day of the forecast period was 1.12 mm/day. In summary, this project has established a mathematical model of ${ET}_0$ prediction based on machine learning, which can achieve more accurate predictions for within a few days. Full article

Conducting precise evaluations and predictions of the environmental conditions for plant growth in green spaces is crucial for ensuring their health and sustainability. Yet, assessing the health of urban greenery and the plant growth environment represents a significant and complex challenge within the fields of urban planning and environmental management. This complexity arises from two main challenges: the limitations in acquiring high-density, high-precision data, and the difficulties traditional methods face in capturing and modeling the complex nonlinear relationships between environmental factors and plant growth. In light of the superior spatial interpolation capabilities of CEDGAN (conditional encoder–decoder generative adversarial neural network), notwithstanding its comparative lack of robustness across different subjects, and the excellent ability of FCNN (fully connected neural network) to fit multiple nonlinear equation models, we have developed two models based on these network structures. One model performs high-precision spatial attribute interpolation for urban green spaces, and the other predicts and evaluates the environmental conditions for plant growth within these areas. Our research has demonstrated that, following training with various samples, the CEDGAN network exhibits satisfactory performance in interpolating soil pH values, with an average pixel error below 0.03. This accuracy in predicting both spatial distribution and feature aspects improves with the increase in sample size and the number of controlled sampling points, offering an advanced method for high-precision spatial attribute interpolation in the planning and routine management of urban green spaces. Similarly, FCNN has shown commendable performance in predicting and evaluating plant growth environments, with prediction errors generally less than 0.1. Comparing different network structures, models with fewer hidden layers and nodes yielded superior training outcomes. Full article

Understanding soil phosphorus (P) distribution and its key drivers is fundamental for sustainable P management. In this study, a 21-year fertilization experiment on black soil was carried out, setting up five fertilization treatments: unfertilized control (CK), nitrogen and potassium (NK), nitrogen, P and potassium (NPK), NPK plus straw (NPKS), and NPK plus manure (NPKM). The distribution and effecting factors of P pools within soil aggregates were investigated. Compared to CK, the NK and NPK treatments decreased calcium-associated P concentration in all aggregate fractions. Meanwhile, the NPK treatment significantly increased the organic P extracted from NaOH in unaggregated particles (<0.053 mm). This was mainly due to the reduction in soil pH. The NPKS and NPKM treatments increased almost all P forms in aggregates, especially Ca-P. For the NPKM treatment, inorganic P extracted from resin, NaHCO₃, and NaOH increased as aggregate size increased. This was mainly because straw or manure addition promoted soil organic carbon (SOC) storage in aggregates, creating more sorption sites via association with amorphous metallic minerals, and, thus, facilitating P accumulation. In conclusion, decreasing soil pH by chemical fertilizers is an effective strategy for mobilizing soil P, whereas increasing SOC by straw or manure facilitates P accumulation. Full article