Agronomy, Volume 12, Issue 11 (November 2022) – 317 articles

Cucurbitaceae crops play an important role in agricultural production, and they are a primary source of vegetables and fruits for daily needs. The cultivation of cucurbit varieties with excellent agronomic characters has attracted much attention in recent years. As the main source energy organ of Cucurbitaceae, the development of leaves is closely related to yield and environmental response. In this paper, the main research achievements on leaf development of Cucurbitaceae plants were summarized, and the origin, genetic research, gene mapping, and effects on the agronomic and economic characters of the leaf shape and leaf color mutants of Cucurbitaceae were introduced. In addition, the effects of some hormones and environmental factors were reviewed. This work provides a reference point for molecular breeding of leaf development of Cucurbitaceae. Full article

Soil nutrient testing is an effective way to uncover soil nutrient status. However, the conventional testing method (CT method) and Mehlich 3 method (M3 method) demand long-time consumption, tedious testing steps, high testing cost, dangerous chemicals contained in extractant, etc. Therefore, it is important to develop a new rapid test method or improve the existing rapid test method of soil available nutrients. In this study, an improved Mehlich3 method (IM3 method) with the new combined extractant were developed and evaluated on the testing feasibility, precision, efficiency, and cost. The results showed that: (1) IM3 method avoided the usage of two hazardous chemicals, i.e., ammonium nitrate and nitric acid, which were difficult in purchase and storage but contained in the combined extractant of M3 method. (2) The correlation coefficients of available P, K, Fe, Mn, Cu and Zn in calcareous soil between M3 and CT, and between IM3 and CT methods all reached highly significant level. The correlation coefficient of available Zn between IM3 and CT method was significantly higher than that between M3 and CT method, and those of the other elements had not obviously changed. (3) The variation coefficients of available P, K, Fe and Cu determined by M3 and IM3 methods were all lower than those determined by CT method. The variation coefficients of available Mn and Zn determined by IM3 were 3.67% and 6.43%, which were slightly higher than those determined by CT method with 2.72% and 5.29%, but were lower than those determined by M3 method. (4) Under the premise of ensuring testing precision, IM3 method took only 6.3 min/piece for determining six elements, reducing testing time by 70.7% and 3.08% compared with CT (21.5 min/piece) and M3 (6.5 min/piece) methods, respectively. The testing cost of IM3 method was reduced by 26% and 61.2% compared with M3 and CT methods, respectively. In conclusion, IM3 method is an ideal rapid measurement method for the simultaneous determination of available soil nutrients in calcareous soil. Full article

Saposhnikovia divaricata is a high-demand medicinal plant containing various bioactive metabolites (e.g., chromone). However, root rot disease leads to a dramatic reduction in the yield and quality of S. divaricata. The use of rhizospheric microorganisms is one of the best strategies for biological control. In this study, a total of 104 fungi isolated from the rhizospheric soil of S. divaricata plants were examined for their different antifungal properties. Subsequently, strain MR-57 was selected as a potential stock for biocontrol due to its broad-spectrum antagonistic activity against pathogens, including F. equiseti. Based on the analysis of morphological properties and rDNA internal transcribed spacers (ITSs), strain MR-57 was identified as Acrophialophora jodhpurensis (GenBank No. OK287150.1), a newly recorded species for China. In an in vitro antifungal assay, the culture filtrate of strain MR-57 significantly reduced the conidial germination rate and induced alterations in the mycelia morphology of F. equiseti, such as deformation and degradation. To assess the antifungal efficacy of MR-57 against root rot disease and the properties promoting the growth of S. divaricata, pot experiments were performed under natural outdoor conditions. The results indicated that co-inoculation with MR-57 delayed the occurrence of S. divaricata root rot and showed a control efficacy of 65.41% (p < 0.05) based on the measurement of suppressed disease lesions. Additionally, MR-57 successfully colonized and formed a stable population in the soil in which S. divaricata was grown, and it exhibited a consistently positive effect on the promotion of the growth of S. divaricata plants. In short, Acr. jodhpurensis MR-57 could be considered for the development of a potential biocontrol agent for the management of S. divaricata root rot caused by F. equiseti. Full article

Recent innovations are increasingly recognizing applications in precision agricultural systems that use data science techniques as well as so-called machine learning techniques. Big data analytics have created various data-intensive decision-making opportunities. This study reviews the big data analysis practices in the agriculture industry to resolve various problems to provide prospects and exciting fields of application in China. In the successful implementation of precise farming, the high-volume and complicated data generated present challenges for the economic growth of China. Emerging deep learning techniques seem promising and must be reinvented to meet current challenges. Thus, this paper suggests a big data analytics agriculture monitoring system (BDA-AMS) to ensure the highly accurate prediction of crop yield in precision agriculture and economic management using a deep learning algorithm. The convolution neural network gathers the raw images from UAVs and performs early predictions of crop yield. The simulation analysis using an open-source agricultural dataset resulted in a high parameter–precision ratio (98.8%), high accuracy (98.9%), a better performance ratio (95.5%), an improved data transmission rate (97.8%), a reduced power consumption ratio (18.8%), and an enhanced weather forecasting ratio (94.8%), production density ratio (98.8%), and reliability ratio (98.6%) compared to the baseline models. Full article

Safflower (Carthamus tinctorius L.) is a high-value oilseed crop with growing importance in numerous countries around the globe. This study was performed to evaluate the efficacy of the basic tillage technique and various seeding rates on the yield, oil accumulation and photosynthetic potential of different safflower cultivars (Kamyshinskiy 73, Zavolzhskiy 1 and Alexandrite) in the Volgograd Region of Southern Russia. Three field experiments were conducted at the research farm of Volgograd Agricultural State University during 2018–2020. The treatments were arranged as split plots based on a randomized complete block design with three blocks. Tillage treatments (basic tillage as the control (moldboard PN-4-35, depth 20–22 cm), chisel ploughing (OCHO 5-40, depth 35–37 cm) and disc ploughing (BDM-4, depth 12–14 cm)) were assigned to the main plots, and seeding rates (200, 300 and 400 m²/m²) were allocated to the subplots. The maximum leaf area, with a value of 26.35 m²/m² and the greatest photosynthetic potential of 1489 thousand m² × day ha⁻¹, was obtained in Alexandrite with the interaction of deep chisel ploughing and a seeding rate of 400 thousand seeds ha⁻¹. The highest dry biomass was also achieved in Alexandrite, with a value of 3.24 t ha⁻¹, with the interaction of deep chisel ploughing and a seeding rate of 400 thousand seeds ha⁻¹. The highest yield (1.84 t ha⁻¹) and oil accumulation (28.75%) were recorded for Alexandrite with the interaction of deep chisel ploughing and a seeding rate of 300 and 400 thousand seeds ha⁻¹ respectively. Overall, in terms of tillage treatments, the safflower productivity was highest when chisel tillage was performed, and the lowest yield was observed with the small disc ploughing practice. The yield of Alexandrite cultivar was noted to be 4.4–4.8% higher than that of the Zavolzhsky cultivar and 9.2–10.8% higher than that of the Kamyshinsky 73 cultivar. Full article

The frequency and magnitude of climate extremes, especially temperature extremes (TE), are increasing, which are exposing insect populations. However, insect responses to TE are poorly understood. In this study, we investigated the impact of high-temperature (HT: 38 °C) and low-temperature (LT: 3 °C) stresses on demographic parameters and population projections of the peach fruit fly, Bactrocera zonata, a destructive pest of fruits and vegetables. Results show that the larval developmental stage was significantly increased by HT (8.30 d) and LT (8.10 d) compared with control (7.02 d). The preadult stage in the HT and LT stressed flies were 18.56 d and 18.40 d, respectively compared with control (17.37 d). Mean longevities of both males and females were also substantially prolonged in HT and LT treatments. Compared with control, the total pre-oviposition period (TPOP) and oviposition days of B. zonata were significantly increased in both stress conditions. Furthermore, female fecundity of flies significantly increased in both HT and LT (705.48 and 698.38 respectively) treatments compared with control (578.35). These findings show that temperature stresses in the larval stage delayed the larval development and increase the reproduction and life span of B. zonata. The temperature induces alteration in life-history traits that might have significant agricultural impacts on the control strategies for this key pest. Full article

Perennial grasses undergo compensatory growth after defoliation. Nitrate is the main nitrogen source for the growth of perennial ryegrass and plays a significant role in plant resistance to stress. The aim of the study was to understand the physiological mechanism of ryegrass in response to defoliation stress under different nitrate supplies and to explore possible ways to alleviate defoliation stress. We performed pot experiments where 12-week-old ryegrass plants grown in low (0.05 mM KNO₃) or moderate nitrate (5 mM KNO₃) conditions were defoliated and subsequently supplied with different concentrations of nitrate following defoliation treatments. During the regrowth stage, the regrowth rate, biomass, photosynthetic parameters, and the response of the antioxidant system to low or moderate nitrate supply of ryegrass were investigated. The results showed that moderate nitrate supply after defoliation increased the content of photosynthetic pigments in ryegrass and improved its photosynthetic efficiency. In addition, adding moderate nitrate after defoliation increased the activity of antioxidant enzymes and the accumulation of osmotic regulating substances, thereby enhancing plant resistance, effectively reducing the damage to plants caused by defoliation stress, and promoting plant regrowth, especially for plants grown in a low nitrate environment before defoliation. Therefore, this study showed that the addition of exogenous nitrate could counteract some of the adverse effects of defoliation stress on the growth and development of ryegrass. Full article

Potato virus Y (PVY) causes serious loss in the yield and quality of potatoes. The effect of chitosan nanoparticles (CS-NPs) on the regeneration response and production of PVY-free plants under in vitro conditions was studied. Murashige and Skoog (MS) medium supplemented with 0.1 mg L⁻¹ Gibberellic acid (GA₃), 0.1 mg L⁻¹ Naphthalene acetic acid (NAA) and 500 mg L⁻¹ malt extract was used for regeneration of plantlets from sprouts. Double Antibody Sandwich Enzyme-Linked Immunosorbent Assay (DAS-ELISA) and Reverse Transcript Polymerase Chain Reaction (RT-PCR) was used for virus indexing of the mother plant and in vitro-regenerated plantlets. Explants of PVY positive potato plants were cultured on same medium amended with 100, 200, 250, and 300 mg L⁻¹ of (CS-NPs). Shoot regeneration decreased from 100 to 200 mg L⁻¹ as the concentrations of antiviral (CS-NPs) up to 250 mg L⁻¹. It was decreased with the increase in the concentration of the antiviral (CS-NPs) up to 300 mg L⁻¹. Antiviral (CS-NPs) at the concentration of 250 mg L⁻¹ showed a positive effect on shoot regeneration. In vitro-regenerated plantlets were virus free and tested negative in both ELISA and RT-PCR. The level of 100 mg L⁻¹ of (CS_NPs) produced 38.8% PVY-free plants and 30.50% of cultures showed shoot regeneration. The level of 200 mg L⁻¹ of (CS-NPs) produced 49.6% PVY-free plants while 46.8% of cultures showed shoot regeneration. The level of 250 mg L⁻¹ of (CS-NPs) was the most effective and produced 100.0% PVY-free plants and 100.0% of cultures showed shoot regeneration. Histopathological changes simultaneously with elucidation of resistance and growth enhancement were evident in the treated plants with (CS-NPs) than those untreated control. In conclusion, (CS-NPs) treatment is an effective tool to produce PVY-free sprouts explants and has potential for producing virus-free planting material for the potato industry. Full article

Globally, croplands represent a significant contributor to climate change, through both greenhouse gas emissions and land use changes associated with cropland expansion. They also represent locations with significant potential to contribute to mitigating climate change through alternative land use management practices that lead to increased soil carbon sequestration. In spite of their global importance, there is a relative paucity of tools available to support field- or farm-level crop land decision making that could inform more effective climate mitigation practices. In recognition of this shortcoming, the Simple Algorithm for Yield Estimate (SAFY) model was developed to estimate crop growth, biomass, and yield at a range of scales from field to region. While the original SAFY model was developed and evaluated for winter wheat in Morocco, a key advantage to utilizing SAFY is that it presents a modular architecture which can be readily adapted. This has led to numerous modifications and alterations of specific modules which enable the model to be refined for new crops and locations. Here, we adapted the SAFY model for use with spring barley, winter wheat and winter oilseed rape at selected sites in Ireland. These crops were chosen as they represent the dominant crop types grown in Ireland. We modified the soil–water balance and carbon modules in SAFY to simulate components of water and carbon budgets in addition to crop growth and production. Results from the modified model were evaluated against available in situ data collected from previous studies. Spring barley biomass was estimated with high accuracy (R² = 0.97, RMSE = 95.8 g·m⁻², RRMSE = 11.7%) in comparison to GAI (R² = 0.73, RMSE = 0.44 m²·m⁻², RRMSE = 10.6%), across the three years for which the in situ data was available (2011–2013). The winter wheat module was evaluated against measured biomass and yield data obtained for the period 2013–2015 and from three sites located across Ireland. While the model was found to be capable of simulating winter wheat biomass (R² = 0.71, RMSE = 1.81 t·ha⁻¹, RRMSE = 8.0%), the model was found to be less capable of reproducing the associated yields (R² = 0.09, RMSE = 2.3 t·ha⁻¹, RRMSE = 18.6%). In spite of the low R² obtained for yield, the simulated crop growth stage 61 (GS61) closely matched those observed in field data. Finally, winter oilseed rape (WOSR) was evaluated against a single growing season for which in situ data was available. WOSR biomass was also simulated with high accuracy (R² = 0.99 and RMSE = 0.52 t·ha⁻¹) in comparison to GAI (R² = 0.3 and RMSE = 0.98 m²·m⁻²). In terms of the carbon fluxes, the model was found to be capable of estimating heterotrophic respiration (R² = 0.52 and RMSE = 0.28 g·C·m⁻²·day⁻¹), but less so the ecosystem respiration (R² = 0.18 and RMSE = 1.01 g·C·m⁻²·day⁻¹). Overall, the results indicate that the modified model can simulate GAI and biomass, for the chosen crops for which data were available, and yield, for winter wheat. However, the simulations of the carbon budgets and water budgets need to be further evaluated—a key limitation here was the lack of available in situ data. Another challenge is how to address the issue of parameter specification; in spite of the fact that the model has only six variable crop-related parameters, these need to be calibrated prior to application (e.g., date of emergence, effective light use efficiency etc.). While existing published values can be readily employed in the model, the availability of regionally derived values would likely lead to model improvements. This limitation could be overcome through the integration of available remote sensing data using a data assimilation procedure within the model to update the initial parameter values and adjust model estimates during the simulation. Full article

In view of the need to remove empty cells and unqualified seedlings for automatic transplanting of leafy vegetable seedlings, this paper proposes a method to detect the growth parameters of leafy vegetable seedlings by using machine vision technology. This method uses the image processor PV200 to perform image grayscale, threshold segmentation, corrosion, expansion, area division, etc. to obtain the pixel value of the leaf area of the seedling and compare it with the set standard value, which provides guiding information for eliminating empty cells and unqualified seedlings. Lettuce seedlings at 17 days, 20 days, and 22 days of seedling age were used as the test objects, and the growth status and test results of the seedlings were analyzed to determine the optimum seedling age for transplanting. The test results show that there is basically no leaf cross-border between the lettuce seedlings at the age of 17 days, the average pixel area of the leaves is 3771.74, and the detection accuracy rate is 100%; the seedlings at the age of 22 days grow 5–6 leaves, the detection accuracy of unqualified seedlings and qualified seedlings was 62.50% and 88.16%, respectively, and the comprehensive detection accuracy was 85.71%. The comprehensive detection accuracy rate showed a downward trend with the increase of seedling age, mainly due to the partial occlusion between leaves. The transplanting of leafy vegetable seedlings is a sparse transplanting operation, and the seedling spacing increases after transplanting. Therefore, the detection of seedlings in the process of transplanting can greatly improve the recognition accuracy and solve the problem that the leaves of the seedlings in the seedling tray are obscured by each other and affect the detection accuracy. The research results can provide a theoretical basis and design reference for the development of the visual inspection system and the transplanting actuator of the leafy vegetable seedlings transplanting robot. Full article

Sorghum landraces are essential for developing cultivars with improved properties, such as disease tolerance, yield and metabolite content. In this study, 139 genotypes (136 Korean sorghum landraces and 3 control cultivars) collected from various provinces were investigated using eleven agronomical and five biochemical traits. The landraces showed little variation in their qualitative agronomical traits. In contrast, quantitative agronomical and biochemical traits differed significantly among the landraces. It was discovered that 16 landraces matured ahead of all control cultivars. Furthermore, 26 landraces had significantly higher thousand seed weights (TSWs) than two of the control cultivars, including Nampungchal (30.63 g) and Sodamchal (30.53 g), whereas only 1 landrace had a significantly higher TSW than the other control cultivar, Wheatland (37.93 g) (p < 0.05). The levels of total tannin content (TTC), total phenolic content (TPC), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium (ABTS) radical cation scavenging activity, 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity and ferric reducing antioxidant power (FRAP) were in the ranges of 0.12–428.95 mg CE/g, 1.17–10.23 mg GAE/g, 1.64–67.60 mg TE/g, 0.48–31.99 mg AAE/g and 0.63–21.56 mg AAE/g, respectively, and were all affected by collection area, seed weight and seed color. Landraces from northern provinces were discovered to have higher metabolite contents. Furthermore, large seeds had higher TTC and TPC levels as well as DPPH, ABTS and FRAP activities than medium and small seeds, except for the TTC and FRAP, which were significantly different. In terms of seed color, white seeds had significantly lower metabolite contents and antioxidant activities and were notable in principal component analysis. Correlation analysis revealed positive and significant associations between biochemical traits, as well as between panicle-related agronomic traits. In general, the landraces with superior characteristics could be ideal candidates for sorghum breeding programs. Full article

Improving aroma profile represents one of the principal goals in winemaking. This paper focuses to evaluate the influence of enzymes applied before alcoholic fermentation of Fetească regală and Sauvignon blanc wines, even if most studies analyze their use in different winemaking stages. Fetească regală wines are described by higher proportions (1.07–4.28%) of ethyl octanoate (exotic fruits), 3-methylbutyl acetate (pear, banana), hexanoic acid (creamy, phenolic, exotic fruits), propan-2-yl acetate (ripe fruits, banana), and ethyl decanoate (floral, fruity, woody), while Sauvignon blanc wines are distinguished by significant proportions (2.77–42.15%) of 3-methylbutan-1-ol (exotic fruits), acetic acid (vegetal, sour), 1-phenylethanol (floral, honey), and diethyl butanedioate (fruity, floral). Variables as 3-methylbutyl acetate-ethyl decanoate, ethyl decanoate-hexanoic acid (r > 0.8) showed proportional levels in Fetească regală wines. In Sauvignon blanc samples, positive correlations were observed for 2-ethyl hydroxypropanoate-diethyl butanedioate or 2,3-butanediol-ethyl 4-hydroxybutanoate (r > 0.7). Data confirmed a significant influence of enzymes on wine’s aroma profile (p < 0.05). The higher proportions of the most volatile compounds were obtained in samples treated with pectinases, for both varieties. In correlation with the sensory analysis, these variants showed the lowest intensity for negative descriptors such as phenolic sensation, the mineral or bitter taste, demonstrating that pectinases can give more acceptable results regarding the sensory perception compared to β-glycosidases. Full article

Models based on thermal or hydrothermal time are used to predict the seedling emergence pattern of weeds. These models rely on sigmoidal functions such as Gompertz, Weibull or logistic, in which daily soil temperature and moisture data are inputs and the percentage of total expected emergences is the output. The models give good predictions at local and regional scales but they lose accuracy when extrapolated to different geographic areas from where the equations were developed. They also must be validated prior to their release and have subjectivity of the date to start the accumulation of the degree-days. We propose the use of the differential form of the function rather than the integrated form. Under this approach, the starting date to accumulate degree-days is set to the week before the first weed emergence is recorded (if recorded on a weekly basis) and emergence predictions only rely on the current sigmoidal relationship between data recordings. When the weed emergence rate in the field decreases, the relationship between data recordings and time, measured either as thermal or hydrothermal degrees, starts to decrease. When the derivative of the emergence over time falls below a threshold that should be set up based on our knowledge of the economic threshold of the species, a post-emergence weed control measure should be carried out. Under this approach, weekly counts of weeds must be recorded until the derivative reaches the threshold. This approach has been checked on 39 data sets of different weeds in different crops and seasons by applying the differential form of the Gompertz function, obtaining a correlation of 0.99 between the predicted and the observed emergence. The methodology could be particularly useful when timing control measures in cropping areas with unknown or very little knowledge of the species and their emergence pattern. Full article

A greenhouse study was conducted to investigate the roles that host plant resistance and soil potassium (K) levels play in affecting Rotylenchulus reniformis Linford and Oliveira (Tylenchida: Hoplolaimidae) (RN) populations and early season cotton (Gossypium hirsutum L.) growth. Two upland, RN-resistant cotton lines (G. barbadense introgressions: 08SS110-NE06.OP and 08SS100), a genetic standard (Deltapine 16) and a commercially available susceptible cultivar (PHY 490 W3FE) were evaluated at four different levels of K [100% of recommended rate, 150% of recommended, 50% of recommended, and a base level] from seeding until harvesting, 60 days after sowing (DAS). Quadratic functions (r² = 0.82 to 0.95) best described the early season growth response of cotton genotypes to soil K. The base K level was associated with the lowest values for most morphological variables, including plant height (PH), mainstem nodes (MSN), leaf area, and dry weight at 30 DAS and 60 DAS. However, soil K did not affect RN population counts (RC). Additionally, soil K did not influence the rate of change in growth variables among genotypes. The resistant genotype 08SS110-NE06.OP showed greater growth in terms of time to first true leaf, PH, MSN, and above-ground dry weights compared to the commercially available susceptible genotype. No interaction between K and RN or genotype and RN was found in early season cotton growth. However, RC in pots of resistant genotypes was less than in pots of susceptible genotypes. Our research on the early season growth response to soil K by novel, RN-resistant genotypes and susceptible genotypes contributes to the development of improved RN resistance and fertilization management in cotton. Full article

The aim of the study was to demonstrate the feasibility of using hydrogen peroxide stabilized with silver (H₂O₂-Ag⁺) and selected fungicides for the treatment of hyacinth bulbs and to determine their effects on the development of fungi colonizing the substrate and bulbs and their impact on plant growth and development. Hydrogen peroxide stabilized with silver (H₂O₂-Ag⁺) and captan, pyraclostrobin + boscalid and methyl thiophanate + tetraconazole were used to treat hyacinth bulbs before planting, in the form of a 20 min soak. The effect of the treatment on the development of fungi on the bulbs and substrate was evaluated during rooting in the refrigerated storerooms and after placement in the greenhouse. Observations were also made on the effect of treatment on hyacinth growth and development. The study showed a significant effect of H₂O₂-Ag⁺ and fungicides used for the treatment of hyacinth on reducing the development of fungi on bulbs and substrate during the period of hyacinth rooting. It was found that H₂O₂-Ag⁺, at concentrations ranging from 2% to 10%, significantly increased the Chlorophyll Index and Nitrogen Balance Index. In some of the concentrations tested, it also increased petal width, inflorescence width, the number of flowers, leaf length, leaf width, plant quality, fresh weight without inflorescences and the dry weight of plants without inflorescences at some of the concentrations tested. It was shown that, for all fungicides used, flower diameter, inflorescence width, total height, leaf length, leaf width, plant fresh weight without inflorescence and plant dry weight without inflorescence were significantly increased compared to control plants. None of the treatments tested were phytotoxic to hyacinth. Full article

Tillering fertilization is an important part of field management in rice production. As the first peak fertilizer requirement period of rice, tillering fertilization directly affects the number of tillers and the growth of rice in the middle and late stages. In order to investigate a method of constructing an accurate fertilizer prescription map in the tillering stage using an unmanned aerial vehicle (UAV) remote sensing nitrogen demand diagnosis and reduce the amount of chemical fertilizer while ensuring the rice yield, this study realized the diagnosis of the rice nitrogen nutrient demand using UAV hyperspectral remote sensing during the tilling stage fertilization window. The results showed that the fertilizer amount was determined using the characteristic waveband and remote sensing. The results showed that five rice hyperspectral variables were extracted in the range of 450–950 nm by the feature band selection and feature extraction for the inversion of rice nitrogen content, and the inversion model of rice nitrogen content constructed by the whale-optimized extreme learning machine (WOA-ELM) was better than that constructed by the whale-optimized extreme learning machine (ELM). The model coefficient of determination was 0.899 and the prescription map variable fertilizer application method based on the nitrogen content inversion results reduced the nitrogen fertilizer by 23.21%. The results of the study can provide data and a model basis for precise variable fertilizer tracking by agricultural drones in the cold rice tillering stage. Full article

Lodging is one of the main factors causing yield loss of maize under high-density planting conditions. Root lodging as an important lodging type has received little attention. Plant growth regulators (PGRs) and nitrogen fertilizer can coordinate the relationship between root lodging and yield. This two-year field experiment was conducted with two nitrogen levels of N225 (225 kg ha⁻¹) and N300 (300 kg ha⁻¹) at a high planting density (90,000 plants ha⁻¹) during the maize growth season from 2019 to 2020. Plant growth regulator (Yuhuangjin, the mixture of 3% DTA-6 and 27% ethephon) was sprayed at the V8 stage. The results showed that PGRs significantly decreased plant height, improved root distribution and dry weight, enhanced photosynthetic rate and activities of photosynthetic carboxylase in ear leaves, and improved root bleeding sap and root activities after the silking stage. N225 combined with PGRs reduced the occurrence of root lodging and was conducive to photosynthate accumulation and root nutrient supply; it coordinated root regulation and morphological and physiological shoot functions, and played a crucial role in reducing root lodging and improving maize yield. Full article

Melon is an important horticultural crop worldwide. The high diversity of melon makes it a model plant for various different properties. Some quantitative trait loci or candidates have been discovered, but few were verified as limiting genetic transformation and genome editing systems. Identifying new genetic resources with resistance and special fruit quality traits is imperative to develop effective and useful breeding technologies in melon. This review describes the advances in genetics, genomics, and the breeding of melon and puts forward some recommendations in these areas. Full article

Future emission scenarios can interfere with the yield of major crops. In this study, we investigated the future impact of increased air temperature and relative humidity on melon phenology and water demand in the Brazilian semi-arid region. We applied the PRECIS (Providing Regional Climates for Impact Studies) climatological model to develop the Intergovernmental Panel on Climate Change emission scenarios—B2 optimistic emission scenario and A2 pessimistic emission scenario—and we assessed the climate change effects on the phenology and water demand of two melon cultivars. The “Orange County” hybrid, the Honeydew melon, grew from 2006–2007, and the “Néctar” hybrid, the Galia melon, grew in 2008. These cultivars were also considered using the actual emission scenario. We found that the B2 and A2 emission scenarios will cause a cycle decrease of 15.49 and 25.35% for the “Orange County” hybrid and a 9.84 and 18.03% decrease for the “Néctar” hybrid. Future changes to the climate will increase the melon crop coefficient and daily rate of evapotranspiration. Regarding the “Orange County” hybrid, the cycle shortening overcomes the daily water demand increases, decreasing water demand by 13.7–18.3%. Regarding the “Néctar” hybrid, cycle shortening will be proportional to the increase in water demand. The Honeydew melon will be more sensitive to air temperature and relative humidity increases than the Galia melon. Full article

Accurately identifying weeds in crop fields is key to achieving selective herbicide spraying. Weed identification is made difficult by the dense distribution of weeds and crops, which makes boundary segmentation at the overlap inaccurate, and thus pixels cannot be correctly classified. To solve this problem, this study proposes a soybean field weed recognition model based on an improved DeepLabv3+ model, which uses a Swin transformer as the feature extraction backbone to enhance the model’s utilization of global information relationships, fuses feature maps of different sizes in the decoding section to enhance the utilization of features of different dimensions, and adds a convolution block attention module (CBAM) after each feature fusion to enhance the model’s utilization of focused information in the feature maps, resulting in a new weed recognition model, Swin-DeepLab. Using this model to identify a dataset containing a large number of densely distributed weedy soybean seedlings, the average intersection ratio reached 91.53%, the accuracy improved by 2.94% compared with that before the improvement with only a 48 ms increase in recognition time, and the accuracy was superior to those of other classical semantic segmentation models. The results showed that the Swin-DeepLab network proposed in this paper can successfully solve the problems of incorrect boundary contour recognition when weeds are densely distributed with crops and incorrect classification when recognition targets overlap, providing a direction for the further application of transformers in weed recognition. Full article

The yield potential of cassava might be increased by enhancing light interception and the ability to convert energy into biomass and yield, which is described as radiation use efficiency (RUE). The objective of this study was to determine light interception, extinction coefficient (k), and RUE of three cassava genotypes (Kasetsart 50 (KU50), Rayong 11 (RY11), and CMR38-125-77) under seasonal variations. The field experiments were conducted in a randomized complete block design with four replications, using two planting dates for 2 years at Khon Kaen, Thailand. Data were recorded for weather conditions, light interception, leaf area index (LAI), and biomass. Solar radiation interception, RUE, and k were calculated. Light interception of the crop planted in May sharply increased in the early growth stage, whereas the crop planted in November slowly increased and could maintain higher light interception from the mid–late growth stages. Light interception and LAI had a moderate to high coefficient of determination (R² = 0.61–0.89) for three cassava genotypes and all planting dates. The k values ranged from 0.59 to 0.94, varying by genotypes and planting dates, indicating that the leaf orientation of the three cassava genotypes was horizontally oriented. The relationship between biomass accumulation and cumulative solar radiation produced a high value of R² (0.86–0.99). The RUE for biomass (RUE_bi) varied by genotype and planting date, ranging from 0.66 g MJ⁻¹ to 0.97 g MJ⁻¹. However, the RUE for storage root dry weight (RUE_sr) ranged from 0.29 g MJ⁻¹ to 0.66 g MJ⁻¹. The RUE_bi and RUE_sr in each genotype on each planting date were significantly different. The highest RUE_bi and RUE_sr were found at 4–6 and 7–9 MAP for almost all genotypes and planting dates, except for the crop planted in November 2015, when both RY11 and CMR38-125-77 had the highest RUEbi at 10–12 MAP. RY11 had a lower LAI compared to other genotypes, which contributed to lower light disruption and lower RUE_bi and RUE_sr. KU50 and CMR38-125-77 could maintain canopy light interception during canopy development and storage root accumulation stages and had high RUE_bi and RUE_sr, resulting in high biomass and crop yield. Full article

Winter rye (Secale cereale L.) is a grain crop well known for its outstanding tolerance to unfavorable weather and soil conditions. Because of rye’s wide range of possible uses (e.g., cover crop, feed for livestock, bread, cookies, distilled and brewed beverages), its pro-health properties and unique flavor, interest in this crop is increasing in the United States. In 2018/2019 and 2019/2020 we tested 24 winter rye varieties that were available in the US at 3 planting dates: early, intermediate, and late. The aims of this study were to (1) identify conventional and hybrid varieties suitable for the US mid-south environment; (2) establish an optimal planting date of winter rye and (3) quantify genotype x planting date interaction. At both locations and in both growing seasons the best yielding, and most resistant to disease and lodging entries were European hybrids (KWS Serafino, KWS Daniello, KWS Bono and KWS Brasetto), and the best yielding conventional varieties were AC Hazlet and ND Dylan. There were statistically significant (p < 0.01 in 2019 and p < 0.0001 in 2020) differences in yield between planting dates both seasons. The response to planting date differed between varieties. In the 2018/2019 growing season we observed that, on average, rye performed better when planted early, but in 2019/2020, a severe May freeze caused extensive damage in early planted rye, and the best planting date was the late one. Overall, the majority of varieties analyzed individually performed the best at intermediate and late planting dates. Full article

Polysaccharides such as hemicellulose in rapeseed can be used as an abundant resource to develop biomass energy. In the present study, the hemicellulose content in the middle stalk and taproot of a rapeseed core population of 139 accessions in Guizhou, Hubei and Anhui provinces was determined. Genotyping of the core population was carried out by a 60 K single nucleotide polymorphism chip, and a genome-wide association study (GWAS) was performed to reveal the associated sites of hemicellulose content in rapeseed. The results of the GWAS showed that 28 SNPs (p ≤ 0.001) were significantly associated with hemicellulose content, and revealed that three sites—qHCs.C02 (contribution rate = 17.20%), qHCs.C05 (10.62%), and qHCs.C08 (8.80%)—are significantly associated with hemicellulose content in the stalk and three sites—qHCt.A09 (9.49%), qHCt.C05 (9.18%) and qHCt.C08 (13.10%)—are significantly associated with hemicellulose content in the taproot. Seven candidate genes associated with hemicellulose synthesis were identified in these major loci. Further RNA-seq analysis showed that two key differentially expressed genes (BnaC05G0092200ZS and BnaC05G0112400ZS) involved in hemicellulose synthesis were identified as having underlying QTL. This study excavated the key loci and candidate genes for regulating hemicellulose synthesis, providing a theoretical basis for developing rapeseed varieties with high hemicellulose content. At the same time, our results will be helpful in producing rapeseed cultivars with high lodging-resistance as well as highlighting the value of rapeseed as a resources for the bioenergy industry. Full article

There is a growing demand for high quality and sustainable food in the world and this need falls within the context of the European Green Deal’s strategy “From Farm to Fork”. In order to achieve these outcomes, the use of modern and innovative technologies of plant production and protection is required. The use of nanoparticles (NPs) in agriculture and horticulture is an example of such technology. However, research on the effect of length of exposure to metal nanoparticles on seeds germination and seedlings development are limited in the literature. In our study, the effect of silver (AgNPs) and gold nanoparticles (AuNPs) on the seedling growth and biochemical response of rapeseed after 7, 14 and 21 days was analyzed. In the experiments, 0, 50 and 100 ppm concentrations of NPs were used in vitro. The level of photosynthetic pigments, anthocyanins as well as other stress parameters, such as free phenolic compounds, free sugars or H₂O₂, decreased due to the application of both AgNPs and AuNPs at the initial culture period; however, the differences were observed in the successive weeks of exposure. The parameters were increasing, irrespective of the kind of nanoparticles; however, as for the content of free sugars and free radicals, higher values were recorded due to the effect of AuNPs. Our results showed that length of plants exposure to NPs is very important factor modifying growth and final response of seedlings. Better understanding of its influence could speed up use of NPs in agriculture and horticulture for production of high-quality plant material (e.g., to seed priming, stimulation of seedlings’ growth and their protection), not contaminated with pesticides, fertilizers and mycotoxins. Full article

Synthetic fertilization can increase maize yields, but also cause environmental impacts, as well as increasing production costs and food security risks. Sun mushroom (Agaricus subrufescens) is an important Brazilian fungus used to generate large amounts of spent mushroom substrate. This residue can be used for maize fertilization, but little is known about its ideal application rates to reduce maize dependence on synthetic fertilizers. Therefore, this study aimed to evaluate the agronomic performance of a maize crop under different combinations of synthetic fertilizers and two different spent mushroom substrate doses. The experiment was carried out in pots and evaluated maize germinate and biometric parameters, as well as soil and leaf chemical characteristics. The results showed that residue application increased maize germination and Emergence Speed Index. Regarding the maize biometric parameters, height, stem diameter, shoot fresh and dry masses, and leaf area were superior for residue with synthetic fertilization at sowing only at higher doses. Moreover, residue with synthetic fertilization at sowing proved to be more relevant for maize growth according to canonical discriminant analysis. In terms of nutrients, the use of spent mushroom substrate increased significantly leaf P, K, and S levels and mainly K content in the soil, justifying non-application at maize topdressing. Full article

Using plant-based allelopathic compounds might be a potent substitute to help mitigate the effects of synthetic herbicides. Annona reticulata L. is often planted for its fruit in residential gardens. This plant is well-documented for its diverse ethnomedicinal uses. However, there is no information in the literature on the allelopathic potential of A. reticulata leaves. Therefore, the allelopathic potential and relevant allelopathic compounds of A. reticulata leaves were investigated in this study. The bioassays were carried out using a completely randomized experimental layout (CRD), and the resulting data were analyzed using one-way ANOVA at p ≤ 0.05. Aqueous methanol extracts of A. reticulata leaves significantly inhibited the growth of three dicots and three monocots (Lepidium sativum L., Medicago sativa L., Lactuca sativa L., Echinochloa crus-galli (L.) P. Beauv., Lolium multiflorum Lam., and Phleum pratense L., respectively). The level of growth inhibition was proportional to the A. reticulata extract concentration. Three compounds were purified through different chromatographic steps, and their structures were determined using spectroscopy and identified as loliolide, 5-hydroxy-3,4-dimethyl-5-pentylfuran-2(5H)-one, and 3,4-dihydroxyphenylethanol. The 5-hydroxy-3,4-dimethyl-5-pentylfuran-2(5H)-one had the greatest effect on suppressing cress root growth, while loliolide had the greatest effect on suppressing timothy shoot growth. The values for 50% seedling growth suppression showed that the compound with the maximum inhibitory activity was loliolide, followed by 5-hydroxy-3,4-dimethyl-5-pentylfuran-2(5H)-one and 3,4-dihydroxyphenylethanol. Therefore, this result suggests that the three compounds might be responsible for the allelopathic effects of A. reticulata leaf extracts, and these compounds have the potential to be used to develop effective bioherbicides. Full article

The effect of beneficial soil fungi, bacteria and mineral fertilizers containing nitrogen, phosphorus and potassium on the level and species composition of weed infestation, uptake of macronutrients by weeds and the nutritional status of ‘Sampion’ apple trees with nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg) and calcium (Ca) was assessed in three-year studies. In the field experiment, the effect of thirteen treatments was investigated, where fungal or bacterial inocula and mineral fertilizers at a standard dose and a dose reduced by 40% were applied individually or together. The fungal inoculum contained two species: Aspergillus niger and Purpureocillium lilacinum. The bacterial consortium consisted of three Bacillus strains: Bacillus sp., Bacillus amyloliquefaciens and Paenibacillus polymyxa. The weight of weeds and the uptake of macronutrients by weeds in the apple orchard increased significantly more after the application of mineral fertilization than after the application of beneficial organisms. The increased uptake of macronutrients by weeds did not significantly change the mineral nutritional status of apple trees expressed as the content of N, P, K Mg and Ca in apple leaves. After the use of NPK mineral fertilization, also with the addition of beneficial organisms, the uptake of N by both weeds and apple trees increased. P and K were more efficiently absorbed by weeds and they achieved greater benefits from fertilization with these two macroelements than trees. Full article

This study sought to evaluate the potential of mulched gravel to release nutrients in the field by conducting trials with three variations of wet-and-dry cycling of the soil beneath gravel mulch and bare soil. The results revealed that quartz, muscovite, clinochlore, and albite were the most abundant minerals in the gravels. Throughout the whole wet-and-dry cycle, the total content of 30 elements measured in the gravel-mulched soil was higher than in the bare soil treatment, and the content of the total element rose with increasing wet–dry cycle humidity. The enrichment ratio (B_r) of each element in soil under gravel mulch relative to bare soil was in the sequence Mg > Ca > K > Cr > Na > Mn > V > Zn > Fe > Ti > Si > C > N > B> Co > (B_r = 0) > Pb > Cu > Ga > P > Sn > Sr > Al > Be > Li > Mo > Ni > Se > As > S. Under gravel mulch, the elements impacted by the wet–dry cycle are primarily rock-forming, whereas the elements affected under bare soil are primarily trace elements. The wet-and-dry cycles of gravel affected soil nutrients mainly by increasing soil K, Ca, Na, and Mg contents. The differences in soil K and Ca contents significantly affected the growth of jujube trees and the jujube fruit yield. A dry/wet cycle level of 5 L/d per tree under gravel cover conditions can effectively improve soil nutrients and increase the jujube fruit yield without causing environmental problems. Full article

Roasting has been used by the coffee industry to promote changes in the physical and chemical structure of coffee beans that influence the sensory quality of coffee beverages. However, there are no standardization rules for the temperature and roasting time. Thus, this study evaluated the influence of four roasting profiles obtained by two different roasters on the chemical and sensory quality of the coffee bean. Baked, light, medium, and dark roasting were evaluated using medium infrared spectroscopy and cupping test. Individual and joint effects of temperature and time for each roasting profile were observed on the loss of grain mass. There are specific regions in the infrared spectrum that can be used as markers to discriminate the roasting profiles and the type of roaster used. Despite the difference observed in the ranges of the infrared spectra, the roasters did not present significant differences in the average of the final sensory notes. This result shows the need to use analytical chemical techniques together with sensory analysis in order to better determine differences between coffee samples. Therefore, differences observed in the chemical analyzes and in the sensory attributes of roasted coffee are related to the roasting profile and type of roaster. Full article

Adoption of sustainable agriculture innovations is acknowledged to be an effective response to agro-ecological challenges, such as climate change, pests, drought, natural catastrophes, and food insecurity. However, its level of dissemination is still low across the world, particularly in the Global South. There is a need for a better understanding of the adoption determinants of these innovations in order to enhance them. This paper presents a systematic literature review focused on the use of sociopsychological determinants to understand the adoption of sustainable agriculture innovations, combining conventional bibliometric analysis with the method of vote-count. This method enabled an evaluation of the ability of the determinants considered by the models, as well as respective sociopsychological constructs, to explain the innovation adoption. Our results show a significant growth in the research employing theory and models built on sociopsychological factors to understand the decision-making processes undertaken by farmers in the context of the adoption of sustainable agriculture innovations. The development of statistical models and techniques, such as the structural equation model (SEM), has facilitated the inclusion of a growing set of sociopsychological variables. However, our review highlights that the selection of the sociopsychological constructs used by research to explain farmers’ adoption of sustainability innovations relies mainly on constructs defined for other decisional contexts, such as the adoption of innovations by firms in other sectors. Hence, the low ability evidenced by the models to explain farmers’ adoption behavior is due to a poor selection of constructs. The review highlights that this poor selection is a result of repetition of constructs, such as attitude, subjective norms, and little inclusion of other relevant constructs such as knowledge. The paper suggests the need for a better selection of the innovation determinants and measurement of respective constructs adjusted to the case of agriculture and the specificities of the diverse geographical farming contexts. Full article