Editor’s Choice Articles

The world is changing, and climate change has become a serious issue. Organizations, governments, companies, and consumers are becoming more conscious of this impact and are combining their forces to minimize it. Cooperatives have a business model that differs from those in the private or public sector. They operate according to their own principles of cooperation, which makes it difficult to obtain results that are in harmony with the objectives of the organization and the cooperative members. However, they are also aware of climate change because their businesses are directly affected. Thus, in this review, we have tried to answer the following questions: What is necessary to meet the sustainability goals? Are wine cooperatives competitive in the context of the global market? How can we respond to the challenges of environmental sustainability while maintaining wine quality standards and economic profitability? What are the economic and social impacts of reducing the carbon footprint of cooperatives and their members? Full article

Wheat interactions against fungal pathogens, such as Zymoseptoria tritici, are affected by changes in abiotic factors resulting from global climate change. This situation demands in-depth knowledge of how predicted increases in temperature and CO₂ concentration ([CO₂]) will affect wheat—Z. tritici interactions, especially in durum wheat, which is mainly grown in areas considered to be hotspots of climate change. Therefore, we characterized the response of one susceptible and two resistant durum wheat accessions against Z. tritici under different environments in greenhouse assays, simulating the predicted conditions of elevated temperature and [CO₂] in the far future period of 2070–2099 for the wheat-growing region of Córdoba, Spain. The exposure of the wheat—Z. tritici pathosystem to elevated temperature reduced disease incidence compared with the baseline weather conditions, mainly affecting pathogen virulence, especially at the stages of host penetration and pycnidia formation and maturation. Interestingly, simultaneous exposure to elevated temperature and [CO₂] slightly increased Z. tritici leaf tissue colonization compared with elevated temperature weather conditions, although this fungal growth did not occur in comparison with baseline conditions, suggesting that temperature was the main abiotic factor modulating the response of this pathosystem, in which elevated [CO₂] slightly favored fungal development. Full article

This study was conducted to determine the optimal temperature difference in day–night indoor cultivation conditions to enhance the flower yield and functional component contents of female hemp plants. Hemp clones were cultivated under five distinct day and night temperature differences (DIF) during the reproductive stage. The daytime and nighttime temperature settings were as follows: 18:30 °C (negative 12 DIF), 21:27 °C (negative 6 DIF), 24:24 °C (0 DIF), 27:21 °C (positive 6 DIF), and 30:18 °C (positive 12 DIF). Seven weeks after transplantation, the growth parameters, leaf gas exchange, total phenolic compounds, 2,2-diphenylpicrylhydrazyl scavenging activity, and cannabinoid contents were analyzed. The total shoot biomass based on dry weight was highest at 21:27, reaching 41.76 g, and lowest at 30:18, measuring 24.46 g. However, the flower biomass, which is the primary production site, was highest at 24:24 and lowest at 18:30, showing a 4.7-fold difference. The photosynthesis-related parameters were temperature-dependent and strongly correlated with biomass production. The cannabinoid content of the hemp leaves increased at 21:27, whereas that of the hemp flowers increased at 27:21. The findings of this study indicate that the optimal temperature condition for female hemp flower production in a limited space is positive 6 DIF treatment, which corresponds to 27:21 °C. These results can contribute to advancements in indoor crop cultivation technology. Full article

Agrivoltaic systems, which combine the cultivation of crops with solar panel installations, offer a novel solution to the dual challenges of energy production and agricultural productivity. This research verifies the impact of agrivoltaic (APV) conditions on the growth and quality of garlic and kimchi cabbage over two consecutive years in Naju-si, Jeollanam Province, Republic of Korea. In the 2019–2020 cultivation season, both kimchi cabbage and garlic grown under APV conditions experienced weight reductions of 18% and 15%, respectively, when compared to those grown in conventional settings. Intriguingly, despite the altered light conditions of APV leading to microenvironmental changes (mainly 41% light reduction), the quality of these crops, particularly in terms of their sulfur compound concentrations, remained consistent. This suggests that there was no discernible difference in the sensory quality of APV-grown kimchi cabbage and garlic compared to their traditionally grown counterparts. These findings highlight the potential of APV systems in promoting sustainable agriculture by balancing both crop yield and quality. Based on these results, the study suggests three innovative cultivation techniques to enhance crop growth in APV environments. Full article

Ammonia (NH₃) emissions affect the environment, the climate, and human health and originate mainly from agricultural sources like urea fertilizers. Such losses from urea fertilizer can be avoided by different application techniques like incorporation. However, the knowledge of the effect of these techniques on NH₃ emissions is very limited and ambiguous since incorporation can also promote nitrous oxide (N₂O) emissions. Three different principles of fertilizer incorporation methods were compared in three different soils (sandy, loamy, and clayey) at two moisture levels of 70% and 30% water-holding capacity (WHC), shallow mixing at 2 cm, injection with the slit technique at 5 cm, and deep complete incorporation at 5 cm simulating plow incorporation. The laboratory study was conducted with open dynamic incubation chambers where NH₃ emissions were monitored with washing bottles while N₂O emissions were studied with gas chromatographic (GC) measurements. The highest cumulative NH₃ emissions occurred at low soil moisture levels in sandy soil (34% of the N applied). A maximum reduction in emissions by 87% was achieved with slit injection and 82% with deep injection compared to standard surface application. The reduction effect was positively related to increasing clay content. N₂O emissions were delayed and highest from sandy soil. Overall, all urea incorporation techniques showed great potential for mitigating NH₃ emissions on the clayey soil; for sandy and drier soils, only deeper or closed slot injection were consistently effective. However, connected to the surface incorporation at the higher moisture level, a relevant increase in N₂O emissions compared to surface application was observed. Therefore, an increase in N₂O emissions by urea incorporation may rule out specific incorporation techniques for NH₃ emissions reduction from field-applied urea. In agricultural practice, a lower reduction in NH₃ by fertilizer incorporation can be assumed in sandy soils or under dry soil conditions, as well as a more challenging technical implementation. Full article

The role of the agrifood industry is key to mitigating the impact of climate change, as it is one of the industrial sectors with the highest energy consumption. The optimisation of photovoltaic systems in agroindustries faces problems such as the fluctuation of energy prices or the evident seasonal nature of some producers. This paper provides a global view of the profitability and optimal sizing of photovoltaic (PV) systems in the new energy context. For this purpose, almost 4 million cases were analysed, including different consumption patterns, energy prices, etc. Some general conclusions can be drawn from the results. First, the adaptation to the new context requires adjustments in the sizing of PV systems in all industries analysed, which is also associated with changes in the return on investment. Second, seasonality strongly conditions the optimal size of PV installations, the return on the investment and the potential savings. Finally, in the face of future energy price variations, the ratio “Savings/payback” seems to be an appropriate reference for sizing, combining savings and profitability. In addition, they may justify special subsidies to seasonal industries. The conclusions of this paper should be considered to optimise the design of PVs. Full article

Computer vision provides a real-time, non-destructive, and indirect way of horticultural crop yield estimation. Deep learning helps improve horticultural crop yield estimation accuracy. However, the accuracy of current estimation models based on RGB (red, green, blue) images does not meet the standard of a soft sensor. Through enriching more data and improving the RGB estimation model structure of convolutional neural networks (CNNs), this paper increased the coefficient of determination (R²) by 0.0284 and decreased the normalized root mean squared error (NRMSE) by 0.0575. After introducing a novel loss function mean squared percentage error (MSPE) that emphasizes the mean absolute percentage error (MAPE), the MAPE decreased by 7.58%. This paper develops a lettuce fresh weight estimation method through the multi-modal fusion of RGB and depth (RGB-D) images. With the multimodal fusion based on calibrated RGB and depth images, R² increased by 0.0221, NRMSE decreased by 0.0427, and MAPE decreased by 3.99%. With the novel loss function, MAPE further decreased by 1.27%. A MAPE of 8.47% helps to develop a soft sensor for lettuce fresh weight estimation. Full article

The potential benefits of applying information and communication technology (ICT) in precision agriculture to enhance sustainable agricultural growth were discussed in this review article. The current technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), as well as their applications, must be integrated into the agricultural sector to ensure long-term agricultural productivity. These technologies have the potential to improve global food security by reducing crop output gaps, decreasing food waste, and minimizing resource use inefficiencies. The importance of collecting and analyzing big data from multiple sources, particularly in situ and on-the-go sensors, is also highlighted as an important component of achieving predictive decision making capabilities in precision agriculture and forecasting yields using advanced yield prediction models developed through machine learning. Finally, we cover the replacement of wired-based, complicated systems in infield monitoring with wireless sensor networks (WSN), particularly in the agricultural sector, and emphasize the necessity of knowing the radio frequency (RF) contributing aspects that influence signal intensity, interference, system model, bandwidth, and transmission range when creating a successful Agricultural Internet of Thing Ag-IoT system. The relevance of communication protocols and interfaces for presenting agricultural data acquired from sensors in various formats is also emphasized in the paper, as is the function of 4G, 3G, and 5G technologies in IoT-based smart farming. Overall, these research sheds light on the significance of wireless sensor networks and big data in the future of precision crop production Full article

Plant in vitro cultures have been a crucial component of efforts to enhance crops and advance plant biotechnology. Traditional plant breeding is a time-consuming process that, depending on the crop, might take up to 25 years before an improved cultivar is available to farmers. This is a problematic technique since both beneficial qualities (such as pest resistance) and negative ones (such as decreased yield) can be passed down from generation to generation. In vitro cultures provide various advantages over traditional methods, including the capacity to add desirable characteristics and speed up the development of new cultivars. When it comes to oat (Avena sativa L.), the efficient method of plant regeneration is still missing compared to the most common cereals, possibly because this cereal is known to be recalcitrant to in vitro culture. In this review, an effort has been made to provide a succinct overview of the various in vitro techniques utilized or potentially involved in the breeding of oat. The present work aims to summarize the crucial methods of A. sativa L. cultivation under tissue culture conditions with a focus on the progress that has been made in biotechnological techniques that are used in the breeding of this species. Full article

Agronomic biofortification, encompassing the use of mineral and organic nutrient resources which improve micronutrient concentrations in staple crops is a potential strategy to promote the production of and access to micronutrient-dense foods at the farm level. However, the heterogeneity of smallholder farming landscapes presents challenges on implementing agronomic biofortification. Here, we test the effects of zinc (Zn)- and selenium (Se)-containing fertilizer on micronutrient concentrations of wheat (Triticum aestivum L.) and teff (Eragrostis tef (Zucc.) Trotter) grown under different landscape positions and with different micronutrient fertilizer application methods in the western Amhara region of Ethiopia. Field experiments were established in three landscape positions at three sites, with five treatments falling into three broad categories: (1) nitrogen (N) fertilizer rate; (2) micronutrient fertilizer application method; (3) sole or co-application of Zn and Se fertilizer. Treatments were replicated across five farms per landscape position and over two cropping seasons (2018 and 2019). Grain Zn concentration ranged from 26.6 to 36.4 mg kg⁻¹ in wheat and 28.5–31.2 mg kg⁻¹ in teff. Grain Se concentration ranged from 0.02 to 0.59 mg kg⁻¹ in wheat while larger concentrations of between 1.01 and 1.55 mg kg⁻¹ were attained in teff. Larger concentrations of Zn and Se were consistently attained when a foliar fertilizer was applied. Application of ⅓ nitrogen (N) yielded significantly larger grain Se concentration in wheat compared to a recommended N application rate. A moderate landscape effect on grain Zn concentration was observed in wheat but not in teff. In contrast, strong evidence of a landscape effect was observed for wheat and teff grain Se concentration. There was no evidence for any interaction of the treatment contrasts with landscape position except in teff, where an interaction effect between landscape position and Se application was observed. Our findings indicate an effect of Zn, Se, N, landscape position, and its interaction effect with Se on grain micronutrient concentrations. Agronomic biofortification of wheat and teff with micronutrient fertilizers is influenced by landscape position, the micronutrient fertilizer application method and N fertilizer management. The complexity of smallholder environmental settings and different farmer socio-economic opportunities calls for the optimization of nutritional agronomy landscape trials. Targeted application of micronutrient fertilizers across a landscape gradient is therefore required in ongoing agronomic biofortification interventions, in addition to the micronutrient fertilizer application method and the N fertilizer management strategy. Full article

Vertical farming is experiencing significant growth, and the optimization of artificial lighting is essential for enhancing the sustainability of this growing system. Therefore, the aim of this study was to examine how light segmentation, the incorporation of a low-intensity lighting phase known as the light compensation point (LCP) instead of the traditional dark phase, and variations in the light spectrum impact the agricultural outcomes of organically cultivated leafy greens. In controlled growth chamber environments, a variety of leafy plant species (Spinacia oleracea L., Ocimum basilicum, Beta vulgaris L., Lactuca sativa L. cv. ‘Garrison’ and ‘Blade’, Brassica rapa cv. ‘Japonica’ and ‘Chinensis’, Brassica juncea cv. ‘Scarlet Frills’ and ‘Wasabina’, Eruca sativa and Perilla frutescens L.) were subjected to four light treatments with varying intensities and durations of lighting, while in a second experiment, five different spectral growing conditions were compared. Irrespective of the plant species, shortening the length of the diel cycle by extending the cumulative daily lighting to 20–24 h per day (5L/1N [5 h at 261 µmol m⁻² s⁻¹ + 1 h darkness for a total of 20 h of light per day] and 5L/1LCP [5 h at 256 µmol m⁻² s⁻¹ + 1 h LCP at 20 µmol m⁻² s⁻¹ for a total of 24 h of light per day]) led to an average increase of +12% in height, fresh weight (+16%), dry weight (+23%), and specific leaf weight (+11%), compared to the control plants (18L/6N; 18 h at 289 µmol m⁻² s⁻¹ + 6 h darkness) and 6L/6LCP plants (6 h at 418 µmol m⁻² s⁻¹ + 6 h LCP at 20 µmol m⁻² s⁻¹ for a total of 24 h of light per day) during the first harvest. This also resulted in better light utilization, expressed as increased fresh (+16%) and dry (+24%) biomass per mol of light received. Conversely, the studied light spectral treatments had no effect on the growth parameters of the four selected species. In conclusion, our study showed that reducing light intensity while extending the photoperiod could potentially represent a cost-effective LED strategy for the indoor cultivation of organically or conventionally grown leafy greens. Full article

Perennial crops, especially legumes, have a crucial role in the development of sustainable agriculture. One such species may be fodder galega (Galega orientalis Lam.), whose utility values, including persistence and multi-directional use, are still not sufficiently known and appreciated. The aim of this study was to evaluate fodder galega yield dynamics, taking into account some indices of fodder value and the accumulation of mineral components in long-term use in light soil under moderate climate conditions with periodic shortages of precipitation. The results of six long-term experiments conducted at the Mochełek Research Station (53°120′ N, 17°510′ E) were evaluated. The dynamics of dry matter, total protein yield, and accumulation of minerals were best reflected by trend lines in the form of logarithmic functions, where during the first 4–5 years of use, a significant increase in the assessed values was noted, and in subsequent years, the increase continued but at a lower rate. The advancement in plant development in the establishment year had a significant impact on yields in the first production year. On average, during 10 production years, the dry matter yield obtained was 936 g m², and the total protein yield was 177 g m². Between 50% and 60% of the yield was determined by herbage accumulation in the first cut. Among minerals, the highest accumulation level was achieved for potassium. The height of shoots and the content of crude fiber in the plants increased linearly in the following years. The shoot density, leafiness, and content of minerals did not depend on the age of the galega stand, and their values were different among growth periods within a season. The number of shoots per 1 m² in successive cuts was 170, 139, and 92, and their height was 79, 67, and 31 cm, respectively. The share of leaves in the first cut yield was 50%, and in the second and third cuts, it was 65% on average. In these conditions, over 10 years of use, galega turned out to be a valuable, persistent, and reliably yielding fodder crop. Full article

Plant height is a crucial phenotypic trait that plays a vital role in predicting cotton growth and yield, as well as in estimating biomass in cotton plants. The accurate estimation of canopy height from single-flight LiDAR data remains a formidable challenge in current high-density cotton cultivation patterns, where dense foliage obstructs the collection of bare soil terrain, particularly after flowering. The existing LiDAR-based methods for cotton height estimation suffer from significant errors. In this study, a new method is proposed to compensate for the canopy height estimation by using the canopy laser interception rate. The ground points are extracted by the ground filtering algorithm, and the interception rate of the laser per unit volume of the canopy is calculated to represent the canopy density and compensate for the cotton height estimation. The appropriate segmented height compensation function is determined by grouping and step-by-step analysis of the canopy laser interception rate. Verified by 440 groups of height data measured manually in the field, the results show that the canopy laser interception compensation mechanism is of great help in improving the estimation accuracy of LiDAR. R² and RMSE reach 0.90 and 6.18 cm, respectively. Compared with the estimation method before compensation, R² is increased by 13.92%, and RMSE is reduced by 49.31%. And when the canopy interception rate is greater than 99%, the compensation effect is more obvious, and the RMSE is reduced by 62.49%. This research result can significantly improve the height estimation accuracy of UAV-borne for high planting density cotton areas, which is helpful to improve the efficiency of cotton quality breeding and match genomics data. Full article

Insects have developed dormancy mechanisms to survive coldness in winters. The specific forms of winter dormancy, however, vary among different geographical and climatic zones and species. While there is extensive research on winter dormancy in insect pests and parasitoids in temperate zones, our understanding of how predatory insects, such as predatory stink bugs in subtropical regions, cope with cold winters and the specific forms of dormancy they undergo remains limited. The effects of winter temperatures on the population dynamics, development, and reproduction of the predatory stink bug Eocanthecona furcellata in the subtropics were investigated through greenhouse and laboratory experiments. E. furcellata exhibits two distinct peaks in population distribution throughout the year: one in April–May and another in October–November. Interestingly, the proportions of adults show an opposite pattern to the population dynamics, with the highest proportions of adults observed during the winter and summer seasons, when temperatures are the lowest and the highest, respectively. Laboratory studies showed that E. furcellata reared at lower temperatures (16 °C, 18 °C, and 20 °C) experienced prolonged development and higher mortality rates for eggs and nymphs compared to higher temperatures (22 °C and 26 °C). Further experiments observed that E. furcellata adults reared at 16 °C, 18 °C, and 20 °C entered into winter dormancy, where ovarian development was either completely halted or slowed down. The observed high proportion of E. furcellata adults and low proportion of nymphs during the cold winter months align well with the dormancy period. This study sheds light on the underlying mechanisms driving the population dynamics of E. furcellata during the subtropical winter. These findings have significant implications in accurately predicting the population dynamics of E. furcellata, implementing effective field release strategies, and optimizing cold storage techniques in the context of biological control programs. Full article

Pollination is essential for the reproductive output of crops. Anthropogenic disturbance and global pollinator decline limit pollination success, reducing the quantity or quality of pollen. Relationships between the abundance of flower visitors and fruit production are often poorly understood. We aimed to (1) identify and quantify flower visitors in a mango orchard; (2) assess how much of the crop resulted from self- versus cross-pollination at increasing distances from a cross-pollen source in large, single-cultivar blocks of the cultivar Kensington Pride or the cultivar Calypso; and (3) determine how pollen parentage affected the size, colour, flavour attributes, and nutritional quality of fruit. Mango flowers were mostly visited by rhiniid flies and coccinellid beetles. Approximately 30% of the fruit were the result of cross-pollination, with the percentage significantly decreasing with an increasing distance from a cross-pollen source in the cultivar Calypso. Self-pollinated Calypso fruit were slightly larger and heavier, with higher acid and total polyphenol concentrations than cross-pollinated fruit. Our results showed higher-than-expected levels of cross-fertilisation among fruit, although self-pollen was likely more abundant than cross-pollen in the large orchard blocks. Our results suggest the preferential cross-fertilisation of flowers or the preferential retention of cross-fertilised fruitlets, both representing strategies for circumventing inbreeding depression. Growers should establish vegetated habitats to support pollinator populations and interplant cultivars more closely to maximise cross-pollen transfer. Full article

In recent years, the decrease in solar radiation has led to insufficient light, resulting in a shading effect on crops and a deterioration of stem quality, which seriously affects wheat yield. In this experiment, two different lodging-sensitive wheat varieties, SN16 (SN16) and SN23 (SN23), were selected as experimental materials, and two treatments were set up, with 50% shade (S1) and natural light as control (S0) from the jointing stage to the maturity stage. Two treatments, spraying 400 mg L⁻¹ (C1) silicon fertilizer and spraying water as control (C0), were set up at the jointing stage of wheat. The effects of spraying silicon fertilizer on the yield, morphological and mechanical characteristics of the stem, and lignin content of winter wheat under low-light stress were investigated. The results showed that spraying silicon fertilizer increased the lignin content of the stem and improved stem lodging resistance mainly by improving the degree of lignification. An effective cultivation measure for wheat’s resistance to lodging can be provided by spraying silicon fertilizer when future low-light stress occurs. Full article

The mineralization of nitrogen in apple orchard soil will increase the soil supply. An incubation study to test the soil potential and the validity of analytical methods was conducted at 3, 8, 15, and 20 °C for up to 128 days on soils from western and south-eastern Norway. Soils with the highest pH showed the highest mineralization. The mineralization increased with increasing temperature and time, but start-up N reduced mineralization. The mineralization cannot be estimated from standard soil chemical parameters because the different C/N ratio indicates organic material of different origin and quality. The increase in NO₃-N started very quickly and ranged from 17 to 182% and 12 to 64% after 8 days at 3 °C and 20 °C, respectively. There was no correlation between total N in the soil and the amount of mineralized N. On average, the mineralization increased by 5–7% for a change of 1 °C in the interval from 8 to 15 °C in the soil. The chemical extraction method using heated KCl correlated well with the mineralization data. On average, the chemical method estimated 30 kg N ha⁻¹, which corresponded to 0.48% of total N. Recommendations for N fertilization based on total N in the soil overestimate the contribution of plant-available N in most cases. Full article

Intensive irrigation and nutrient management practices in agriculture have given rise to serious issues in aquifer water depletion and groundwater quality. This review discusses the effects of irrigation and nitrogen management practices on potato growth, yield, and quality, and their impacts on water and nitrogen use efficiencies. This review also highlights the economics and consequences of applying deficit irrigation strategies in potato production. Many researchers have demonstrated that excessive irrigation and nitrogen application rates negatively impact potato tuber yield and quality while also increasing nitrate leaching, energy consumption, and the overall costs of production. An application of light-to-moderate deficit irrigation (10–30% of full irrigation) together with reduced nitrogen rates (60–170 kg/ha) has a great potential to improve water and nitrogen use efficiencies while obtaining optimum yield and quality in potato production, depending on the climate, variety, soil type, and water availability. There is an opportunity to reduce N application rates in potato production through deficit irrigation practices by minimizing nitrate leaching beyond the crop root zone. The best irrigation and nitrogen management techniques for potato production, as discussed in this review, include using sprinkle and drip irrigation techniques, irrigation scheduling based on local crop coefficients, soil moisture content, and crop modeling techniques, applying slow-release nitrogenous fertilizers, split nitrogen application, and applying water and nitrogenous fertilizers in accordance with crop growth stage requirements. Full article

The changing climate and the projected increase in the variability and frequency of extreme events make accurate predictions of crop yield critically important for addressing emerging challenges to food security. Accurate and timely crop yield predictions offer invaluable insights to agronomists, producers, and decision-makers. Even without considering climate change, several factors including the environment, management, genetics, and their complex interactions make such predictions formidably challenging. This study introduced a statistical-based multiple linear regression (MLR) model for the forecasting of rainfed maize yields in Kansas. The model’s performance is assessed by comparing its predictions with those generated using the Decision Support System for Agrotechnology Transfer (DSSAT), a process-based model. This evaluated the impact of synthetic climate change scenarios of 1 and 2 °C temperature rises on maize yield predictions. For analysis, 40 years of historic weather, soil, and crop management data were collected and converted to model-compatible formats to simulate and compare maize yield using both models. The MLR model’s predicted yields (r = 0.93) had a stronger association with observed yields than the DSSAT’s simulated yields (r = 0.70). A climate change impact analysis showed that the DSSAT predicted an 8.7% reduction in rainfed maize yield for a 1 °C temperature rise and an 18.3% reduction for a 2 °C rise. The MLR model predicted a nearly 6% reduction in both scenarios. Due to the extreme heat effect, the predicted impacts under uniform climate change scenarios were considerably more severe for the process-based model than for the statistical-based model. Full article

A web mapping XYZ Tile Layer Service, such as Google Earth (GE), provides an amazing resource for the visualization of spatial data against aerial and satellite imagery with global coverage, typically at a resolution finer than 5 m. However, the increasing requirement on spatial accuracy in farm information requires a greater appreciation of the issues involved in the use of such services. Position errors can be created in the georeferencing and orthorectification of images, transformation between reference frames (datums) in map projection, e.g., using a spheroid as compared to an ellipsoid earth model, and tectonic shifts. A review is provided of these issues, and a case study is provided of the horizontal positional accuracy of web map imagery for Australian mango orchards. Positional accuracies varied from 1.804 to 6.131 m across four farms using GE 2021 imagery, between 1.556 and 3.365 m in one farm for the most recent imagery available from each of four web map providers, and from 0.806 m (in 2016) to 10.634 m (in 2003) in one farm for the period of 2003 and 2021 using the historical GE imagery resource. A procedure involving the estimation of four transformation parameters was demonstrated for the alignment of GNSS data with GE imagery. However, as the scale factor was unity and the rotational value was near zero, the use of a simple horizontal mean shift vector was recommended. Further recommendations are provided on (i) the use of web mapping services, with a comparison of the use of UAV survey imagery, and (ii) the need for metadata, particularly the date of collection, on collected position data, in the context of use in farm management information systems. Full article

Information regarding the relative importance of elevated day/night-time temperatures combined with water stress on mungbean yield is limited. This study aimed to investigate the yield response of mungbean cultivars to different water stress and temperature regimes under controlled glasshouse conditions. Two mungbean cultivars, Celera II-AU and Jade-AU, were grown and evaluated under four temperature regimes with and without water stress, each replicated 10 times in a randomized complete block design. The four temperature regimes were as follows: (i) HTHT: Plants were consistently exposed to high day/high night temperatures (35/25 °C). (ii) LTHT: Plants experienced ambient day/ambient night temperatures (25/15 °C) for the first 35 days, followed by the HTHT environment. (iii) LTLT: Plants were maintained at ambient day/ambient night temperatures (25/15 °C) throughout the experiment. (iv) HTLT: Plants were subjected to high day/high night temperatures (35/25 °C) for the initial 35 days, followed by the LTLT environment. Under water stress conditions, mungbean yield declined significantly in the HTHT environment by 57% for Jade-AU and 76% for Celera II-AU compared to the LTLT environment. The highest seed yield (10.2 g plant⁻¹ for Jade-AU and 11.4 g plant⁻¹ for Celera II-AU) for both cultivars was observed when grown without water stress in the LTLT environment. However, yield decreased substantially when plants experienced combined heat and water stress during the reproductive stage (HTHT and LTHT environments). Without water stress, mungbean yield under the HTHT environment decreased by 30% for Jade-AU and 60% for Celera II-AU compared to the LTLT environment. Surprisingly, no significant difference in response to water stress was observed between the two cultivars. Furthermore, when grown under no-water stress and HTHT environments, the yield of Celera II-AU was reduced by 37% compared to Jade-AU. Similarly, a comparable response was seen between cultivars under no-water stress and LTHT environment. The results indicated that water and heat stress negatively affected mungbean seed yield. Moreover, it was observed that Jade-AU outperformed Celera II-AU regarding seed yield under heat-stress conditions. In conclusion, this study suggests that adjusting sowing time and selecting suitable heat-tolerant cultivars, such as Jade-AU, could enhance mungbean yield under heat and water stress conditions. The results demonstrate substantial impacts on mungbean productivity from changing climatic and water stress conditions and these findings can be utilized for improving mungbean productivity in dryland regions. Full article

This study investigated the effects of substituting B with FR and UVA (50 μmol·m⁻²·s⁻¹) at two growth stages on the growth and quality of loose-leaf lettuce (cv. Fangni). The basal light was red and blue LEDs at 250 μmol·m⁻²·s⁻¹. At stage I (the first 10 days of 20-day pre-harvest), there were three treatments: B substituted by FR (FR); B substituted by UVA (UVA); and no substituting (CKI). At stage II (next ten days after stage I), there were 9 treatments: FF (FR + FR), UF (UVA + FR), BF (B + FR), FU (FR + UVA), UU (UVA + UVA), BU (B + UVA), FB (FR + B), UB (UVA + B), and B + B (CKII). At stage I, compare with UV-A and CKI, the shoot fresh weight, leaf area, leaf width, leaf length, and vitamin C content highly increased under far-red light (FR), whereas specific leaf weight and the chlorophyll contents significantly decreased by FR. In CKI, nitrate contents and the antioxidant capacity (FRAP, DPPH) were significantly higher than in FR and UVA. At stage II, higher leaf width, leaf length, leaf area, and shoot fresh and dry weight were observed in FF, UF, and BF. The lowest biomass was shown in CKII. Higher chlorophyll contents were found in FU and FB. The soluble sugar contents significantly increased by all treatments. In addition to UB and BU, soluble protein contents increased by other treatments. There were higher vitamin C contents in UU, UB, and CKII. Large amounts of nitrates accumulated under CKII. The higher antioxidant capacity (DPPH, FRAP) was found in FB and CKII. The highest flavonoid content was found in UB, and higher polyphenols contents were found in UB and BU. In this study, substituting B with FR at 2 stages were the best way to increase lettuce biomass. The optimal measure to both increased lettuce nutrition quality and biomass was FB at stage II. Full article

Since the introduction of genetically modified (GM) glyphosate-resistant crops, especially in Australia, the United States, and Canada, the use of glyphosate has exploded, raising concerns about its environmental effects both in terrestrial and aquatic environments. There are several factors that can affect the transport of glyphosate in soil, including the pH of the soil, the iron and aluminium oxides in the soil, and the structure of the soil, as well as the application time and microbial biodegradation in the soil. Furthermore, some field studies have shown that glyphosate, along with its degradation products, can be found deep in the aquatic environment and can contaminate groundwater by leaching, which implies that studying glyphosate leaching through agricultural soils is very crucial. The research in this study involves column-leaching experiments on glyphosate-dosed soils using application and flow rates representative of field conditions with bromide as a non-reactive tracer. To determine whether the observed behaviour of glyphosate is consistent with commonly recognized transport processes, the results obtained were incorporated into a one-dimensional transport model (HYDRUS 1D). Initially, physical transport parameters were determined by fitting experimental bromide breakthrough curves (BTCs) with analytical solutions to advection–dispersion equations (ADEs) for pulse boundary conditions at the upper end and zero-gradient conditions at the lower end. Then, these parameters and those from the sorption experiments were used in HYDRUS 1D to describe glyphosate transport behaviour. After three different glyphosate applications, the columns with soils C and A showed the highest glyphosate leaching rates, which is closely related to their macropore structures since bromide also leached at higher rates. A similar lower glyphosate leaching rate was found for soil B as for bromide BTC, indicating that competition between phosphorus and glyphosate for sorption sites did not result in higher rates of leaching. Full article

Spring barley (Hordeum vulgare L.) is an increasingly important cash crop in the province of Quebec (Canada). Soil–crop models are powerful tools for analyzing and supporting sustainable crop production. STICS model has not yet been tested for spring barley grown over several decades. This study was conducted to calibrate and evaluate the STICS model, without annual reinitialization, for predicting aboveground biomass and N nutrition attributes at harvest during 31 years of successive cropping of spring barley grown in soil (silty clay, Humic Gleysol) from the Saguenay–Lac-Saint-Jean region (northeastern Quebec, Canada). There is a good agreement between observed and predicted variables during the 31 successive barley cropping years. STICS predicted well biomass accumulation and plant N content with a low relative bias (|normalized mean error| = 0–13%) and small prediction error (normalized root mean square error = 6–25%). Overall, the STICS outputs reproduced the same trends as the field-observed data with various tillage systems and N sources. Predictions of crop attributes were more accurate in years with rainfall close to the long-term average. These ‘newly calibrated’ parameters in STICS for spring barley cropped under continental cold and humid climates require validation using independent observation datasets from other sites. Full article

Plastic film mulching has been widely used to improve crop yield and water use efficiency, although the effects of plastic film mulching on water, heat, nitrogen dynamics, and crop growth are rarely presented comprehensively. This study investigated a large number of studies in film mulching fields from the past 10 years (mostly from 2019 to 2023) and summarized the impact of plastic film mulching, progress in modeling with film mulching, and future research directions. The effects of plastic film mulching were intricate and were influenced by film mulching methods, irrigation systems, crop types, crop growth stages, etc. Overall, plastic film mulching showed a positive effect on improving soil water, temperature, and nitrogen status, enhancing crop transpiration and photosynthetic rates, and promoting crop growth and yield, although film mulching may have negative effects, such as increasing rainfall interception, blocking water entering the soil, and reducing net radiation income. The crop yield and water use efficiency could increase by 39.9–84.7% and 45.3–106.4% under various film mulching methods. Coupled models of soil water and heat transport and crop growth under plastic film mulching conditions have been established by considering the effects of plastic film mulching on the upper boundary conditions of soil water and heat, energy budget and distribution processes, and the exchange of latent and sensible heat between soil and atmosphere. The models have good applicability in film mulched farmland of maize, rice, and potato for different regions of China. Further development is needed for soil water, heat, nitrogen migration, and crop growth models under different plastic film mulching methods, and the acquisition of soil and crop indicators under plastic film mulching conditions based on big data support. The study will provide reference for the subsequent development and innovation of plastic film mulching technology. Full article

Intercropping using mixtures of dryland crop species for grain or seed production was investigated in southern Australia across a range of rainfall zones over three years. The objective was to understand the productivity and profitability of intercropping in extensive, high-input grain cropping systems. Previous research has shown large productivity benefits of mixtures; however, few farmers practice intercropping in Australia, and an analysis of profitability is needed to support future potential adoption. Experimental results showed strong mixture responses (in terms of yield, value and land equivalence), but not all were profitable compared to an equivalent share of monoculture crops (as measured by gross margins). The most promising mixtures were those containing high-value crops (canola) and legumes (field pea or faba bean) at the wetter sites where the additional gross margin over equivalent monoculture crops ranged from $12/ha to $576/ha. Mixtures containing highly competitive crops (wheat or barley) were generally unprofitable. Mixtures involving cereals were doubly disadvantaged by the aggressiveness of these lower-value crops in the mixtures we examined and the high grain separation costs post-harvest. Cost reduction in mixture systems involving high-value crops that are synergistic (grain legumes) should provide enduring opportunities for intercropping in southern Australia. Full article

Spain is one of the main producers of black truffle (Tuber melanosporum Vittad.), a fungus of great economic importance. Black truffles are usually cultivated in Quercus ilex orchards, as water availability is one of the most important factors influencing truffle production. Optimizing watering systems is essential to reduce the amount of water wasted. Nevertheless, up to now, no study has been carried out comparing the efficiency of different irrigation systems in truffle plantations. The aim of this study was to compare the efficiency of two different irrigation systems, namely a drip irrigation system and a micro-sprinkler system, in a Quercus ilex plantation situated in Burgos, Spain. Our data showed that there were no differences between the two irrigation systems in terms of truffle yields, the number of truffles, quality (based on truffle size), or the date of truffle harvesting. However, when other parameters were taken into consideration, such as the economic and environmental impact of installing and running these systems, drip irrigation was deemed the superior irrigation system because it uses less water. This study validates for the first time the use of drip irrigation rather than a micro-sprinkler system (the most commonly used in truffle plantations) because of its greater water use efficiency, which is an increasingly important consideration given future climate change scenarios marked by global water scarcity. Full article

Unmanned farms employ a variety of sensors, automated systems, and data analysis techniques to enable fully automated and intelligent management. This not only heightens agricultural production efficiency but also reduces the costs associated with human resources. As integral components of unmanned farms’ automation systems, agricultural UAVs have been widely adopted across various operational stages due to their precision, high efficiency, environmental sustainability, and simplicity of operation. However, present-day technological advancement levels and relevant policy regulations pose significant restrictions on UAVs in terms of payload and endurance, leading to diminished task efficiency when a single UAV is deployed over large areas. Accordingly, this paper aggregates and analyzes research pertaining to UAV swarms from databases such as Google Scholar, ScienceDirect, Scopus, IEEE Xplorer, and Wiley over the past decade. An initial overview presents the current control methods for UAV swarms, incorporating a summary and analysis of the features, merits, and drawbacks of diverse control techniques. Subsequently, drawing from the four main stages of agricultural production (cultivation, planting, management, and harvesting), we evaluate the application of UAV swarms in each stage and provide an overview of the most advanced UAV swarm technologies utilized therein. Finally, we scrutinize and analyze the challenges and concerns associated with UAV swarm applications on unmanned farms and provide forward-looking insights into the future developmental trajectory of UAV swarm technology in unmanned farming, with the objective of bolstering swarm performance, scalability, and adoption rates in such settings. Full article

Strawberries are a very important economic crop; thus, a lot of research has been conducted on several production areas. However, phenological performance is still lacking information, especially when it comes to modeling. Therefore, this study aims to develop a phenological model for flower–fruit development under hydroponic conditions to support growers’ decision-making. Two day-neutral cultivars, ‘Albion’ and ‘San Andreas’, were established in a drip hydroponic system in Auburn, Alabama for the 2022–2023 production season. Phenological data were collected daily on 30 flowers per cultivar for three periods (Oct 25–Dec 16, Dec 27–Feb 21, and Feb 28–Apr 16). Weather data were obtained from a weather station placed in the greenhouse. Growing degree days (GDD) accumulation was calculated for each stage and cycle using a base temperature (Tb) of 3 °C. The Gaussian model was adjusted for each stage and cycle using a non-linear procedure to obtain Gaussian curves. Simulations were made for the model assuming temperature would increase or decrease by 1 °C. Six stages were identified, and their cycle ranged from 43–56 days to be accomplished. ‘Albion’ needed more days to reach maturity, with 51, 56, and 47 days, and ‘San Andreas’ took 43, 54, and 46 days for cycles 1, 2, and 3 respectively. In addition, for cycles 1 and 2, not all the buds reached maturity, as expected. Stage 5 (fruit formation) needed more days than the rest of the stages to be completed. Because of the different starting dates for each cycle, the starting GDD was different as well. A sensitivity analysis simulation of the model showed that if temperature decreases by 1 °C, the GDD accumulated to complete the stages would be less (same dates), and it would be more if the temperature increased by 1 °C. The opposite happened with the days, if the temperature increased by 1 °C, the duration of the stage decreased, and it would increase if the temperature decreased by 1 °C, affecting stages 4, 5, and 6. Overall, ‘San Andreas’ performed better than ‘Albion’ under hydroponic conditions during three productive cycles. Full article

The use of sulfur is an important factor in potato production. At the beginning of this study, a hypothesis was put forward according to which sulfur carrier affects yield (TY) and nitrogen efficiency (EN). The three-year study was conducted in a two-factor system: (1) sulfur fertilization, SF (control—without S, elemental sulfur—S⁰, calcium sulfate—CS), and (2) nitrogen fertilization level, NF (0, 30, 60, 90, 120, and 150 kg N·ha⁻¹). In addition to TY, the following EN indicators were analyzed: agronomical efficiency (EA), physiological efficiency (EPh), partial factor productivity (PFP), and recovery (R). For both sources of sulfur, an increase in TY was confirmed. After applying CS, the optimum for the maximum yield was 106 kg N·ha⁻¹, while the application of S⁰ resulted in 134 kg N·ha⁻¹. The impact of SF on the nitrogen economy decreased in the direction of EA = PFP > EF > R and depended on the sulfur carrier. A positive trend was found, associated with the increase in R under the influence of S⁰ and the clearly higher EPh after the application of CS. A particularly strong effect of CS on EA was evident in the range of lower nitrogen doses. The EN values depended on the meteorological conditions during the research years. The strongest variability was subject to EPh, which, as a result of SF, was significantly higher in relation to the control (without S) during the growing season, with an unfavorable distribution of precipitation. The application of CS reduced the unit nitrogen uptake (UU-N). Using path analysis, a direct relationship of Ca accumulation (controlled by N and S) with TY was demonstrated. The conducted research indicates a significant impact of sulfur fertilizers, related to TY and EN, especially visible under conditions of limited nitrogen supply. Full article

Despite their importance for biodiversity and other ecosystem services, many semi-natural grasslands deteriorate or have even disappeared due to insufficient grazing and neglect. Preservation of grassland habitats depends on a good understanding of sustainable grazing management as well as effective agricultural policy measures that ensure long-term economic sustainability for the farmer. Through meta-evaluation and synthesis of previous investigations and discussion of scientific literature, we aimed to evaluate factors that determine the extent to which cattle and sheep in Sweden graze semi-natural grasslands instead of more productive land and what this means for biodiversity and sustainability. We also aimed to propose which practises and policy measures may be the most cost-effective to promote habitat quality and the sustainable use of grasslands. Results from a nationwide survey of Swedish farmers’ attitudes towards agri-environmental payment schemes are discussed in relation to farm characteristics and other factors influencing the use of cattle and sheep for sustainable grazing. This study supports recommendations by environmental economists that payments should be targeted more strongly at the most valuable grasslands, emphasising the need for a more detailed and nuanced framework for classifying grasslands in Europe. A comparison with independent estimates of the area of agricultural land from nation-wide, sample-based monitoring shows that the data from official statistics normally used for nationwide evaluations are partly biased and of insufficient quality, underscoring the need for more sophisticated and precise methods for monitoring both overall trends and detailed environmental effects related to the preservation of semi-natural grasslands. Full article

This study focuses on assessing the accuracy of supervised machine learning regression algorithms (MLAs) in predicting actual crop evapotranspiration (ETc act) for a deficit irrigated vineyard of Vitis vinifera cv. Tempranillo, influenced by a typical Mediterranean climate. The standard approach of using the Food and Agriculture Organization (FAO) crop evapotranspiration under standard conditions (FAO-56 Kc-ET₀) to estimate ETc act for irrigation purposes faces limitations in row-based, sparse, and drip irrigated crops with large, exposed soil areas, due to data requirements and potential shortcomings. One significant challenge is the accurate estimation of the basal crop coefficient (Kcb), which can be influenced by incorrect estimations of the effective transpiring leaf area and surface resistance. The research results demonstrate that the tested MLAs can accurately estimate ETc act for the vineyard with minimal errors. The Root-Mean-Square Error (RMSE) values were found to be in the range of 0.019 to 0.030 mm·h⁻¹. Additionally, the obtained MLAs reduced data requirements, which suggests their feasibility to be used to optimize sustainable irrigation management in vineyards and other row crops. The positive outcomes of the study highlight the potential advantages of employing MLAs for precise and efficient estimation of crop evapotranspiration, leading to improved water management practices in vineyards. This could promote the adoption of more sustainable and resource-efficient irrigation strategies, particularly in regions with Mediterranean climates. Full article

The biological activity (contact and contact-digestive toxicity, repellent and fumigant effects, effect on the insect’s development and life cycle parameters) of industrial hemp (Cannabis sativa L.) ethanolic extract was assessed against Plodia interpunctella, the most destructive storage pest of sunflower. Additionally, the study aimed to examine the phytotoxic activity of the extract in order to assess its potential as a sunflower grain protectant. Phytotoxicity assessment was based on the effect on germination energy and seed germination and the activity of antioxidative enzymes, enzymes of the polyphenolic metabolism, and the intensity of lipid peroxidation in sunflower seedlings. The antioxidant capacity and content of phenolic compounds (total phenolics and total tannins) were also measured in seedlings. In the experiments, 70% ethanolic extract of dried flowering buds of industrial hemp (variety Helena) was applied at 0.5%, 1.0% and 2.0% concentrations directly on sunflower seeds. Ethanol solution (70%) was the control. The hemp extract (1% and 2%) revealed medium repellence for P. interpunctella larvae (L_3–4) while at 2% concentration it caused 42.5% larval mortality after 72 h. Moreover, the insect’s development was prolonged and fecundity significantly reduced in hemp treatments. The extract did not exhibit fumigant activity. Germination energy and germination of sunflower seeds were stimulated in treatment with 2% hemp extract, while most biochemical parameters of the seedlings were not significantly affected by the hemp extract. Full article

Going beyond previous work, this paper presents a systematic literature review that explores the deployment of satellites, drones, and ground-based sensors for yield prediction in agriculture. It covers multiple aspects of the topic, including crop types, key sensor platforms, data analysis techniques, and performance in estimating yield. To this end, datasets from Scopus and Web of Science were analyzed, resulting in the full review of 269 out of 1429 retrieved publications. Our study revealed that China (93 articles, >1800 citations) and the USA (58 articles, >1600 citations) are prominent contributors in this field; while satellites were the primary remote sensing platform (62%), followed by airborne (30%) and proximal sensors (27%). Additionally, statistical methods were used in 157 articles, and model-based approaches were utilized in 60 articles, while machine learning and deep learning were employed in 142 articles and 62 articles, respectively. When comparing methods, machine learning and deep learning methods exhibited high accuracy in crop yield prediction, while other techniques also demonstrated success, contingent on the specific crop platform and method employed. The findings of this study serve as a comprehensive roadmap for researchers and farmers, enabling them to make data-driven decisions and optimize agricultural practices, paving the way towards a fully digitized yield prediction. Full article

Phenological shifts in peaches have been observed over the last few years due to the fluctuation of the seasonal climate conditions experienced during dormancy, affecting orchard management practices and influencing production and harvest dates. This study aimed to model the vegetative and floral budbreak of selected peach cultivars. Three peach cultivars, including “Rubyprince”, “Harvester”, and “Red Globe”, were considered in this study based on the representation of the early, early-mid, and mid-seasons. The prediction of the budbreak in peaches was assessed using different models that integrate the combination of chill and heat requirements. Models used include the Weinberger model, the modified Weinberger model, Utah, the dynamic model, and the growing degree model. The accumulation of chill varies according to the season evaluated. A model that considers both chill and heat accumulation is presented for each cultivar. Budbreak as an indicator of dormancy completion was established for each cultivar. The outcome of this study is to determine the amount of chilling accumulation and thermal time required to mark the beginning of the budbreak in selected cultivars with a model that predicts the duration of the dormancy. These results are valuable information that can be used for crop management practices and support the mitigation of cold damage during this critical period of crop development. Full article

To detect quickly and accurately “Yuluxiang” pear fruits in non-structural environments, a lightweight YOLO-GEW detection model is proposed to address issues such as similar fruit color to leaves, fruit bagging, and complex environments. This model improves upon YOLOv8s by using GhostNet as its backbone for extracting features of the “Yuluxiang” pears. Additionally, an EMA attention mechanism was added before fusing each feature in the neck section to make the model focus more on the target information of “Yuluxiang” pear fruits, thereby improving target recognition ability and localization accuracy. Furthermore, the CIoU Loss was replaced with the WIoUv3 Loss as the loss function, which enhances the capability of bounding box fitting and improves model performance without increasing its size. Experimental results demonstrated that the enhanced YOLO-GEW achieves an F1 score of 84.47% and an AP of 88.83%, while only occupying 65.50% of the size of YOLOv8s. Compared to lightweight algorithms such as YOLOv8s, YOLOv7-Tiny, YOLOv6s, YOLOv5s, YOLOv4-Tiny, and YOLOv3-Tiny; there are improvements in AP by 2.32%, 1.51%, 2.95%, 2.06%, 2.92%, and 5.38% respectively. This improved model can efficiently detect “Yuluxiang” pears in non-structural environments in real-time and provides a theoretical basis for recognition systems used by picking robots. Full article

Throughout the world, salinity is a major environmental issue that limits agricultural productivity, particularly in arid and semi-arid regions. In addition, climate change is the most important reason for the salinization of agricultural soils in the world, so it is now essential to find solutions to increase salinity tolerance in plants. This study investigated the potential of arbuscular mycorrhizal fungi (AMF) inoculation to enhance the growth and yield performances of flax under different salinity levels by conducting a pot experiment. The experiment was laid out in a two-factor completely randomized design including AMF inoculation (AMF+: with inoculation; AMF−: without inoculation) and irrigation water salinity (0, 50, 100, and 150 mM NaCl). According to the results, it is evident that salt stress caused negative physiological effects, including limited growth, reduced photosynthesis, and decreased nitrogen (N) and phosphorus (P) content in the shoots and roots of flax plants. Moreover, mycorrhizal association improved the salt tolerance of the plants by increasing chlorophyll content, and enhancing N and P shoot and root contents and consequently yield parameters, such as seed and stem fiber yield, particularly at moderate salt concentrations (50 and 100 mM NaCl). In particular, under 100 mM, AMF increased the total chlorophyll content, N shoot and root content, P shoot and root content, and seed and stem fiber yield by 30.4%, 36.1%, 31.0%, 38.9%, 45.4%, 35.2%, and 26.9%, respectively. As a result of using AMF, flax plants grown under salt stress exhibited tolerance, suggesting that AMF could be applied in saline environments to maintain ecological stability. Full article

The urgent need to mitigate greenhouse gas (GHG) emissions has prompted the exploration of various strategies, including the adaptation of carbon farming practices, to achieve sustainability in agricultural systems. In this research, we assess the viability of carbon farming practices for organic vegetable growing in Europe. The study explores the potential benefits of these practices, including GHG emissions’ mitigation and improved soil health, biodiversity, and ecosystem services, while also acknowledging the need for further research to optimize implementation strategies and foster widespread adoption. However, the suitability and effectiveness of carbon farming practices in organic vegetable production systems remain uncertain. The analysis considers the measurement and estimation methods employed to assess changes in soil carbon stocks and the potential environmental and economic implications for farmers. Despite a substantial body of data demonstrating the sustainable attributes of carbon farming and its multifaceted advantages, a degree of hesitancy persists. Considering this, we propose undertaking a concise strengths, weaknesses, opportunities, and threats (SWOT) analysis to evaluate multiple aspects of carbon farming. The findings reveal that carbon farming practices can be viable and advantageous in organic vegetable production. Carbon farming practices, such as cover cropping, reduced tillage, compost application, and agroforestry, can significantly enhance the sustainability of organic farming systems. Implementing these practices can mitigate greenhouse gas emissions, improve soil health and fertility, and promote biodiversity conservation. Farmer education and support, policy measures, and continued research are crucial for maximizing the potential of these practices for a sustainable future. These practices also contribute to developing climate-friendly agricultural systems, promoting environmental resilience, and reducing the ecological footprint of organic vegetable production. However, further research is needed to optimize implementation strategies, address site-specific challenges, and foster widespread adoption of carbon farming practices in organic vegetable production. Full article

Rice has an important position in China as well as in the world. With the wide application of rice hybridization technology, the problem of mixing between individual varieties has become more and more prominent, so the variety identification of rice is important for the agricultural production, the phenotype collection, and the scientific breeding. Traditional identification methods are highly subjective and time-consuming. To address this issue, we propose a novel locality preserved selective projection learning (LPSPL) method for non-destructive rice variety identification based on leaf hyperspectral characteristics. The proposed LPSPL method can select the most discriminative spectral features from the leaf hyperspectral characteristics of rice, which is helpful to distinguish different rice varieties. In the experiments, support vector machine (SVM) is adopted to conduct the rice variety identification based on the selected spectral features. The experimental results show that the proposed method here achieves higher identification rates, 96% for the early rice and 98% for the late rice, respectively, which are superior to some state-of-the-art methods. Full article

Understanding genetic architectures of yield and yield-related traits of wheat (Triticum aestivum L.) grown under dryland or irrigated conditions is pivotal for developing modern high-yielding germplasm and cultivars. The objectives of this study were to detect quantitative trait loci (QTL) linked to yield and yield components using a mapping population derived from ‘TAM 113’/‘Gallagher’, including 191 recombinant inbred lines (RILs). The population was grown in McGregor, College Station, and Bushland, Texas, for three consecutive years from 2019 to 2021. A high-density genetic map covering all 21 chromosomes was constructed using a set of 8,075 single nucleotide polymorphisms (SNPs) obtained using genotyping-by-sequencing (GBS). A total of 147 QTLs for 16 yield-related traits were identified, which included 16 QTLs consistently detected in multiple experiments and 8 QTLs that showed pleiotropic effects. Of them, five pleiotropic QTLs overlapped with the consistent QTL. They increased grain yield (YLD) up to 37.64 g m⁻², thousand kernel weight (TKW) up to 1.33 g, harvest (HI) up to 0.97%, kernel length up to 0.08 mm, and kernel width up to 0.04 mm with Gallagher alleles and increased YLD up to 22.21 g m⁻², kernels spike⁻¹ up to 1.77, TKW up to 1.14 g, and HI up to 3.72% with TAM 113 alleles. One major and consistent QTL on chromosome 2D at 34.4 Mbp overlapped with the major photoperiod gene Ppd-D1 and was affected by multiple traits, including kernel diameter (DIAM), TKW, kernel hardness index (KHI), heading date (HD), and plant height (PH). Another QTL cluster region on 7D between 52 and 66 Mbp, encompassing one consistent and three pleiotropic QTLs. One of the pleiotropic QTLs at 52 Mbp increased YLD up to 24.16 g m⁻², HI up to 1%, and DIAM up to 0.03 mm. This study dissected genetic loci associated with yield and yield-related traits, providing valuable information on wheat improvement using marker-assisted selection (MAS). Full article

With the rapid development of China’s industrialization and urbanization, the problem of heavy metal pollution in soil has become increasingly prominent, seriously threatening the safety of the ecosystem and human health. The development of hyperspectral remote sensing technology provides the possibility to achieve the rapid and non-destructive monitoring of soil heavy metal contents. This study aimed to fully explore the potential of ground and satellite image spectra in estimating soil heavy metal contents. We chose Xushe Town, Yixing City, Jiangsu Province as the research area, collected soil samples from farmland over two different periods, and measured the contents of the heavy metals Cd and As in the laboratory. At the same time, under field conditions, we also measured the spectra of wheat leaves and obtained HuanJing-1A HyperSpectral Imager (HJ-1A HSI) satellite image data. We first performed various spectral transformation pre-processing techniques on the leaf and image spectral data. Then, we used genetic algorithm (GA) optimized partial least squares regression (PLSR) to establish an estimation model of the soil heavy metal Cd and As contents, while evaluating the accuracy of the model. Finally, we obtained the best ground and satellite remote sensing estimation models and drew spatial distribution maps of the soil Cd and As contents in the study area. The results showed the following: (1) spectral pre-processing techniques can highlight some hidden information in the spectra, including mathematical transformations such as differentiation; (2) in ground and satellite spectral modeling, the GA-PLSR model has higher accuracy than PLSR, and using a GA for spectral band selection can improve the model’s accuracy and stability; (3) wheat leaf spectra provide a good ability to estimate soil Cd (relative percent difference (RPD) = 2.72) and excellent ability to estimate soil As (RPD = 3.25); HJ-1A HSI image spectra only provide the possibility of distinguishing high and low values of soil Cd and As (RPD = 1.87, RPD = 1.91). Therefore, it is possible to indirectly estimate soil heavy metal Cd and As contents using wheat leaf hyperspectral data, and HJ-1A HSI image spectra can also identify areas of key pollution. Full article

Soybeans are the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) for soybean quality traits and mining related candidate genes are of great significance for the molecular breeding of soybean quality traits and understanding the genetic mechanism of protein/fat metabolism. In this study, the F₂ population was derived from the high-protein material Changjiang Chun 2 and Jiyu 166. On the basis of a genetic linkage map constructed in our previous study, the QTL of crude protein content, crude oil content and fatty acid fractions were detected using the multiple-QTL model (MQM) mapping method. The results show that a total of 92 QTL were obtained affecting quality traits under three environments, including 14 QTL of crude oil content, 9 QTL of crude protein content, and 20, 20, 11, 10 and 8 QTL for the content of palmitic, stearic, oleic, linoleic and linolenic acids, respectively. Sixteen QTL clusters were identified, among which Loci01.1, Loci06.1 and Loci11.1 were identified as stable QTL clusters with phenotypic contribution rates of 16.5%, 16.4% and 12.1%, respectively, and candidate genes were mined in their regions. A total of 32 candidate genes related to soybean quality were finally screened via GO enrichment and gene annotation. The present study lies the foundations for understanding the genetic mechanism and elite germplasm innovation of seed quality in soybean. Full article

Compared to the traditional production of ginseng roots, Panax ginseng sprouts (PGSs) are currently regarded as a substitute due to the relatively short-term culture but still high nutrition. However, the optimal light intensity for the growth ability of PGSs and the characterizations of the responses of PGSs to the light intensity have been largely neglected. This study aimed to determine the influences of the light intensity on the growth, morphogenesis, and photosynthetic responses in PGSs. To this end, two-year-old ginseng rootlets were subjected to one of six light intensities (from 30 to 280 PPFD with 50 PPFD intervals) in a plant factory with artificial lighting (PFAL) via LED light for 10 weeks. On the whole, the recorded parameters of the PGSs showed gradually decreasing trends in response to the increasing light intensities. However, the 80 PPFD-treated PGSs possessed similar or greater root dry weights, leaf areas, carotenoids levels, and photosynthesis (the maximal PSII quantum yield) compared to those in the 30 PPFD regime. Additionally, photoinhibition symptoms as evidenced by chlorosis, necrosis, and stunted growth were observed as the light intensity attained 180 PPFD. Thus, 130 PPFD could be considered a safe point for the appearance of photoinhibition in PGSs. Taken together, we show that the light intensity range of 30–80 PPFD is suitable for maximizing the production of PGSs in PFALs. Full article

To optimise sector design in drip irrigation systems, a two-stage procedure is presented and applied in a commercial vineyard plot. Soil apparent electrical conductivity (ECa) mapping and soil purposive sampling are the two stages on which the proposal is based. Briefly, ECa data to wet bulb depth provided by the VERIS 3100 soil sensor were mapped before planting using block ordinary kriging. Looking for simplicity and practicality, only two ECa classes were delineated from the ECa map (k-means algorithm) to delimit two potential soil classes within the plot with possible different properties in terms of potential soil water content and/or soil water regime. Contrasting the difference between ECa classes (through discriminant analysis of soil properties at different systematic sampling locations), irrigation sectors were then designed in size and shape to match the previous soil zoning. Taking advantage of the points used for soil sampling, two of these locations were finally selected as candidates to install moisture sensors according to the purposive soil sampling theory. As these two spatial points are expectedly the most representative of each soil class, moisture information in these areas can be taken as a basis for better decision-making for vineyard irrigation management. Full article

Minirhizotron tubes were installed to monitor root growth dynamics of mature Shiraz grapevines in a rootstock trial established in the hot climate Riverina region of New South Wales, Australia. The vertical root distribution and seasonal root growth dynamics of Shiraz on own-roots and Shiraz grafted on the rootstocks Ramsey, 140 Ruggeri and Schwarzmann was studied for five seasons across a seven-year period to a depth of 60 cm. New root production was significantly influenced by genotype, soil depth, season, growth stage and year. Soil moisture and soil temperature were monitored at 10, 30 and 60 cm in the last two seasons. Soil moisture at 30 cm and soil temperature at all three depths were significant predictors of root growth. New root numbers were significantly higher in 140 Ruggeri than the other rootstocks. To the depth studied, 140 Ruggeri roots were evenly distributed from the topsoil down, whereas the majority of roots of Schwarzmann and Shiraz were located at intermediate depths in the 10–40 cm ad 20–40 cm zones respectively, while Ramsey roots were found at 20 cm or below. Depending on genotype, root growth occurred across several phenological stages but tended to peak at flowering. In some years we observed root growth in early and late winter at rates exceeding that of autumn, and this was associated with warmer temperatures during this period. In general, the seasonal dynamics of root growth attributes were found to be influenced by abiotic factors, but mainly determined by genotype. The insights gained from this study can help us better understand the interplay between rootstock, environment, and management, and predict how different rootstock genotypes may perform under changing climatic conditions. Full article

This work was aimed at the characterization of residual generated biomass from pruned tree species present in the Andean areas of Ecuador as a source of energy, both in plantations and in urban areas, as a response to the change in the energy matrix proposed by the Ecuadorian government. From the proximate analysis (volatiles, ashes, and fixed carbon content), elemental analysis (C, H, N, S, O, and Cl), structural analysis (cellulose, lignin, and hemicellulose content), and higher heating value, the studied species were pine (Pinus radiata), cypress (Cupressus macrocarpa), eucalyptus (Eucalyptus globulus), poplar (Populus sp.), arupo (Chionanthus pubescens), alder (Alnus Acuminata), caper spurge (Euphorbia laurifolia), and lime (Sambucus nigra L.) trees. We evaluated the influence of the presence of leaves in the biomass. From this characterization, we developed a method based on obtaining the main components for the identification of the biomass’s species. If the origin of the biomass was unknown, this method enabled us to identify the species, with all its characteristics. If the origin of the biomass was unknown, this innovative method enabled the identification of the species from the lignocellulosic biomass, with all of its characteristics. Finally, we developed regression models that relate the higher heating value to the elemental, proximate, and structural composition. Full article

Organic wheat production systems have lower yields compared with intensive conventional production and often do not achieve the grain protein content and quality thresholds set by millers and bakers. In contrast, organic production methods were reported to result in higher concentrations of nutritionally desirable micronutrients and lower concentrations of the toxic metal Cd in wheat grain and wholegrain flour. However, although N-availability and variety characteristics are known to affect both gain yields and bread-making quality, the exact reasons for the yield gap and differences in grain processing and nutritional quality between organic and conventional spring wheat production in the UK are poorly understood. The overall aim of this study was therefore to determine to what extent changes in variety choice and fertilization regimes may reduce the yield gap and improve processing quality without affecting nutritional quality in organic spring wheat production. To achieve this aim, we compared crop health, yield, grain processing, and nutritional quality parameters in spring wheat produced using (i) six contrasting spring wheat varieties grown with a standard fertilization regime and (ii) one variety widely used by organic farmers (Paragon) with nine different fertilization regimes in (iii) three UK sites/farms with contrasting pedoclimatic conditions. Significant differences in foliar disease severity, grain yield, and quality parameters were detected between six contrasting spring wheat varieties when grown under organic management regimes. Specifically, the varieties Paragon and Tybalt were identified as the best-performing varieties with respect to foliar disease resistance and grain yield under organic farming conditions and also produced high processing and nutritional quality across the three UK sites. However, the highest grain yields were obtained by Paragon at the Gilchester site and Tybalt at the Sheepdrove and Courtyard sites, while the highest protein contents were produced by Tybalt at the Gilchester site and Paragon at the Sheepdrove and Courtyard sites, which suggests that there is a need for site-specific wheat variety selection in the UK organic sector. Although organic fertilizer input type and level also affected wheat performance, differences between fertilization regimes were smaller than those observed between the five contrasting varieties, which suggests that improvements in spring wheat breeding/selection have a greater potential for increasing crop yield and quality in the organic sector compared with changes to fertilization practices. Overall, results suggest it is feasible to breed/select spring wheat varieties that combine high protein, vitamin E, and micronutrients with low toxic metal (Cd, Pb) concentrations when produced under organic farming conditions. These findings also support the hypothesis that differences in variety choice by organic and conventional farmers have contributed to the differences in nutritional quality between organic and conventional wheat products reported in previous studies. Full article

Irrigated agriculture is facing a serious problem of water scarcity, which could be mitigated by optimizing the application of regulated deficit irrigation (RDI) strategies. For this reason, the aim of our study was to determine irrigation thresholds based on direct water status indicators of apricot trees under RDI to maximize water productivity. Three treatments were tested: (i) Control (CTL), irrigated at 100% of the crop evapotranspiration (ET_c) during the entire crop cycle; (ii) RDI₁, irrigated as CTL, except during fruit growth stages I–II when irrigation was reduced by 20% of CTL, and during late post-harvest, with an irrigation threshold of a moderate water stress of −1.5 MPa of stem water potential (Ψ_s); and (iii) RDI₂, irrigated as RDI₁, but during late post-harvest using a severe water stress threshold of −2.0 MPa of Ψ_s. As the irrigation scheduling of RDI₁ and RDI₂ did not affect yield and fruit quality, the crop water productivity was increased by 13.2 and 25.6%, respectively. This corresponded to 1124 and 2133 m³ ha⁻¹ of water saved for RDI₁ and RDI₂. A water stress integral of 30.2 MPa day during post-harvest could be considered optimal since when 41 MPa day was accumulated, vegetative growth was reduced by 35%. The non-sensitive periods to water deficit were delimited by the accumulation of growing degree days (GDD) from full bloom, the end of fruit growth stages I–II corresponded to an accumulation of 640 °C GDD, and the beginning of the late post-harvest to an accumulation of 1840 °C GDD. Full article

Recognition and localization of fruits are key components to achieve automated fruit picking. However, current neural-network-based fruit recognition algorithms have disadvantages such as high complexity. Traditional stereo matching algorithms also have low accuracy. To solve these problems, this study targeting greenhouse tomatoes proposed an algorithm framework based on YOLO-TomatoSeg, a lightweight tomato instance segmentation model improved from YOLOv5n-seg, and an accurate tomato localization approach using RAFT-Stereo disparity estimation and least squares point cloud fitting. First, binocular tomato images were captured using a binocular camera system. The left image was processed by YOLO-TomatoSeg to segment tomato instances and generate masks. Concurrently, RAFT-Stereo estimated image disparity for computing the original depth point cloud. Then, the point cloud was clipped by tomato masks to isolate tomato point clouds, which were further preprocessed. Finally, a least squares sphere fitting method estimated the 3D centroid co-ordinates and radii of tomatoes by fitting the tomato point clouds to spherical models. The experimental results showed that, in the tomato instance segmentation stage, the YOLO-TomatoSeg model replaced the Backbone network of YOLOv5n-seg with the building blocks of ShuffleNetV2 and incorporated an SE attention module, which reduced model complexity while improving model segmentation accuracy. Ultimately, the YOLO-TomatoSeg model achieved an AP of 99.01% with a size of only 2.52 MB, significantly outperforming mainstream instance segmentation models such as Mask R-CNN (98.30% AP) and YOLACT (96.49% AP). The model size was reduced by 68.3% compared to the original YOLOv5n-seg model. In the tomato localization stage, at the range of 280 mm to 480 mm, the average error of the tomato centroid localization was affected by occlusion and sunlight conditions. The maximum average localization error was ±5.0 mm, meeting the localization accuracy requirements of the tomato-picking robots. This study developed a lightweight tomato instance segmentation model and achieved accurate localization of tomato, which can facilitate research, development, and application of fruit-picking robots. Full article

Two experiments were conducted to investigate the chemical and fermentative characteristics of by-product-mixed silages consisting of wheat straw (WS), grape pomace (GP), olive mill wastewater (OMWW) and cheese whey (CW) at 7, 30 and 90 days. The silage formulations were based on a ratio of 60% solids (WS + GP) and 40% liquids (CW + OMWW), with the addition of water (W) where necessary to achieve 40% of liquids. In experiment 1, the effects of the inclusion of GP or CW in a mixture of WS and OMWW were studied according to two silage formulations: SIL-A, WS40% + OMWW5% + GP20% + W35%; SIL-B, WS60% + OMWW5% + CW35%. In experiment 2, the effects of two levels of CW and the inclusion of OMWW in mixed silages based on WS, GP, and CW were studied according to four silage formulations: SIL-C, WS40% + GP20% + CW20% + W20%; SIL-D, WS40% + GP20% + CW20% + OMWW5% + W15%; SIL-E, WS40% + GP20% + CW35% + W5%; SIL-F, WS40% + GP20% + CW35% + OMWW5%. In experiment 1, the silage formulation affected the chemical composition showing a greater (p < 0.05) content of DM in SIL-B; crude protein, ether extract and ADL contents were higher (p < 0.05) in SIL-A. In experiment 2, no differences (p > 0.05) in the chemical characteristics of the silages were found. In both of the experiments, the chemical composition and total phenol content did not change (p > 0.05) during the ensiling period. Fermentative characteristics were not affected (p > 0.05) by the by-product combination nor the ensiling period and proved to be adequate for good-quality silages. The Flieg’s scores at D30 and D90 were greater than a 100 score in all the experimental silages, leading to the conclusion that WS, GP, OMWW and CW can be effective for producing silage. Full article