Row Planting Research Articles

Automation in Agriculture: A Robotic Approach to Weed Control for Greenhouse Cucumber Cultivation

The increasing global population has heightened the demand for efficient food production, leading to the adoption of compact cultivation methods such as greenhouses. However, weed growth within these controlled environments significantly challenges crop productivity. The application of robots can be a useful and economic choice. This study presents an innovative, purely mechanical system for weed control in greenhouses, specifically designed to operate autonomously on a monorail. The machine stops in the distance between the two main plant rows (cucumber) and its arm goes into the gap to deploy the weeds by rotating its blades. This is continued repeatedly. The cutting is by the rotational speed of the blade. Variable-speed motions of the blade were at 3500, 2500 and 1500 rpm for 3 types of moulinex, triangular, and circular blades. The movement speed of the arm was 10 and 30 rpm and the forward movement speed of the machine was 30, 40, 50, 60, 80 and 120 rpm. The results showed that different blades, blade speeds and engine speed affect significantly (p <0.05) the percentage of weeds being cut. Although the interactions of these factors have no significant effect on percentage; the average percentages by the blades have significant differences. Although the interactions between these factors were not statistically significant, the comparison of means revealed that at lower blade speeds, the blade type had a pronounced effect on weed-cutting efficiency. As blade speed increased, differences in blade performance diminished. The most effective combination was achieved using Moulinex blades at 3500 rpm with a 10-rpm arm speed, resulting in the highest percentage of weeds cut. These findings suggest that optimizing blade type and speed can significantly enhance the mechanical weed control efficiency in greenhouse environments.

Effect of Land Configuration and Rainfall on Pennisetum glaucum (L.) R. Br. under Saline Irrigation

Field experiment was conducted in Eastern Block Farm of Tamil Nadu Agricultural University, Coimbatore to evaluate the effect of land configuration and rainfall on growth and yield of pearl millet under saline water irrigation in summer, 2024. The study was carried out in split plot design with three main plots (flatbed (M1), ridges and furrows (M2) and raised bed paired row planting (M3)) along with four subplot treatments (direct sowing (S1), 10 Day Old Seedlings (DOS) (S2), 15 DOS (modified dapog) (S3) and 20 DOS (S4)) which was replicated thrice. Water availability is a critical factor in influencing the length of the growing period while water quality significantly influences crop growth and yield. Consequently, rainfall received during the growing period affects plant height, Leaf Area Index (LAI), effective tillers and yield. The cumulative rainfall received 208 mm in 22 days and with 10 rainy days during the crop growth period. Rainfall between 40 to 60 Days After Sowing/Planting (DAS/P) corresponded with Crop Growth Rate (CGR). Among main plot treatments, ridges and furrows (M2) recorded higher plant height (173 cm) and effective tillers (2.6) at harvest. Grain and stover yields (t ha-1) were also higher in ridges and furrows (M2) (3.31 and 6.12, respectively) which was statistically on par with raised bed paired row planting (M3) (3.31 and 6.12, respectively).

Intercropping grapevine with rosemary: A promising alternative to conventional agriculture in the current frame of global change

The Mediterranean region is well known for its long history of viticulture and the use of herbs and spices in its cuisine. Given the increasing focus on intercropping as a sustainable agricultural approach to maximize land use efficiency or improve soil fertility amid global change, we conducted a study to assess the feasibility of intercropping grapevine (Vitis vinifera L. cv. Merlot) with rosemary (Salvia rosmarinus Spenn.) in a Mediterranean vineyard. The trial was established in a 22-year-old vineyard, where rows of rosemary plants were cultivated between grapevine rows one year prior to the evaluation. To test intercropping feasibility and the abiotic stress effects on the harvest of rosemary, two sampling dates were set to monitor grape maturation (veraison and harvest) and rosemary quality in terms of antioxidant contents and composition, so that both crops were simultaneously analyzed under typical Mediterranean conditions, using both physiological and quality parameters. Results showed that intercropping with young rosemary plants did not affect grapevine physiology state, and observed differences in the two samplings were due to environmental stress only, indicating a positive coexistence between these crops in the context of global change. Regarding grape quality, variations in total soluble sugars, titratable acidity, and phenolic compounds were influenced by ripening during the summer, but not by intercropping, thus maintaining fruit quality. Rosemary contained high levels of antioxidants and exhibited strong antioxidant activity, particularly during mid-August (coinciding with vintage), indicating its potential as a valuable source of natural antioxidants for dietary intake, including phenolic diterpenes, vitamin C, and vitamin E. In conclusion, intercropping grapevines with rosemary did not negatively impact plant physiological performance or grape quality, promoting the production of two high-quality products with significant added value in the food sector under current stressful Mediterranean climatic conditions.

Determining the influence of structural and technological parameters of strip tillage on sunflower vegetation

The object of this study is the process of strip tillage, its effect on soil moisture in the strip, and subsequent vegetation of sunflower plants. At the same time, the task to increase the efficiency of strip tillage was solved. It has been established that the rational values of the structural and technological parameters of the strip tillage section in terms of fuel consumption depend on the speed of movement of the unit, the depth and width of the tilled strip of soil. One section of the unit was used for the research. The studies were conducted using the Box-Benkin three-factor experiment design. It was established that the rational values of the structural and technological parameters of strip tillage in terms of fuel consumption have the following values: the depth of strip tillage h=20‒25 cm, the width of strip tillage b=20‒25 cm, the speed of the unit from 7.5 to 11 km/hours. In this case, the actual fuel consumption ranged from 4.2 to 6.3 l/ha. It was also established that an increase in the width and depth of the strip cultivation leads to an increase in moisture loss in it. The highest value of soil moisture occurs at the minimum values of the depth and width of the strip cultivation, and the lowest at their maximum values. The influence of the width of the cultivated strip on the height of sunflower plants is more significant than the influence of the depth of tillage. This applies both to the range of changes in the height of sunflower plants (12.4‒13.6 cm compared to 12.5‒13.1 cm) and the intensity of the impact. The greatest influence on the height of sunflower plants is exerted by the magnitude of the transverse displacement of the axis of the row of plants. The intensity of this influence is approximately the same as the depth of tillage, and the range of changes in the height of sunflower plants is 11.7‒14 cm. Research results could be used in the design of units for strip tillage and sowing units.

Design and Test of Potato Seedling Killing and Residual Film Recycling Integrated Machine

Plastic film mulching technology can effectively enhance crop yield and quality, and the use of mulch has been increasing in recent years; however, the problem of mulch residue is worsening due to the large amount of recycling work and slow natural degradation. In this study, a potato seedling killing and residual film recycling machine is designed to provide good working conditions for potato harvesters before harvesting in response to the problems of difficult separation of film tangles, the low net rate of recycling due to the mixing of residual film with soil, and the high soil content in residual film recycling operations in northwest China. The machine is based on the potato monoculture and double row planting mode in Gansu area. This paper puts forward the overall design scheme and carries out the theoretical analysis and parameter determination of the key components, such as the seedling killing device, the film surface cleaning device, the film unloading device, and so on. Using EDEM software to carry out the virtual simulation test and Design-Expert13 to analyze the test results, we determined the optimal working scheme for the machine, with a forward speed of 0.8 m/s, a film gap of 125 mm, and a spiral stirrer speed of 600 r/min. Based on a field test for verification, the test results show that the machine’s residual film recovery rate was 83.3%, the impurity rate was 3.8%, and the rate of injury to the potatoes was 1.4%. The machine meets the requirements of national and industry standards, and it can simultaneously realize straw crushing, film surface cleaning, residual film recycling, and hydraulic film unloading operations, with better operating results and while reaching the expected results. It can also provide a reference for the design and testing of a seeding and residual film recycling machine.

Driveway Detection for Weed Management in Cassava Plantation Fields in Thailand Using Ground Imagery Datasets and Deep Learning Models

Weeds reduce cassava root yields and infest furrow areas quickly. The use of mechanical weeders has been introduced in Thailand; however, manually aligning the weeders with each planting row and at headland turns is still challenging. It is critical to clear weeds on furrow slopes and driveways via mechanical weeders. Automation can support this difficult work for weed management via driveway detection. In this context, deep learning algorithms have the potential to train models to detect driveways through furrow image segmentation. Therefore, the purpose of this research was to develop an image segmentation model for automated weed control operations in cassava plantation fields. To achieve this, image datasets were obtained from various fields to aid weed detection models in automated weed management. Three models—Mask R-CNN, YOLACT, and YOLOv8n-seg—were used to construct the image segmentation model, and they were evaluated according to their precision, recall, and FPS. The results show that YOLOv8n-seg achieved the highest accuracy and FPS (114.94 FPS); however, it experienced issues with frame segmentation during video testing. In contrast, YOLACT had no segmentation issues in the video tests (23.45 FPS), indicating its potential for driveway segmentation in cassava plantations. In summary, image segmentation for detecting driveways can improve weed management in cassava fields, and the further automation of low-cost mechanical weeders in tropical climates can be performed based on the YOLACT algorithm.

Optimizing daylily (Hemerocallis citrina Baroni) cultivation: integrating physiological modeling and planting patterns for enhanced yield and resource efficiency

IntroductionOptimizing the dynamics of daylily (Hemerocallis citrina Baroni) growth under various planting patterns is critical for enhancing production efficiency. This study presents a comprehensive model to simulate daylily growth and optimize planting patterns to maximize bud yield while minimizing land resource utilization.MethodsThe model incorporates source-sink relationship specific to daylilies into physiological process modeling, considering environmental factors such as micro-light and temperature climate, and CO2 concentration. Spatial factors, including planting pattern, row spacing, plant spacing, and plant density were examined for their impact on light interception, photosynthesis, and resource efficiency. Employing partial least square path modeling (PLS-PM), we analyzed the interrelations and causal relationships between planting configurations and physiological traits of daylily canopy leaves and buds. Through in situ simulations of 36 planting scenarios, we identified an optimal configuration (Scenario ID5) with a density of 83,000 plants·ha−1, row spacing of 0.8 m, and equidistant planting with a plant spacing of 0.15 m.Results and discussionOur research findings indicate that increased Wide+Narrow row spacing can enhance yield to a certain extent. Although planting patterns influence daylily yield, their overall impact is relatively minor, and there is no clear pattern regarding the impact of plant spacing on individual plant yield. This modeling approach provides valuable insights into daylily plant growth dynamics and planting patterns optimization, offering practical guidance for both farmers and policymakers to enhance daylily productivity while minimizing land use.

Effect of irrigation levels, crop geometry and mulching on yield, economics and water use efficiency of fennel (Foeniculum vulgare Mill.) grown under drip system in Western Rajasthan, India

A study was carried out at Swami Keshwanand Rajasthan Agricultural University, Bikaner, Rajasthan, during the rabi seasons of 2015–16 and 2016–17 to investigate the effects of irrigation levels, crop geometry, and mulch on yield parameters, yield, economics, and water use efficiency of fennel (Foeniculum vulgare Mill.). Findings showed that the irrigation level of 0.8 ETc considerably increased the yield parameters of fennel, including seed (1684 kg ha-1) and stover yield (3110 kg ha-1), net return (103149 ha-1) and benefit: cost ratio (2.58). At 0.6 ETc, a maximum water use efficiency of 5.48 kg ha-1 mm-1 was observed. 40 cm x 60 cm paired row planting produced significantly superior yield parameters, seed yield, and water use efficiency. Results further revealed that the application of plastic mulch considerably improved yield parameters, yield, net return, and benefit: cost ratio as compared to no mulch treatment. However, test weight and harvest index were not influenced by plastic mulch. Thus, in arid and semi-arid parts of Rajasthan, integrated use of drip irrigation at 0.8 ETc and plastic mulch under paired row sowing of 40 cm x 60 cm proved more viable for ensuring higher productivity of rabi fennel.

Effect of Tillage, Crops Residues and Crops Management Practices on Runoff Erosion, Soil Loss and Soil Properties in Ethiopa: Review

The conducted investigations showed that tillage practices with crop residue and proper cropping systems protect loss of soil from runoff erosion which depletes soil nutrients and affects soil physical and chemical properties. The review was conducted with aim of reviewing the effect of tillage, crops residues and crops management practices on runoff, soil loss and soil properties in Ethiopia. The three years study conducted in the Upper Blue Nile basin of Northwestern Ethiopia showed that reduced tillage reduced soil loss over conventional tillage, row planting reduced soil loss over broadcast planting, without trampling reduced soil loss over with trampling planting, and the sediment concentration was ranged from 0.01 to 5.37g/L and total soil loss was 0.20 to 0.50t/ha. The study conducted in the humid highlands of Ethiopia showed that the lower average soil loss was 16 t/ha.yr under zero tillage with crop residue and maximum was 30 t/ha.yr in conventional tillage without crop residue. The investigation indicated that zero tillage with maize soya bean intercrop, maize rotation, continuous maize and continuous soya bean improved soil properties than conventional tillage system. The investigation which was carried out to evaluate the effects of tillage and cropping system on soil properties showed that enrichment ratio ≤1 under no tillage with intercropping and no tillage with mulch reduce nutrient losses and enrichment ratio. The study conducted at Derashe and Arba Minch Zuriya in Ethiopia showed that some selected properties were statistically significant (P<0.05) and conservation tillage is favored for soil management relative to conventional tillage. Therefore, tillage practices like zero tillage and minimum tillage with crop residue management like mulching and crop management such as intercropping and crop rotation reduce surface runoff erosion, soil loss and soil fertility depletion, but additional continual research is needed to reveal trends in tillage, crops residues and crops management.

Effects of intercropping with Fenlong tillage “145” mode on ratoon sugarcane photosynthesis, growth, and yield

AbstractSoil compaction and resource competition are bottlenecks in the improvement of sugarcane productivity in intercropping systems. Fenlong tillage improves crop yields by alleviating soil compaction and ensuring water supply. Wide‐narrow rows are an effective solution for light competition. An efficient intercropping system with Fenlong tillage technology as the core needs to be constructed. A two‐cycle field study was conducted to investigate the effects of planting methods [sole ratoon sugarcane (S) and ratoon sugarcane‐soybean intercropping (I)] combined with tillage [conventional rotary tillage (RT), Fenlong tillage “145” mode (FL145)] on soil physical characteristics, photosynthesis, and growth of ratoon sugarcane, as well as crop yields. For the ratoon sugarcane, compared to RT‐I, FL145‐I decreased bulk density and increased porosity in the 0–40 cm soil layer. Root growth parameters were improved under FL145‐I in the 0–20 cm soil layer. FL145‐I positively affected the stomatal conductance, causing increases in the net photosynthetic and transpiration rates. The increased leaf area index, chlorophyll relative content, and photosynthesis under FL145‐I caused higher dry matter accumulation. The increased single stalk weight under FL145‐I resulted in 17.13%–22.55% higher stalk yield with similar quality. Intercropping under the wide‐narrow row planting pattern had no negative effects on the growth and stalk yield of ratoon sugarcane. For the soybean, compared to RT‐I, the increased 100‐seed weight under FL145‐I resulted in 11.14% higher seed yield with similar quality. Therefore, FL145‐I presents a promising and novel management practice for sustainably increasing ratoon sugarcane productivity in China.

Tuber pathogenicity of Macrophomina phaseolina strain 3a isolated from rotten cassava tuber from farm lands in Osogbo, Osun State, Nigeria, its virulence genes and ADMET properties.

Macrophomina phaseolina is a pathogen that causes an opportunistic disease that spreads by soil and seeds and affects more than 500 different plant species, like fruits, trees, and row crops. Mycotoxins, such as phaseolinic acid, and phaseolinone, are produced by M. phaseolina isolates in previous investigations; however, the production of these mycotoxins seems to vary depending on the host and the region. In this study, Macrophomina phaseolina strain 3A was isolated from rotten cassava tuber and identified using the analysis of the sequences of the internal transcribed spacer region. The isolate was inoculated on a fresh healthy cassava tuber at 25°C and tuber-rotting potential was monitored for 4 weeks. Virulence genes MPH_06603, MPH_06955, and MPH_01521 were determined with designed primers, and secondary metabolites were characterized by FTIR and GCMS. The rotten tuber effect was observed from the 2nd week of the experiment with severe tuber rot and weight reduction. The PCR showed the presence of MPH_06603 virulence gene. The GCMS showed N-Methylpivalamide (115.0m/z), Butane, 1,4-dimethoxy- (119.0m/z), and 5-Hydroxymethylfurfural (126.0m/z) were the predominant metabolites produced by the pathogen. The compounds in the metabolites inhibit CYP3A4 enzymes, cause eye irritation, and Human Ether-a-go-go-related gene inhibition. This study revealed that M. phaseolina was responsible for the cassava tuber rot which leads to a lower yield of farm produce. The metabolites produced are toxic and unsafe for human consumption. It is suggested that farmers should destroy any cassava affected by this pathogen to prevent its toxic effects on humans and animals.

Spontaneous vegetation recovery in recently abandoned avocado (Persea americana Mill.) orchards in semi‐arid Central Chile

AbstractAvocado (Persea americana Mill.) is an important commodity with substantial global growth in semi‐arid regions under irrigation, such as Central Chile. This region of Chile has faced severe drought that has resulted in the abandonment of avocado orchards, previously established in a global biodiversity hotspot. This study investigates the early effects of abandonment of avocado farms on vegetation recovery and soil after severe droughts. We measured and characterized early plant successional processes by identifying the flora, vegetation coverage, similarity, and soil characterization through 42 transects distributed in four recently abandoned sites, a productive farm, and a natural site. Multivariate analysis was used to identify significant relationships between soil and habitat properties and vegetation abundance and coverage variations for the dominant species. The Jaccard similarity coefficient was used to compare sites. The establishment of native or endemic species was extremely limited and variable between sites. In total, we recorded 55 vascular plants (49.1% were native). The results indicated that Schinus molle L. has become a dominant colonizer, particularly in highly disturbed planting rows in abandoned farms. Factors such as the sources of S. molle propagules, soil salinity, and organic matter accumulation were identified as key predictors of its coverage and presence in abandoned farms. The study concludes that the abandonment of avocado farms, coupled with severe drought, has created favorable conditions for the recruitment of this species, adversely impacting other native species. This research underscores the importance of considering the remaining features of soil and habitat in new successional processes in highly disturbed areas.

Root Influences Rhizosphere Hydraulic Properties through Soil Organic Carbon and Microbial Activity.

Processes of water retention and movement and the hydraulic conductivity are altered in the rhizosphere. The aim of this study was to investigate the physical-hydric properties of soil aggregates in the rhizosphere of annual ryegrass (Lolium multiflorum) cropped in a Kandiudalfic Eutrudox, taking into account aspects related to soil aggregate stability. Soil aggregates from rhizosphere soil (RZS) and soil between plant rows (SBP) were used to determine soil water retention curves (SWRCs) and saturated hydraulic conductivity (Ksat). In addition, properties related to soil aggregate stability, such as water-dispersible clay, soil organic carbon (SOC), and microbial activity, were also assessed. The higher microbial activity observed in the RZS was facilitated by increased SOC and microbial activity, resulting in improved soil aggregation (less water-dispersible clay). For nearly all measured matric potentials, RZS had a higher water content than SBP. This was attributed to the stability of aggregates, increase in SOC content, and the root exudates, which improved soil water retention. The increase in total porosity in RZS was associated with improved soil aggregation, which prevents deterioration of the soil pore space and results in higher Ksat and hydraulic conductivity as a function of the effective relative saturation in RZS compared to SBP.

Application of Mycorrhiza-Biofertilizer to Increase Yield of Several Varieties of Soybean Intercropped Between Maize Double Rows of Different Row Spacings

This research aimed to examine the effects of application of mycorrhiza biofertilizer on yield performance of several varieties of soybean relay-planted between double rows of maize plants grown under different planting distances between rows. The experiment was arranged according to Split Split Plot Design, with three treatment factors, i.e. mycorrhiza biofertilizer (M0= without; M1= with mycorrhiza biofertilizer) as the main plots, soybean varieties (V1= Detap, V2: Biosoy-2, V3= Dena-1) as the subplots, and planting distances between double rows of maize in which two rows of soybean were grown (D1= 80; D2= 90; D3= 100 cm) as the sub-subplots. The results indicated that among those treatment factors, different varieties resulted in significant differences on all measurement variables, while increasing planting distances between maize double rows also significantly increased yield components of soybean, including branch number, pod number, and grain yield per clump, as well as weight of 100 grains, whereas application of mycorrhiza biofertilizer to the soybean plants only significantly increased branch number, pod number, and grain yield per clump. However, mycorrhiza biofertilizer showed interaction effect on most variables, especially in interaction with varieties and double row distances. Based on the patterns of mycorrhiza-varieties interaction, application of mycorrhiza biofertilizer significantly increased pod number (28%) on V1 showing the highest pod number on M1V1 treatment (87.87 pod/clump), while grain yield was highest on M1V3 (26.54 g/clump) and lowest (17.19 g/clump) on M0V1 treatment. The intercropping/monocropping yield ratio was also increased by application of mycorrhiza biofertilizer (from 69.33 to 88.18%) on V2.

Effect of adoption of conservation agriculture on household food security of smallholder maize farmers in Ghana

This cross-sectional study set out to examine the effect of conservation agriculture (CA) adoption on the food security of smallholder maize farmers in the Adansi Akrofuom District in the Ashanti Region of Ghana. Using the multistage sampling technique, 400 small-scale farmers who have been introduced to CA were selected. The findings of the study show that crop rotation, row planting, fertilizer application, improved seeds and cover cropping were the CA practices often implemented by the farmers. Age of the farmer, household size, years of education, religion, access to extension, frequency of group visits, and the area under CA cultivation were significant predictors of farmers' adoption of CA practices. Implementation of CA practices has a significant effect on household level of food security. There was an agreement among the farmers that access to credit is the greatest challenge they face in using CA practices. The paper proposes that efforts towards the continuous and high adoption of CA practices must be given more attention since they can affect farmers’ household food security.

Determinants of the adoption of climate smart agriculture practices by smallholder wheat farmers in northwestern Ethiopia

Frequent climate variability and change had the strongest direct influences on the availability and accessibility of food through reducing agricultural productivity and cropping patterns. Despite the Ethiopian government having made substantial efforts to boost production and productivity through the introduction of Climate Smart Agriculture Practices (CSAPs), the implementation of these practices by smallholder wheat farmers has remained low. This study, therefore, tried to investigate the determinants of the adoption of CSAPs in Northwestern Ethiopia. The primary data were gathered from 385 randomly selected wheat producers (including 702 plot-level observations). The CSAPs considered in this investigation were wheat row planting, crop rotation, and improved wheat varieties. The factors that influence the adoption of CSAPs were determined using a multivariate probit (MVP) model. The results revealed that the age of the sampled wheat producer farmers, education level of sampled wheat farmers, livestock holding, contact with development agents, credit access, off-farm activities participation, distance to input supply institution, slope of the plot, and soil fertility status of the plot were the major determinants of the adoption of CSAPs. The study suggested that policy-makers and stakeholders should strengthen farmers’ skills by providing sufficient and effective short-term training. Moreover, encouraging mixed crop-livestock production systems, strengthening credit access, development agents, and access to near-input supply institutions are required to scale-up the adoption of CSAPs.

Restoring a dry tropical forest through assisted natural regeneration: enhancing tree diversity, structure, and carbon stock

Deforestation is a key factor in global climate change, severely impacting ecosystem services. Effective implementation of reducing emissions from deforestation and forest degradation (REDD+) initiatives is essential for mitigating this change. Reforestation is a sustainable way to mitigate deforestation effects. We studied the impact of assisted natural regeneration (ANR) on restoring dry forest land, increasing biodiversity, structure, and carbon stock. Reforestation units were established at a multiple row planting system in a dry tropic region. We selected 63 plots, each 20 m × 20 m, categorized into multiple row–mixed plantation (MRMP) and multiple row–unmixed plantation (MRUP). We measured tree height and diameter at breast height (DBH) and evaluated biodiversity indices, including the Shannon–Weiner Index (SWI), species richness, evenness, and Important Value Index (IVI). Carbon stock was estimated using allometric equations. We identified 931 individual trees representing 27 species, 24 genera, and 14 families. MRMP showed significantly higher biodiversity, species richness, and evenness than MRUP. Terminalia arjuna was the most dominant species (IVI=124.45), followed by Khaya senegalensis (53.84). Survival rates exceeded 90 % for T. arjuna, K. senegalensis, Madhuca longifolia, and Pongamia pinnata (p<0.001). No significant differences were observed in tree DBH, tree height, tree density, basal area, and carbon stock among the plantation categories. The species Albizia saman exhibited a high diameter increment rate (4.07 ± 1.55 cm/year), followed by K. senegalensis (3.83 ± 0.43 cm/year). A mean value of 5.63 ± 1.13 MgC/ha of carbon stock was stored, while 20.66 ± 4.13 Mg/ha of atmospheric CO2 was sequestered. The results highlight that promoting mixed tree species in multiple rows to enhance biodiversity and optimize carbon regulation. This technique should be popularized to restore the dry forest landscape across the region.

The Impact of Planting Technology on the Maize Yield

The three–year trials of the impact of the planting technology on the maize yield were carried out at the trial sites Jakšić and Tenja. The KWS Intelligens and KWS Kollegas hybrids were used in the research, planted at a standard row spacing of 70 cm, and in the twin rows with a spacing of 48 × 22 cm. In 2020, the highest average grain yield at the site Jakšić in standard planting, with the KWS Intelligens hybrid, was 12.064 t ha–1, and in the twin row planting an increase in yield of +4.17% was recorded. The KWS Kollegas hybrid had the highest difference in grain yield between a standard and twin row planting in 2021 of +7.52%, in favor of the twin row. At the site Tenja, slightly higher grain yields were recorded in all three years of research. The major difference in yield was recorded in 2020 with the hybrid KWS Kollegas, of +8.22%, or 1.115 t more grain, when planting in the twin rows in comparison with a standard planting. The statistical tests indicate that planting in the twin rows at both trial sites obtained statistically significant results in all three years of research concerning the grain yield ha–1, grain weight per ear, and grain moisture content.

Soil respiration response to reductions in maize plant density and increased row spacing (Southeast pampas, Argentina)

Previous studies have recognized the influence of crop cover and agricultural management on variables (soil temperature, soil moisture, and root biomass) that influence soil respiration. However, despite the influence of plant density and row spacing on these variables in the maize crop (Zea mays L.), their impact on soil respiration has received little attention. Thus, the aims of this study were (i) to investigate whether reducing plant density and row spacing influences soil respiration, and (ii) to identify the controlling variables (soil temperature and soil moisture) underlying this response. We conducted field experiments in Balcarce, Argentina, over two seasons. Treatments included (i) maize crops at high plant density (≈8 plants m−2) and narrow rows (0.52 cm, HDN), and (ii) maize crops at low plant density (≈6.5 plants m−2) and wide row spacing (0.70 cm; LDW). Leaf area index (LAI), soil CO2 fluxes, soil superficial temperature, and moisture (characterized by the water-filled pore space, WFPS) were assessed throughout the growing season. Grain yield and cumulative soil CO2 emissions were determined at the final harvest. Major findings relevant to understanding the influence of reducing plant density and wider row spacing on instant CO2 fluxes include: (i) LAI reductions were related to higher superficial soil moisture, which was consistent at LAI ≥ 3; suggesting higher decreases in water uptake than increases in soil evaporation, and in turn (ii) increments in soil moisture were associated with higher CO2 fluxes. While lower plant density and wider row spacing had notable short-term effects on WFPS and soil respiration fluxes, they did not significantly affect cumulative soil respiration throughout the growing season. However, the combination of this practice with low-yield potential genotypes that exhibit low stability to changes in resource availability can increase CO2 emissions per unit of grain yield. These findings contribute to a better understanding of the impacts of management practices on soil respiration and, consequently, on carbon cycling within agricultural ecosystems.

Fruit fast tracking and recognition of apple picking robot based on improved YOLOv5

AbstractThe article proposes a real‐time apple picking method based on an improved YOLOv5. This method accurately recognizes different apple targets on fruit trees for robots and helps them adjust their position to avoid obstructions during fruit picking. Firstly, the original BottleneckCSP module in the YOLOv5 backbone network is enhanced to extract deeper features from images while maintaining lightweight. Secondly, the ECA module is embedded into the improved backbone network to better extract features of different apple targets. Lastly, the initial anchor frame size of the network is adjusted to avoid recognizing apples in distant planting rows. The results demonstrate that this improved model achieves high accuracy rates and recall rates for recognizing various types of apple picking methods with an average recognition time of 0.025s per image. Compared with other models tested on six types of apple picking methods, including the original YOLOv5 model as well as YOLOv3 and EfficientDet‐D0 algorithms, our improved model shows significant improvements in mAP by 1.95%, 17.6%, and 12.7% respectively. This method provides technical support for robots' picking hands to actively avoid obstructions caused by branches during fruit harvesting, effectively reducing apple loss.