Since plug seedling plays a key role in automatic transplanting, this work aimed to explore the effect biochar has on the root growth of plug seedlings. The physicochemical properties tests showed that the addition of biochar in the peats could increase the porosity, pH, and EC values of the substrate, and the substrates treated with 0%, 10%, 20%, and 30% biochar could meet the requirements of seedling raising. The water retention of the substrate was superior with the increase of biochar proportion, and the nitrogen release significantly decreased with the increase of the biochar proportion. Our results demonstrated that the substrate with 10% biochar-treated apparently promoted the growth of seedlings and root systems, even the length of the root-tip cells. However, the substrates with 40% and 50% biochar-treated obviously inhibited the growth of seedlings and root systems. It was noticed that the strength of substrate with appropriate biochar proportion was enhanced, as well. Under the interaction of strong root system and solid substrate, the compressive strength of the substrate with 20% and 10% biochar-treated was much better than others, especially that of 40% and 50% biochar-treated, which efficiently satisfied the requirements of automatic seedling picking. The biochar may have a good application prospect in seedling raising.

Robotically selective broccoli harvesting requires precise lightweight detection models to efficiently detect broccoli heads. Therefore, this study introduces a lightweight and high-precision detection model named LBDC-YOLO (Lightweight Broccoli Detection in Complex Environment—You Look Only Once), based on the improved YOLOv8 (You Look Only Once, Version 8). The model incorporates the Slim-neck design paradigm based on GSConv to reduce computational complexity. Furthermore, Triplet Attention is integrated into the backbone network to capture cross-dimensional interactions between spatial and channel dimensions, enhancing the model’s feature extraction capability under multiple interfering factors. The original neck network structure is replaced with a BiFPN (Bidirectional Feature Pyramid Network), optimizing the cross-layer connection structure, and employing weighted fusion methods for better integration of multi-scale features. The model undergoes training and testing on a dataset constructed in real field conditions, featuring broccoli images under various influencing factors. Experimental results demonstrate that LBDC-YOLO achieves an average detection accuracy of 94.44% for broccoli. Compared to the original YOLOv8n, LBDC-YOLO achieves a 32.1% reduction in computational complexity, a 47.8% decrease in parameters, a 44.4% reduction in model size, and a 0.47 percentage point accuracy improvement. When compared to models such as YOLOv5n, YOLOv5s, and YOLOv7-tiny, LBDC-YOLO exhibits higher detection accuracy and lower computational complexity, presenting clear advantages for broccoli detection tasks in complex field environments. The results of this study provide an accurate and lightweight method for the detection of broccoli heads in complex field environments. This work aims to inspire further research in precision agriculture and to advance knowledge in model-assisted agricultural practices.

Automating vegetable seedling transplanting has led to labor-saving opportunities and improved productivity. Some changes in seedling agronomy are necessary for efficient transplanting. In this study, the local nursery substrates were added with the herbaceous peat, the sphagnum peat, and the coir peat, respectively. Effects of the new compound substrates were investigated on the seedling growth qualities and the root substrate strength. In the results, we found that the addition of three compound mediums significantly affected the physiochemical properties of the original substrates. Under the same conditions of cultivating seedlings, appropriate additions of new compounds promoted the seedling growth. Moreover, deficient or excessive additions inhibited the growing development of seedlings and their roots. The corresponding additions also improved the structural characteristics of the root lumps. Compared with the two other compounds, the nursery substrates added with the sphagnum peat were optimized in contribution to the seedling qualities and the root substrate strengths. As the local substrate and the sphagnum peat were mixed at a volume ratio of 2:1, the dry matter accumulation of seedlings was 2.18 times more than the original. Their root lumps had the best consolidation strength. This new compound of substrates may be an effective application for the necessary qualities of seedlings for automatic transplanting.

Since plug seedlings play a key role in automatic transplanting, this work aimed to explore the interaction between the biochar rate, water content, and N–fertilization in the substrate on the cultivation of cucumber seedlings before and after transplanting. The research showed that most of the factors obtained significant individual and interaction effects by measuring and analyzing the growth parameters of seedlings before transplanting. Most growth parameters significantly decreased with the increase in biochar rate except Water Use Efficiency which obtained the highest value of 2.06 g/L when the biochar rate was 10%. Furthermore, some growth parameters increased significantly with the increase in water content, while the Total Dry Matter and Water Use Efficiency reached their highest values, 0.778 g and 1.94 g/L, respectively, when the water content was 65%. All growth parameters reached their highest values when the N–fertilization was 50%; too high or too low of N–fertilization was not conducive to the growth of seedlings. The growth parameters and photosynthesis indices of seedlings cultivated after transplanting indicated that the seedlings with superior growth before transplanting performed better than other treatments in regard to growth and photosynthesis after transplanting. The interactions were in general optimal when the biochar rate was 5%, water content was 80%, and N–fertilization was 50% in the substrate, and seedlings cultivated under this treatment could not only meet the requirements of automatic transplanting, but also ensure rapid growth after transplanting. This study thus provides some guidance for the effective cultivation of vegetable plug seedlings.

Low degree of transplanting automation will affect production efficiency and planting quality in vegetable cultivation. A new seedling pick-up device was designed and constructed to reduce direct grasping damages to seedlings and improve transplanting efficiency. The pick-up device consists of an air jet loosening device, a flexible pick-up manipulator, a parallel feeding device, and a multi-axis motion control system. Its working principle is to use air jet ejection to assist in loosening of seedling roots from the tray cells, grasp their stems for extracting with the pick-up manipulator, and finally transfer them to the delivery device for feeding into the planting device as needed. The mechanical structure and working parameters of each component were designed, and the control system was constructed according to the working requirements of ejecting, extracting, transferring, and discharging operations. A prototype of the new pick-up device was constructed, and its performance evaluation was conducted using an orthogonal experimental design using cucumber, pepper and caluiflower as test objects. The results showed that the test object, the root lump's moisture content and the loosening way (either as a whole or individual loosening of seedlings) had significant effects on the success ratio in picking up seedlings. Overall, the success in picking up seedlings from the cell was found to be influenced by horticultural and mechanical factors. Under the optimal level group, the maximum success ratio for automatic picking up seedlings was up to 94.49% for pepper while that of cucumber and cauliflower recorded 90.75% and 92.62%, respectively. The seedling pick-up performance was satisfactory for efficient transplanting requirements.

Efficient greenhouse production has a great supporting role in the development of vegetable agricultural and sideline product processing. In this paper, a simplified automatic transplanting device was designed and evaluated in a laboratory. The device mainly consists of a seedling pick-up gripper, a transplanting manipulator, two conveyors and a control system. The flexible multi-pin gripper was designed to effectively grasp, hold, and release seedlings. Through a combination innovation of the linear modules, the transplanting manipulator was designed to move the seedling gripper to the desired working position. The conveyors were the pallet-type double-row chain transmission system for automatic feeding of plug trays and growth pots. The control system was developed to coordinate each of the aforementioned function units. The multi-factor orthogonal and transplanting performance experiments were carried out under the standard seedling agronomy. The results showed that the transplanting frequency and the pick-up depth significantly affected the transplanting quality. When the transplanting frequency was 15 plants/min, the tightened spring force was 1.2 N, and the pick-up penetration depth was 35 mm, the optimum effects of automatic transplanting seedlings could be achieved. The maximum success in transplanting seedlings was 95.47% for local vegetable crops. The developed prototype could realize less waste of seedling resources at the farm level.