Squash is a sport where referee decisions are essential to the game. However, referee decisions in squash are very subjective in nature. Disputes, both from the players and the audience, regularly happen because the referee made a controversial call. In this study ,we proposed to automate the referee decision process through machine learning. We trained neural networks to predict squash referee decisions using data from 400 referee decisions acquired through extensive video footage reviewing and labeling. Six positional values were extracted, including the attacking player’s position, the retreating player’s position, the ball’s position in the frame, the ball’s projected first bounce, the ball’s projected second bounce, and the attacking player’s racket head position. We calculated nine additional distance values, such as the distance between players and the distance from the attacking player's racket head to the ball's path. Models were trained on Wolfram Mathematica and Python using these values. The best Wolfram Mathematica model achieved an 86% ± 3.03% accuracy, while the best Python model performed a 0.852 ± 0.051 accuracy (85.2% ± 5.1%). These accuracies surpass 85%, demonstrating near-human performances. Our model has great potential for improvement as it's currently trained with limited data (400 referee decisions) and lacks crucial data points such as time and speed. The performance of our model is almost surely going to improve significantly with a larger training data set. Unlike human referees, machine learning models follow a consistent standard, have unlimited attention spans, and make decisions instantly. If the accuracy is improved in the future, the model can potentially serve as an extra refereeing official for both professional and amateur squash matches. Both the analysis of referee decisions in squash and proposal to automate the process using machine learning is unique to this study.

The use of biostimulants consisting of plant growth promoting rhizobacteria (PGPR) is rapidly expanding in horticulture in recent years. In the current study, a novel mix of six Bacillus sp. strains was tested as a PGPR biostimulant in two experiments with zucchini squash (Cucurbita pepo L.) cultivated in the greenhouse soil and in an open field, respectively. In both experiments, seeds of the local landrace ‘Kompokolokytho’ and the commercial hybrid ‘ARO-800’ were either inoculated or non-inoculated with the PGPR biostimulant. The application of the six Bacillus sp. strains increased both the vegetative growth and the yield of zucchini squash, and these effects were associated with significantly higher shoot phosphorus levels in both experiments and both genotypes. Furthermore, at the end of the cultivation, the colony forming units of Bacillus sp. were appreciably higher in plants originating from inoculated compared to non-inoculated seeds, indicating that the tested mix of Bacillus sp can be successfully applied through seed inoculation. ‘ARO-800’ produced more vegetative and fruit biomass than ‘kompokolokytho’ under greenhouse cropping conditions, while in the open-field crop both genotypes performed equally, presumably because the local landrace is traditionally grown in open fields, and thus it is not well adapted to greenhouse cropping.

The plant graft healing process is an intricate development influenced by numerous endogenous and environmental factors. This process involves the histological changes, physiological and biochemical reactions, signal transduction, and hormone exchanges in the grafting junction. Studies have shown that applying exogenous plant growth regulators can effectively promote the graft healing process and improve the quality of grafted plantlets. However, the physiological and molecular mechanism of graft healing formation remains unclear. In our present study, transcriptome changes in the melon and cucurbita genomes were analyzed between control and NAA treatment, and we provided the first view of complex networks to regulate graft healing under exogenous NAA application. The results showed that the exogenous NAA application could accelerate the graft healing process of oriental melon scion grafted onto squash rootstock through histological observation, increase the SOD, POD, PAL, and PPO activities during graft union development and enhance the contents of IAA, GA3, and ZR except for the IL stage. The DEGs were identified in the plant hormone signal-transduction, phenylpropanoid biosynthesis, and phenylalanine metabolism through transcriptome analysis of CK vs. NAA at the IL, CA, and VB stage by KEGG pathway enrichment analysis. Moreover, the exogenous NAA application significantly promoted the expression of genes involved in the hormone signal-transduction pathway, ROS scavenging system, and vascular bundle formation.