Meeting the rising global food demand among limited resources necessitates transformative agricultural innovations. The Internet of Things (IoT) emerges as a pivotal technology in modern agriculture, offering data-driven solutions to optimize productivity and sustainability. This review provides a focused exploration of IoT’s transformative role in agriculture, analyzing its integration with big data, real-time monitoring, and precision farming practices. Key insights include global market trends, projections for IoT adoption in agriculture by 2030, and advancements in IoT-related technologies shaping the future of agritech. The review underscores how IoT enhances agricultural efficiency by enabling precise data collection, automated decision-making, and optimized resource use, while addressing operational challenges such as interoperability, scalability, cost constraints, and regulatory hurdles. By consolidating evidence from emerging studies, this work advocates for interdisciplinary collaborations to deepen understanding and innovation in IoT-driven smart agriculture, positioning it as a cornerstone for achieving global food security.

With the rise of “Internet + Agriculture”, existing related research has focused on the impact of Internet use on agricultural productivity. However, few studies have considered the impact on agricultural green production efficiency. This paper employed the SBM model to calculate the agricultural green production efficiency using the observation data of 459 farmers in Shaanxi, Shanxi, and Henan provinces. Further, the influencing factors, their nonlinear impact, and even the effect of using the internet on agricultural green production efficiency were analyzed. The results show that corn’s average agricultural green production efficiency is 0.44, with the main peak distributed in a low-level range. The impact of the Internet use on agricultural green production efficiency is positively moderated by rural infrastructure, household assets, and educational attainment. Age and arable land area significantly impact agricultural green production efficiency. The endogenous switching regression model (ESR) shows that the agricultural green production efficiency of farmers who do not use the internet will increase by 41.45% if they use the internet. Internet use has a “U-shaped” impact on agricultural green production efficiency, and the threshold value of the farmers’ expenditure to income ratio is 0.0886. The policy aimed at improving agricultural green production efficiency and popularizing Internet use should, therefore, focus on strengthening the emphasis on increasing agricultural green production, increasing investment in rural human capital, providing green production subsidies and green production skills training, improving infrastructure construction in rural areas, integrating and enriching agricultural-related information on the Internet.

Improving fertilizer use efficiency (FUE) is an effective means to reduce fertilizer use and environmental contamination. Few studies have considered the spatial effects of FUE and its determinants. This paper calculated the FUE of agricultural production by adopting panel data on 31 provinces in China from 2007 to 2017 using a stochastic frontier method with a heteroscedastic inefficiency term, and discussed the spatial characteristics. Further, the geographical weighted regression model (GWR) was employed to examine the spatial impact of factors on FUE and revealed the spatial dispersion and agglomeration effect. The results show that averaged FUE in China was 0.722, and had a significantly decreasing trend with a significant regional difference and spatial positive correlation in different provinces. The non-agricultural employment ratio was the leading factor for increasing FUE, and its degree of influence showed a decreasing trend from eastern to western China. The different agricultural industry development modes, crop planting patterns adjustment, labor transfer, and policy incentive systems for increasing the non-agricultural employment ratio should be developed for different regions. Farmers’ income had a negative impact on FUE, but the influence degree decreased annually. Education level had a negative impact on FUE and was relatively weak, but the influence degree was increasing. This should strengthen the exploration of a scientific and practical technical training system for farmers on fertilizer use while improving educational levels in different regions on the basis of local characteristics. The impact of disasters on FUE depended on their severity, and a combined weather and disaster forecasting mechanism should be developed.

Conventional agriculture harms the environment and threatens sustainability. To address these issues, sustainable agricultural practices (SAPs) have become imperative. This study utilizes a meta-analysis approach to comprehensively assess empirical studies, investigate the impact of SAPs on crop productivity, identify influencing factors, and examine their temporal evolution. The findings reveal that (1) SAP adoption significantly and positively influences crop productivity, with multiple practices exhibiting the most substantial impact, followed by sustainable agricultural technology. Individuals who adopted SAPs achieved crop productivity that was 980 kilograms per hectare higher than those who did not. (2) Factors such as age, farm size, family size, livestock units, credit access, off-farm income, market distance, and cooperative membership negatively affect crop productivity, whereas education and extension services have a positive impact. (3) The positive effects of education and extension services on crop productivity strengthen over time. The strengthening of these variables over time implies a gradual increase in farmer awareness, access to resources, and adoption of SAPs, highlighting their evolving role in driving them. Accordingly, none of the past researchers identified any patterns in the variables influencing crop productivity. Therefore, promoting SAP adoption and prioritizing education and extension services can offer farmers with experience and support, thereby enhancing crop productivity. Future initiatives should therefore combine interdisciplinary methods, technology, and community involvement for ensuring SAP’s sustainability and scalability.