As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21^st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions.

Hydroponics, a soilless cultivation technique using nutrient solutions under controlled conditions, is used for growing vegetables, high-value crops, and flowers. It produces significantly higher yields compared to conventional agriculture despite its higher energy consumption. The success of a hydroponic system relies on the composition of the nutrient solution, which contains all the essential mineral elements necessary for optimal plant growth and high yield. This review delves into the discussion of enhancing nutrient solution management strategies across different hydroponic systems. The aim of this review is to discuss various techniques for monitoring nutrient solutions in order to improve nutrient use efficiency (NUE) and water use efficiency (WUE). The conventional approach of monitoring the hydroponic nutrient solution using electrical conductivity measurement may not provide precise information about ion concentrations, potentially resulting in poor yields or excessive fertilizer usage. To overcome these limitations, alternative management strategies have been developed to enable more accurate monitoring and efficient management. One such strategy is the nitrogen-based approach, where nitrogen concentration becomes the primary controlled element in the nutrient solution and leads to WUE and NUE development by prolonging nutrient solution recirculation. Furthermore, various methods have been devised to improve nutrient solution strategies. These include using ion-selective electrodes to measure individual ions in the hydroponic nutrient solution, using sensors to monitor substrate moisture content, estimating water requirements, and implementing programmed nutrient addition methods. In addition to introducing different management techniques to optimize hydroponic performance, this review provides a better understanding of hydroponic systems.

Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.

Intercropping (IC) is a promising approach used to improve soil health and sustainable crop production. However, it is unknown whether IC improve the soil health status and biomass productivity of crops cultivated in podzols under cool climate in boreal ecosystems. Two silage corn and three forage soybean genotypes were cultivated either as inter or monocrop (MC) treatments in a randomized complete block design. IC resulted in 28% increase in total forage production (FP). A reduction in rhizosphere soil pH (RS-pH) was observed in the IC treatments. Conversely, the rhizosphere soil acid phosphatase (RS-APase) activity was significantly higher (26–46%) in the IC treatments and occurred concomitant with a significant increase in available phosphorus (RS-P_available) (26–74%) in the rhizosphere. Furthermore, IC enhanced the active microbial composition and strong positive correlations were observed between RS-P_available, RS-APase, microbial biomass and FP; while RS-pH was negatively correlated with FP, RS-APase and RS-P_available. These findings suggested silage corn intercropped with forage soybean could be a viable approach to enhance FP through improved active microbial community structure, RS-APase activity and RS-P_available when cultivated on podzols in cool climate boreal ecosystem.

Nanopriming has been shown to significantly improve seed germination and seedling vigor in several agricultural crops. However, this approach has not been applied to native upland boreal forest species with complex seed dormancy to improve propagation. Herein, we demonstrate the effectiveness of carbon nanoparticles functionalized with carboxylic acids in resolving seed dormancy and improved the propagation of two native upland boreal forest species. Seed priming with carbon nanoparticles functionalized with carboxylic acids followed by stratification were observed to be the most effective in improving germination to 90% in green alder (Alnus viridis L.) compared to 60% in the control. Conversely, a combination of carbon nanoparticles (CNPs), especially multiwall carbon nanoparticles functionalized with carboxylic acid (MWCNT–COOH), cold stratification, mechanical scarification and hormonal priming (gibberellic acid) was effective for buffaloberry seeds (Shepherdia canadensis L.). Both concentrations (20 µg and 40 µg) of MWCNT–COOH had a higher percent germination (90%) compared to all other treatments. Furthermore, we observed the improvement in germination, seedling vigor and resolution of both embryo and seed coat dormancy in upland boreal forest species appears to be associated with the remodeling of C18:3 enriched fatty acids in the following seed membrane lipid molecular species: PC18:1/18:3, PG16:1/18:3, PE18:3/18:2, and digalactosyldiacylglycerol (DGDG18:3/18:3). These findings suggest that nanopriming may be a useful approach to resolve seed dormancy issues and improve the seed germination in non-resource upland boreal forest species ideally suited for forest reclamation following resource mining.

Precision agriculture (PA) involves the management of agricultural fields including spatial information of soil properties derived from apparent electrical conductivity (EC_a) measurements. While this approach is gaining much attention in agricultural management, farmed podzolic soils are under-represented in the relevant literature. This study: (i) established the relationship between EC_a and soil moisture content (SMC) measured using time domain reflectometry (TDR); and (ii) evaluated the estimated SMC with EC_a measurements obtained with two electromagnetic induction (EMI) sensors, i.e., multi-coil and multi-frequency, using TDR measured SMC. Measurements were taken on several plots at Pynn’s Brook Research Station, Pasadena, Newfoundland, Canada. The means of EC_a measurements were calculated for the same sampling location in each plot. The linear regression models generated for SMC using the CMD-MINIEXPLORER were statistically significant with the highest R² of 0.79 and the lowest RMSE (root mean square error) of 0.015 m³ m⁻³ but were not significant for GEM-2 with the lowest R² of 0.17 and RMSE of 0.045 m³ m⁻³; this was due to the difference in the depth of investigation between the two EMI sensors. The validation of the SMC regression models for the two EMI sensors produced the highest R² = 0.54 with the lowest RMSE prediction = 0.031 m³ m⁻³ given by CMD-MINIEXPLORER. The result demonstrated that the CMD-MINIEXPLORER based measurements better predicted shallow SMC, while deeper SMC was better predicted by GEM-2 measurements. In addition, the EC_a measurements obtained through either multi-coil or multi-frequency sensors have the potential to be successfully employed for SMC mapping at the field scale.