Crops, Volume 4, Issue 3 (September 2024) – 5 articles

Sugarcane suffers from the increased frequency and severity of droughts and floods, negatively affecting growing conditions. Climate change has affected cultivation, and the growth dynamics have changed over the years. The identification of the development stages of sugarcane is necessary to reduce its vulnerability. Traditional methods are inefficient when detecting those changes, especially when estimating sugarcane maturity—a critical step in sugarcane production. Hence, the study aimed to develop a cost- and time-effective method to estimate sugarcane maturity using high spatial-resolution remote sensing data. Images were acquired using a drone. Field samples were collected and measured in the laboratory for brix and pol values. Normalized Difference Water Index, Green Normalized Difference Vegetation Index and green band were chosen (highest correlation with field samples) for further analysis. Random forest (RF), Support Vector Machine (SVM), and multi-linear regression models were used to predict sugarcane maturity using the brix and pol variables. The best performance was obtained from the RF model. Hence, the maturity index of the study area was calculated based on the RF model results. It was found that the field plot has not yet reached maturity for harvesting. The developed cost- and time-effective method allows temporal crop monitoring and optimizes the harvest time. Full article

COVID-19 has caused a deep economic impact on the lives of small and marginal farmers due to travel restrictions, market closures, and social distancing requirements. Due to COVID-induced labor scarcity and water shortage in India, direct-seeded rice (DSR) has emerged as a viable alternative to puddled transplanted rice (PTR). However, there was plenty of labor available in Pakistan and Bangladesh for rice cultivation during COVID-19 times. Therefore, both countries did not observe the shift from PTR to DSR. The cost of inputs, such as seed, fertilizer, pesticide, and fuel, was high due to a supply–demand conflict during the COVID-19 pandemic in three countries. Farmers faced weed problems and physical and/or economical non-availability of suitable machinery for DSR cultivation during the COVID-19 pandemic. In the later years of 2022 and 2023 (post-COVID), the area under DSR decreased by 88% in India, while it remained stagnant in Pakistan and Bangladesh. Full article

Exponential population increases are threatening food security, particularly in mountainous areas. One potential solution is dual-use intercropped agroforestry systems such as olive (Olea europaea)–maize (Zea mays), which may mitigate risk by providing multiple market sources (oil and grain) for smallholder producers. Several studies have conducted integrated agroforestry land suitability analyses; however, few studies have used machine learning (ML) algorithms to evaluate multiple variables (i.e., soil physicochemical properties and climatic and topographic data) for the selection of suitable rainfed sites in mountainous terrain systems. The goal of this study is therefore to identify suitable land classes for an integrated olive–maize agroforestry system based on the Food and Agriculture Organization (FAO) land suitability assessment framework for 1757 km² in Khyber Pakhtunkhwa province, Pakistan. Information on soil physical and chemical properties was obtained from 701 soil samples, along with climatic and topographic data. After determination of land suitability classes for an integrated olive–maize-crop agroforestry system, the region was then mapped through ML algorithms using random forest (RF) and support vector machine (SVM), as well as using traditional techniques of weighted overlay (WOL). Land suitability classes predicted by ML techniques varied greatly. For example, the S1 area (highly suitable) classified through RF was 9%↑ than that of SVM, and 8%↓ than that through WOL. The area of S2 (moderately suitable) classified through RF was 18%↑ than that of SWM and was 17%↓ than the area classified through WOL; similarly, the S3 (marginally suitable) class area via RF was 27%↓ than that of SVM, and 45%↓ than the area classified through WOL. Conversely, the area of N2 (permanently not suitable class) classified through RF and SVM was 6%↑ than the area classified through WOL. Model performance was assessed through overall accuracy and Kappa Index and indicated that RF performed better than SVM and WOL. Crop suitability limitations of the study area included high elevation, slope, pH, and large gravel content. Results can be used for sustainable intensification in mountainous rainfed regions by expanding intercrop agroforestry systems in developing nations to close yield gaps. Full article

In the last few decades, various types of farming systems based on ecological principles have been proposed and developed. There is often interest in knowing about the differences between these systems, but such information must be obtained from several sources describing each of these systems. Therefore, this paper is an effort to consolidate the information on these systems in a concise manner without making comparative ratings between them. We found three components contained in the overarching theme of these systems: the reduction in external inputs, environmental protection, and sustainability. However, several variations exist between them, each with its own focus and guiding principles. Also, these farming systems contain their own specific terms to identify themselves and contain their own set of philosophies based on their founder. In this review, we provided a short description of some of the major ecologically based farming systems such as “agroecology”, “regenerative agriculture”, “holistic management”, “carbon farming”, “organic farming”, “permaculture”, “biodynamic farming”, “conservation agriculture”, and “regenerative organic farming”. We summarized these farming systems as “variants of farming systems based on ecological principles” and outlined the similarities and differences between them. We also discussed how the themes of these systems relate to the United Nations’ thirteen principles of agroecology. Although these systems share several similarities, their philosophy is rooted in their founders and the communities that choose to adopt these philosophies. Last, we discussed some of the challenges in implementing these ecological agriculture systems. Full article

Understanding genotypic variability in tolerance to heat stress during flowering, a critical growth stage, and post-stress recovery remains limited in mungbean (Vigna radiata) genotypes. This study investigates the genetic variability in in vitro pollen viability, seed set, and grain yield among mungbean genotypes in response to transient high temperatures. Thirteen genotypes were evaluated in a glasshouse study, and four in a field study, subjected to high temperatures (around 40 °C/22 °C day/night) imposed midday during flowering. Across all genotypes, the pollen viability percentage significantly decreased from 70% to 30%, accompanied by reductions in the pod size and seed number per pod, and increases in unfertilized pods and unviable seeds. However, the seed yield per plant significantly increased for four genotypes (M12036, Celera-II AU, Crystal, and M11238/AGG325961), attributed to elevated shoot growth and pod numbers under high-temperature treatment in the glasshouse study. Conversely, Satin II, which exhibited the highest stress tolerance index, recorded a greater seed yield under optimum conditions compared to high temperatures. Similar genotypic variability in post-heat-stress recovery and rapid growth was observed in the field study. Under non-limiting water conditions, mungbean genotypes with a relatively more indeterminate growth habit mitigated the heat stress’s impact on their pollen viability by swiftly increasing their post-stress vegetative and reproductive growth. The physiological mechanisms underlying post-stress rapid growth in these genotypes warrant further investigation and consideration in future breeding trials and mitigation strategies. Full article