Maize yield in smallholder agriculture system-An approach integrating socio-economic and crop management factors

Multi-source information fusion-driven corn yield prediction using the Random Forest from the perspective of Agricultural and Forestry Economic Management

The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of crop yield prediction (CYP), particularly for corn, along with ensuring application stability. The digital camera is selected to capture the digital image of a 60 m × 10 m experimental cornfield. Subsequently, the obtained data on corn yield and statistical growth serve as inputs for the multi-source information fusion (MSIF). The study proposes an MSIF-based CYP Random Forest model by amalgamating the fluctuating corn yield dataset. In relation to the spatial variability of the experimental cornfield, the fitting degree and prediction ability of the proposed MSIF-based CYP Random Forest are analyzed, with statistics collected from 1-hectare, 10-hectare, 20-hectare, 30-hectare, and 50-hectare experimental cornfields. Results indicate that the proposed MSIF-based CYP Random Forest model outperforms control models such as support vector machine (SVM) and Long Short-Term Memory (LSTM), achieving the highest prediction accuracy of 89.30%, surpassing SVM and LSTM by approximately 13.44%. Meanwhile, as the experimental field size increases, the proposed model demonstrates higher prediction accuracy, reaching a maximum of 98.71%. This study is anticipated to offer early warnings of potential factors affecting crop yields and to further advocate for the adoption of MSIF-based CYP. These findings hold significant research implications for personnel involved in Agricultural and Forestry Economic Management within the context of developing agricultural economy.

Unbalanced fertilizer use in the Eastern Gangetic Plain: The influence of Government recommendations, fertilizer type, farm size and cropping patterns

Intensive cropping systems with diverse cropping patterns present a challenge for nutrient management on smallholder farms. Government-endorsed recommendations for crop fertilizer use are designed to assist farmers achieve profitable and balanced nutrient inputs, but it is unclear how closely farmers follow these recommendations. We identified farmers’ current nutrient use gaps (overuse or underuse) relative to the Government-endorsed recommended nutrient doses in two cropping patterns in three representative Agro-ecological Zones of Bangladesh. A total of 330 farms were surveyed in 2019 from three farm size categories (referred to as large-, medium and small-scale) and their gaps in nutrient use were assessed relative to Government-endorsed Fertilizer Recommendation Guides (FRG) published in 2012 and in 2018: FRG-2012 and FRG-2018. The large- and medium-scale farms used 11–16%, 80–90% and 21–30%, respectively, over-doses of NPK in the cropping season under fully rice-based cropping pattern relative to FRG-2012 recommendations, while the over-dose levels were much lower for small-scale farms. Small-scale farms used much less than recommended S, Mg, Zn, B and organic manure (OM) rates relative to FRG-2012. The FRG-2018, which increased N and K recommendations but decreased the P recommendation for rice crops relative to FRG-2012, shows that all farms can decrease the dose of P (by 50%) while small-scale farms need to increase the dose of N (7%), K (16%), S (20%) and to apply Zn in the fully rice-based cropping pattern. On the other hand, the farms could greatly reduce NPK (19%, 86% and 44%, respectively) use while increasing S (14%), Mg, Zn, B and OM use relative to FRG-2018 in the pattern with the high-value potato crop. To increase crop profitability, enhance food security and save Government treasury in the Eastern Gangetic Plain enabling approaches are needed to effectively communicate the benefits of balanced nutrient use practices to farmers.

Utilization of Internet of Things and Wireless Sensor Networks for Sustainable Smallholder Agriculture

Agriculture is the economy’s backbone for most developing countries. Most of these countries suffer from insufficient agricultural production. The availability of real-time, reliable and farm-specific information may significantly contribute to more sufficient and sustained production. Typically, such information is usually fragmented and often does fit one-on-one with the farm or farm plot. Automated, precise and affordable data collection and dissemination tools are vital to bring such information to these levels. The tools must address details of spatial and temporal variability. The Internet of Things (IoT) and wireless sensor networks (WSNs) are useful technology in this respect. This paper investigates the usability of IoT and WSN for smallholder agriculture applications. An in-depth qualitative and quantitative analysis of relevant work over the past decade was conducted. We explore the type and purpose of agricultural parameters, study and describe available resources, needed skills and technological requirements that allow sustained deployment of IoT and WSN technology. Our findings reveal significant gaps in utilization of the technology in the context of smallholder farm practices caused by social, economic, infrastructural and technological barriers. We also identify a significant future opportunity to design and implement affordable and reliable data acquisition tools and frameworks, with a possible integration of citizen science.

A Proposed Satellite-Based Crop Insurance System for Smallholder Maize Farming

Crop farming in Sub-Saharan Africa is constantly confronted by extreme weather events. Researchers have been striving to develop different tools that can be used to reduce the impacts of adverse weather on agriculture. Index-based crop insurance (IBCI) has emerged to be one of the tools that could potentially hedge farmers against weather-related risks. However, IBCI is still constrained by poor product design and basis risk. This study complements the efforts to improve IBCI design by evaluating the performances of the Tropical Applications of Meteorology using SATellite data and ground-based observations (TAMSAT) and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) in estimating rainfall at different spatial scales over the maize-growing season in a smallholder farming area in South Africa. Results show that CHIRPS outperforms TAMSAT and produces better results at 20-day and monthly time steps. The study then uses CHIRPS and a crop water requirements (CWR) model to derive IBCI thresholds and an IBCI payout model. Results of CWR modeling show that this proposed IBCI system can cover the development, mid-season, and late-season stages of maize growth in the study area. The study then uses this information to calculate the weight, trigger, exit, and tick for each of these growth stages. Although this approach is premised on the prevailing conditions in the study area, it can be applied in other areas with different growing conditions to improve IBCI design.

Do Satellite Data Correlate with In Situ Rainfall and Smallholder Crop Yields? Implications for Crop Insurance

Adverse weather is one of the most prevalent sources of risk in agriculture. Its impacts are aggravated by the lack of effective risk management mechanisms. That is why resource-poor farmers tend to respond to weather risks by adopting low-capital investment, low-return, and low-risk agricultural practices. This challenge needs to be addressed with innovative risk management strategies. One of the tools that is gaining traction, especially in the developing countries, is weather-index-based insurance (WII). However, WII uptake is still low because of several constraints, one of which is basis risk. This study attempts to address this problem by evaluating the suitability of TAMSAT, CHIRPS, MODIS, and Sentinel-2 data for WII. We evaluated the first three datasets against in situ rainfall measurements at different spatial and temporal scales over the maize-growing season in a smallholder farming area in South Africa. CHIRPS had higher correlations with in situ measured rainfall data than TAMSAT and MODIS NDVI. CHIRPS performed equally well at 10 km and 25 km spatial scales, and better at monthly than daily and 16-day time steps (maximum R = 0.78, mean R = 0.72). Due to the lack of reliable historical yield data, we conducted yield surveys over three consecutive seasons using an objective crop cut method. We then assessed how well rainfall and NDVI related with maize yield. There was a poor relationship between these variables and maize yield (R2 ≤ 0.14). The study concludes by pointing out that crop yield does not always have a linear relationship with weather and vegetation indices, and that water is not always the main yield-limiting factor in smallholder farming systems. To minimize basis risk, the process of designing WII must include identification of main yield-limiting factors for specific localities. Alternatively, insurers could use crop water requirement methods to design WII.

Conservation Agriculture Affects Grain and Nutrient Yields of Maize (Zea Mays L.) and Can Impact Food and Nutrition Security in Sub-Saharan Africa

Maize is a major staple and plays an essential role in food and nutrition security in Sub-Saharan Africa (SSA). Conservation agriculture (CA), a climate-smart agriculture practise based on minimum soil disturbance, crop residue retention, and crop diversification, has been widely advocated but without extensive research on the impact it may have on maize nutrient composition, and food and nutrition security. This study assessed the grain yield, macro- and micronutrient mineral content, and nutrient yield of eight maize varieties grown in Malawi, and how these are affected by CA practises over two seasons. The minerals were analysed by inductively coupled plasma (ICP) coupled to optical emission spectroscopy (OES) and to mass spectroscopy (MS). Grain yield and Se content differed among the varieties, while C, N, Fe, K, Mg, Mn, P, and Zn were similar. The local variety Kanjerenjere showed lowest grain and nutrient yields. The open-pollinated varieties (OPVs) concentrated more minerals than the F1 hybrids, but the latter showed higher yields for both grain and nutrients. Typical consumption of the eight maize varieties could fully meet the protein and Mg dietary reference intake (DRIs) of Malawian children (1–3 years), as well as Mg and Mn needs of adult women (19–50 years), but their contribution to dietary requirements was low for Fe (39–41%) and K (13–21%). The trials showed that CA increased grain yield (1.2- to 1.8-fold) and Se content (1.1- to 1.7-fold), but that it had no effect on C, K, Mg, P, and Zn, and that N (1.1- to 1.2-fold), Mn (1.1- to 1.8-fold), and Fe (1.3- to 3.4-fold) were reduced. The high increase in grain yield under CA treatments resulted in increased yields of protein and Se, no effect on the yields of K, Mg, Mn, P, Zn, and reduced Fe yield. Conservation agriculture could contribute in reducing the risk of Se deficiency in Malawian women and children but exacerbates the risk of Fe deficiency. A combination of strategies will be needed to mitigate some of the foreseen effects of climate change on agriculture, and food and nutrition security, and improve nutrient intake.

Linking Agricultural Index Insurance with Factors That Influence Maize Yield in Rain-Fed Smallholder Farming Systems

Weather extremes pose substantial threats to food security in areas where the main source of livelihood is rain-fed crop production. In most of these areas, agricultural index insurance (AII) is recognized as being capable of securitizing food production by providing safety nets against weather-induced crop losses. Unfortunately, however, AII does not indemnify farmers for non-weather-related crop losses. This study investigates how this gap can be filled by exploring strategies through which AII can be linked with non-weather factors that influence crop production. We do this by using an improvised variable ranking methodology to identify these factors in the O.R. Tambo District Municipality, South Africa. Results show that key agrometeorological variables comprising surface moisture content, growing degree-days, and precipitation influence maize yield even under optimal weather conditions, while seed variety, fertilizer application rate, soil pH, and ownership of machinery play an equally important role. This finding is important because it demonstrates that although AII focuses more on weather elements, there are non-weather variables that may expose farmers to production risk even under optimal weather conditions. As such, linking AII with critical non-weather, yield-determining factors can be a better risk management strategy.

Macronutrient Management Effects on Nutrient Accumulation, Partitioning, Remobilization, and Yield of Hybrid Maize Cultivars

It is critical to understand nutrient dynamics within different plant parts to correctly fine-tune agronomic advices, and to update breeding programs for increasing nutrient use efficiencies and yields. Farmer's field-based research was conducted to assess the effects of nitrogen (N), phosphorus (P), and potassium (K) levels on dry matter and nutrient accumulation, partitioning, and remobilization dynamics in three popular maize (Zea mays L.) hybrids (P3522, P3396, and Rajkumar) over two years in an alluvial soil of West Bengal, India. Experimental results revealed that NPK rates as well as different cultivars significantly (p ≤ 0.05) influenced the dry matter accumulation (DMA) in different plant parts of maize at both silking and physiological maturity. The post-silking dry matter accumulation (PSDMA) and post-silking N, P, and K accumulations (PSNA, PSPA, PSKA) were highest in cultivar P3396. However, cultivar P3522 recorded the highest nutrient remobilizations and contributions to grain nutrient content. Total P and K accumulation were highest with 125% of the recommended dose of fertilizer (RDF) while total N accumulation increased even after 150% RDF (100% RDF is 200 kg N, 60 kg P₂O₅, and 60 kg K₂O ha^-1 for the study region). Application of 125% RDF was optimum for PSDMA. The PSNA continued to increase up to 150% RDF while 125% RDF was optimum for PSPA. Cultivar differences significantly affected both remobilization efficiency (RE) and contribution to grain nutrient content for all tested macronutrients (N, P, and K). In general, RE as well as contribution to grain nutrient content was highest at 125% RDF for N and K, and at 100% RDF for P (either significantly or at par with other rates) for plots receiving nutrients. For all tested cultivars, nutrient remobilization and contribution to grain nutrient content was highest under nutrient-omission plots and absolute control plots. Both year and cultivar effects were non-significant for both grain and stover yields of maize. Application of 75% RDF was sufficient to achieve the attainable yield at the study location. The cultivar P3522 showed higher yield over both P3396 and Rajkumar, irrespective of fertilizer doses, although, the differences were not statistically significant (p ≥ 0.05). The study underscores the importance of maize adaptive responses in terms of nutrients accumulation and remobilization at different levels of nutrient availability for stabilizing yield.

Expression of Thioredoxin/Thioredoxin Reductase System Genes in Aphid-Challenged Maize Seedlings

Thioredoxins (Trxs) and thioredoxin reductases (TrxRs) encompass a highly complex network involved in sustaining thiol-based redox homeostasis in plant tissues. The purpose of the study was to gain a new insight into transcriptional reprogramming of the several genes involved in functioning of Trx/TrxR system in maize (Zea mays L.) seedlings, exposed to the bird cherry-oat aphid (Rhopalosiphum padi L.) or the rose-grass aphid (Metopolophium dirhodum Walk.) infestation. The biotests were performed on two maize genotypes (susceptible Złota Karłowa and relatively resistant Waza). The application of real-time qRT-PCR technique allowed to identify a molecular mechanism triggered in more resistant maize plants, linked to upregulation of thioredoxins-encoding genes (Trx-f, Trx-h, Trx-m, Trx-x) and thioredoxin reductase genes (Ftr1, Trxr2). Significant enhancement of TrxR activity in aphid-infested Waza seedlings was also demonstrated. Furthermore, we used an electrical penetration graph (EPG) recordings of M. dirhodum stylet activities in seedlings of the two studied maize varieties. Duration of phloem phase (E1 and E2 models) of rose-grass aphids was about three times longer while feeding in Waza plants, compared to Złota Karłowa cv. The role of activation of Trx/TrxR system in maintaining redox balance and counteracting oxidative-induced damages of macromolecules in aphid-stressed maize plants is discussed.