Tree Crops Research Articles

Impact of Aggregation Pheromone Traps on Spatial Distribution of Halyomorpha halys Damage in Apple Orchards.

Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) is an invasive pest causing significant damage to tree crops. Our study examined the impact of newly designed aggregation pheromone-baited 'mini-sailboat' (MSB) traps for controlling H. halys and its effect on the spatial distribution of fruit damage. Four replicates of four traps, with a total of 16 MSB traps, were placed along a 1.3 km border of apple orchards, concentrating the traps on one side of the orchards. A fruit damage assessment for incidence and severity was conducted at increasing distances from the orchard border where the traps were placed, encompassing 107 assessment points. Our study showed that deploying MSB traps along the orchard border significantly increased fruit damage within the first 45 m compared to control plots without traps. However, beyond the first 45 m from the border, there was a significant reduction in damage incidence. In the treated plots, 50% of the damage occurred within 26 m of the traps, while in control plots, within 85 m. Shifting the fruit damage pattern means restricting the pests lingering in a narrow strip near the MSB traps, which paves the way for improved techniques to restructure the crop perimeter.

Long‐Term Effects of Arable and Tree Cropping Systems on Soil Organic Carbon and Nitrogen Dynamics in a Tropical Agroecological Transition Zone

ABSTRACTContinuous cropping can affect soil carbon and nitrogen stocks and litter decomposition, but research on smallholder farms in Africa is limited. This study, conducted from 2020 to 2023 in Ghana's forest‐savanna transition zone, examined four cropping systems: continuous maize monocrop (M), maize rotated with legumes (ML), young cashew intercropped with maize or legumes (YCM/L), and mature cashew (MC). The objective was to assess the long‐term impact of the cropping systems on soil organic carbon (SOC), nitrogen (N) stocks, and soil organic matter (SOM) decomposition rates using the tea bag protocol. Results showed significant variability in SOC and N stocks across the systems. At a 0–15 cm depth, SOC in the MC and M systems was 160% and 149% higher than in the YCM/L system. At 15–30 cm, SOC in the M and MC systems was 86% and 132% higher than in YCM/L. Soil nitrogen stocks followed a similar trend, with MC and M systems showing 94%–199% higher values than YCM/L at both depths. SOM decomposition rates for green and rooibos tea in the MC and ML systems were statistically similar after 90 days of incubation (p > 0.05). This study, the first to use the tea bag protocol in Ghanaian soils, revealed that mature cashew and sustainable practices, such as adding maize stover, can enhance SOC and N stocks in highly weathered tropical soils. These findings underscore the potential for specific cropping systems to improve soil health on smallholder farms.

The Determination of Capitalization Rate by the Remote Segments Approach: The Case of an Agricultural Land Appraisal

In the absence of comparative real estate data in the market segment of the property to be estimated, the appraiser may resort to income capitalization to estimate the market value. Often, however, the choice of which rate to apply is affected by subjective and arbitrary assessments. The estimation result can therefore be inaccurate and rather unclear. However, the Remote Segments Approach (RSA), through appropriate adjustments on the original values, prices, and incomes detected in the remote segments, makes it possible to arrive at an appraisal result consistent with estimative logic and real estate valuation standards. The proposed application illustrates the estimation of the market value of a specialized fruit orchard of avocado, which is to be considered new in relation to other fruit species already present in the reference area. The adjustments required by the RSA are solved with the General Appraisal System (GAS), defining the difference matrix based on relevant characters common to all segments considered. The application is carried out by comparing the segment in which the orchard being estimated falls (subject) with other remote market segments in which prices and incomes constituted by other tree crops are collected. The market value of the subject is derived by making adjustments to the prices and incomes observed in the remote segments of comparison with a comparison function constructed through relevant characters common to the segments considered. The comparison function makes it possible to arrive at the determination of the capitalization rate to be used in estimating the value of the fruit orchard by income approach. While it is based on the comparison of segments, the approach followed allows for a value judgment consistent with the estimation comparison and capable of providing a solution less conditioned by the appraiser’s expertise in the presence of particularly pronounced limiting conditions.

Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data

Ginkgo is a multi-purpose economic tree species that plays a significant role in human production and daily life. The dry biomass of leaves serves as an accurate key indicator of the growth status of Ginkgo saplings and represents a direct source of economic yield. Given the characteristics of flexibility and high operational efficiency, affordable unmanned aerial vehicles (UAVs) have been utilized for estimating aboveground biomass in plantations, but not specifically for estimating leaf biomass at the individual sapling level. Furthermore, previous studies have primarily focused on image metrics while neglecting the potential of digital aerial photogrammetry (DAP) point cloud metrics. This study aims to investigate the estimation of crown-level leaf biomass in 3-year-old Ginkgo saplings subjected to different nitrogen treatments, using a synergistic approach that combines both image metrics and DAP metrics derived from UAV RGB images captured at varying flight heights (30 m, 60 m, and 90 m). In this study, image metrics (including the color and texture feature parameters) and DAP point cloud metrics (encompassing crown-level structural parameters, height-related and density-related metrics) were extracted and evaluated for modeling leaf biomass. The results indicated that models that utilized both image metrics and point cloud metrics generally outperformed those relying solely on image metrics. Notably, the combination of image metrics obtained from the 60 m flight height with DAP metrics derived from the 30 m height significantly enhanced the overall modeling performance, especially when optimal metrics were selected through a backward elimination approach. Among the regression methods employed, Gaussian process regression (GPR) models exhibited superior performance (CV-R2 = 0.79, rRMSE = 25.22% for the best model), compared to Partial Least Squares Regression (PLSR) models. The common critical image metrics for both GPR and PLSR models were found to be related to chlorophyll (including G, B, and their normalized indices such as NGI and NBI), while key common structural parameters from the DAP metrics included height-related and crown-related features (specifically, tree height and crown width). This approach of integrating optimal image metrics with DAP metrics derived from multi-height UAV imagery shows great promise for estimating crown-level leaf biomass in Ginkgo saplings and potentially other tree crops.

Unoccupied-Aerial-Systems-Based Biophysical Analysis of Montmorency Cherry Orchards: A Comparative Study

With the global population on the rise and arable land diminishing, the need for sustainable and precision agriculture has become increasingly important. This study explores the application of unoccupied aerial systems (UAS) in precision agriculture, specifically focusing on Montmorency cherry orchards in Payson, Utah. Despite the widespread use of UAS for various crops, there is a notable gap in research concerning cherry orchards, which present unique challenges due to their physical structure. UAS data were gathered using an RTK-enabled DJI Mavic 3M, equipped with both RGB and multispectral cameras, to capture high-resolution imagery. This research investigates two primary applications of UAS in cherry orchards: tree height mapping and crop health assessment. We also evaluate the accuracy of tree height measurements derived from three UAS data processing software packages: Pix4D, Drone2Map, and DroneDeploy. Our results indicated that DroneDeploy provided the closest relationship to ground truth data with an R2 of 0.61 and an RMSE of 31.83 cm, while Pix4D showed the lowest accuracy. Furthermore, we examined the efficacy of RGB-based vegetation indices in predicting leaf area index (LAI), a key indicator of crop health, in the absence of more expensive multispectral sensors. Twelve RGB-based indices were tested for their correlation with LAI, with the IKAW index showing the strongest correlation (R = 0.36). However, the overall explanatory power of these indices was limited, with an R2 of 0.135 in the best-fitting model. Despite the promising results for tree height estimation, the correlation between RGB-based indices and LAI was underwhelming, suggesting the need for further research.

Waking the “sleeping giant?” Mid- to Late-Holocene environment and fire history in the Aitape area, northern Papua New Guinea

The coastlines of the southwestern Pacific are dynamic environments that have been repeatedly reshaped by tectonic forces as well as changing global climate and sea level. It has been theorized that much of the north coast of New Guinea was sparsely inhabited until stabilization of coastal flats fallowing the Mid-Holocene Thermal Maximum and resulting marine high stand. We report on environmental proxy indicators measured in core samples taken near modern day Aitape, Papua New Guinea. These cores record the formation of a large lagoonal system on the modern coastal flats by 5800 cal BP. This lagoon infilled over the next several 1000 years as sea level dropped, with the modern coastal flats stabilizing by 1400 cal BP. A charcoal record spanning the period between 6200 and 1400 cal BP documents substantial increases in influx between ~6200 and 6000 cal BP and particularly from ~3000 to 2600 cal BP. Comparison to regional charcoal and ENSO records suggests that increasing aridity and ENSO intensity may drive regional patterning in fire records, however, localized charcoal records are also heavily influenced by human activity. Between 3000 and 2600 cal BP, forest management practices in the Aitape area, currently focused on tree crops and horticulture characterized by long fallowing and limited burning, shifted to a regime characterized by large scale forest clearance and shorter fallowing. We hypothesize that increasing population driven by abundant Mid-Holocene lagoonal resources may have been difficult to maintain as lagoons infilled and climate became more variable, leading to horticultural intensification.

Future Agricultural Water Availability in Mediterranean Countries under Climate Change: A Systematic Review

Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change (CC) scenarios published during 2009–2024. Two searches were performed in the Scopus and Web of Science databases, to which previously identified significant studies from different periods were also added. By applying a methodology duly protocoled in the PRISMA2020-based guideline, a final number of 44 particularly relevant studies was selected for review. A bibliometric analysis has shown that most of the published research was focused on Southwestern European countries (i.e., Spain, Italy, Portugal) and grapevine and olive tree crops. Overall, the reviewed studies state that future Mediterranean water reserves may not meet agricultural water demands, due to reduced reservoir inflows and higher irrigation demands under future CC and socioeconomic scenarios. Regarding adaptation measures to improve water-use management in agriculture, the majority of the reviewed studies indicate that the use of integrated modelling platforms and decision–support systems can significantly contribute to the development and implementation of improved water/land-management practices.

Advancing multiple ecosystem service assessment in the tropics: Evidence from Barekese and Owabi watersheds in Ghana

Watershed ecosystems are important for the provision of multiple ecosystem services (ES) that are critical to human welfare. Few studies particularly in the tropics assess the multiple ecosystem services, economic value, and effect of land use change on economic value. This paper provides evidence of the quantitative. economic value and effect of land use change on the economic value of watershed ESs from Barekese and Owabi in Ghana. Geospatial analysis and the stated preference method were used for the study. Primary and secondary data were collected from households, institutions, and other sources to quantify and estimate ecosystem services. The geospatial analysis showed that forest degradation and deforestation have increased over the last three decades in the watershed with settlements and cropland being the major land use changes. The two watersheds provide many ecosystem services, including provisioning services (water, fuelwood, bushmeat, fish), regulating services (carbon sequestration, water supply, water purification, soil fertility), and cultural services (ecotourism). An aggregated economic value for the ESs of GH₵ 707.701 x 106 ($144.428 x 106) was estimated for the two watersheds. For the different sites, the economic value for the Barekese and Owabi watersheds were $110.645 x 106 ($6609.06/ha/yr) and $33.783 x 106 ($5857.76/ha/yr) respectively. Our analysis showed that conversion of forest to other land uses resulted in a significant reduction in the value of ecosystem services. Conversion of the watershed to Tree Crop, Food Crop, Grassland or Settlement could reduce the economic value of ESs by 4%–80 %. The study demonstrates that ecosystem services assessment could provide important information for conservation and development policies related to watershed management in the tropics. To ensure ecosystem service supply, the risks of land use change should be considered in watershed conservation strategies including land use zoning and adaptive management systems.

Nitrogen deficiency differentially affects lignin biosynthesis genes and flavanols accumulation in tolerant and susceptible tea genotypes (Camellia sinensis (L.) Kuntze)

The mechanisms of the nitrogen deficiency (ND) response are complex and not sufficiently studied in evergreen tree crops. The aim of this study was to investigate the nitrogen deficiency response in two contrasting tea genotypes to reveal molecular crosstalk between tea quality and tolerance to ND. The transcriptional response to two- and four-month nitrogen deficiency was analyzed in tolerant (cv. Karatum) and susceptible (cv. Kolkhida) tea genotypes. Both GO and KEGG analyses indicated that phenylpropanoid pathway was significantly enriched under nitrogen deficiency in both cultivars. Most of the transcription factor DEGs were related to ABA-mediated stress responses; the following transcription factors were upregulated in both genotypes and in both stress periods: TEAK026346 (bZip23), TEAK015869 (RADIALIS-like 3 isoform X1), TEAK022547 (bHLH78) and one was downregulated TEAK030189 (MYB family transcription factor EFM like) indicating their important role for regulation of nitrogen deficiency response. Gene network of phenylpropanoid pathway DEGs indicated the abandoned edges in lignin biosynthesis DEGs. Generally, the results suggest greater stability of the cell wall metabolism and secondary metabolism in tolerant genotype under long term nitrogen deficiency. The revealed lignin biosynthesis genes can be new candidates for molecular breeding to develop tolerant tea genotypes.

Enhancing Sustainability through Weather Derivative Option Contracts: A Risk Management Tool in Greek Agriculture

This paper investigates the efficacy of weather derivatives as a risk management tool in the agricultural sector of Naousa, Greece, focusing on tree crops sensitive to temperature variations. The specific purpose is to assess how effectively weather derivative options can mitigate financial risks for farmers by providing strategic solutions. The study assesses the strategic application of Heating Degree Days (HDD) index options and their potential to alleviate economic vulnerabilities faced by farmers due to temperatures fluctuations. Employing different strike prices in Long Call and Straddle options strategies on the HDD index, the research offers tailored risk management solutions that cater to varying risk aversions among farmers. Moreover, the study applies the Value at Risk (VaR) methodology to quantify the financial security that weather derivatives can furnish, revealing a significantly reduced probability of severe financial losses in hedged scenarios compared to no-hedge conditions. Results show that all implemented strategies effectively enhance financial outcomes compared to scenarios without hedging, highlighting the exceptional utility of weather derivatives as risk management tools in the agricultural sector. Strategy 4, which exhibits the lowest VaR, emerges as the most effective, providing substantial protection against adverse weather conditions. This research supports the notion that weather derivatives can substantially contribute to the economic sustainability of rural economies, influencing policy decisions toward enhancing financial instruments for risk management in agriculture.

A Sustainable Approach Based on Sheep Wool Mulch and Soil Conditioner for Prunus domestica (Stanley Variety) Trees Aimed at Increasing Fruit Quality and Productivity in Drought Conditions

In the context of extreme climate change, experts in fruit production face a significant challenge in developing new strategies aimed at increasing the productivity of fruit tree crops. In order to investigate the changes in various horticultural indices (production, tree growth, and development) as well as the quality of plum fruits, sheep’s wool mulch, a cornstarch-based soil conditioner, and a combination of the two were applied in a Stanley plum orchard. In parallel, an experimental control variation was used. The results showed that the methods used had a substantial impact on fruit yield, size, and weight, with the best results obtained when mulching with sheep’s wool and soil conditioner. Plum fruits from mulching with sheep wool + soil conditioner exhibited the greatest total phenol concentration (1.30 ± 0.09 mg GAE/g dw), followed by the reference sample at 1.16 ± 0.09 mg GAE/g dw. The antioxidant capacity assessed using the three different methods provided favorable results for the experimental variant, sheep wool + soil conditioner. The results indicate that using the three experimental versions increased the fruit yield with 27% (sheep’s wool mulch) and with, 37% (sheep wool + soil conditioner) on average compared to that of the control group, while also improving the fruit quality. The fruit weight increased with 17.26% (cornstarch-based soil conditioner) and with 48.90% (sheep wool + soil conditioner) compared to that of the control, and the fruit size increased with 5% in two experiments (sheep’s wool mulch and a cornstarch-based soil conditioner) with 19% (sheep wool + soil conditioner), compared to the control group.

Children's perceptions shape primate conservation message in rural communities of the Barú District, Southwestern Panama.

Panama is a habitat for nine primate species, and most of them are threatened. This has shown a fundamental concern in primate conservation by Panamanian-based conservation projects. Among them is the project Conservación del Mono Cariblanco en Agroecosistemas (COMOCA) which initiated a primate conservation education program in Southwestern Panama in 2022. The first stage of this program consisted of evaluating the perceptions that 102 children aged 8-12 years old have about primate habitat. Ianalyzed drawings made by these children exploring three different themes: (1) description of primate species, (2) primate habitat, and (3) food related to primates. The results indicate that children are more familiar with the white-faced capuchins and squirrel monkeys. Despite 89.2% of the children drawing trees, most of them painted tree crops. Thus, the top three most mentioned foods eaten by monkeys were mango, plantain/banana, and apple. These findings highlight the importance of addressing the relationship between primates and native trees in the content of the conservation education program. Additionally, the study illustrates how children's depiction of their reality has implications for the management of human-primate interfaces.

Sub-national scale mapping of individual olive trees integrating Earth observation and deep learning

The olive tree holds great cultural, environmental, and economic significance in the Mediterranean region. In particular, Morocco has been making dedicated investments over $10 billion since 2008 to fuel the transition from cereal to olive production. Understanding the spatial extent of this large-scale land conversion is critical for a variety of socioeconomic purposes. In response to this demand, we conducted a study to map individual olive trees in northern Morocco using satellite imagery and deep learning techniques at a sub-national scale. This study utilized cloud-free, very-high-resolution DigitalGlobe imagery collected between 2018 and 2022 to identify each individual olive tree in six northern Morocco provinces. We compared various deep learning models, including both transformer-based and CNN-based models, to generate patch-level spatial constraints and pixel-level tree identification. We found that transformer-based models outperformed CNN-based models in both tasks. Additionally, spatially constraining the pixel-level results improved olive tree mapping accuracy to varying degrees, depending on the initial performance of the model. The evaluation of the olive map generated from this study shows high accuracy in both surveyed and unsampled regions. This research represents the first-of-its-kind individual olive tree mapping at the sub-national scale that can help monitor the large-scale land conversions such as about 110,000 ha of olive plantings in the six Moroccan provinces studies here. Meanwhile it demonstrates a cost-effective and efficient prototype approach that can be adapted to identify similar tree crop expansion occurring in other parts of the world.

Sensory quality of coffee (Coffea arabica L.): Influence of tree diversity and harvest segmentation in agroforestry systems

Coffee (Coffea arabica L.) is a globally important agricultural crop with increasing quality requirements. However, the challenges posed by climate change impact cup quality. Therefore, the objective was to evaluate the influence of tree diversity and crop segmentation under agroforestry systems on the sensory characteristics of coffee. The study employed a 4A*3B factorial design, with factor A: agroforestry systems (mixed system, shade-free system, system with Erythrina edulis and system with Inga edulis) and factor B: segmented harvest (upper, middle, and lower third cherries). Fragrance/aroma, flavor, residual flavor, acidity, body, uniformity, balance, clean cup, sweetness, cupper's score, and final score were evaluated. The results suggest that coffee trees planted in mixed systems provide the best sensory characteristics of coffee in the cup since the highest averages were obtained in most of the variables evaluated. Likewise, it is concluded that the diversity of trees (mixed system and system with Erythrina edulis) has a positive influence on the sensory quality of the coffee, reaching a score of 82.86 and 82.64 for the mixed system and the system with Erythrina edulis respectively; categorizing them as specialty coffees. Agroforestry systems constitute an option for developing sustainable agriculture while improving the sensory quality of coffee in the Peruvian Amazon.

MULTIVARIATE PROBIT MODELING OF CLIMATE-SMART ADAPTATION CHOICES AMONG FARMERS IN SUB-SAHARAN AFRICA: GHANAIAN STUDY OF COCOA FARMERS

Climate change and variability pose significant challenges to cocoa production in many sub-Saharan African countries, and Ghana is no exception. Therefore, knowledge of how farmers react to climate change and its variability effects is crucial in developing policies and programs to guide the design and implementation of effective climate-smart adaptation strategies at the farm level in Africa. This study aims to examine climate-smart adaptation choices cocoa farmers make as coping strategies for climate change and variability in Ghana using a multivariate probit modeling approach. Following a multistage sampling procedure, primary data was collected from 720 cocoa farmers across the major cocoa-growing regions in Ghana. The study found major adaptation choices for cocoa farmers to include improved and resistant varieties, optimal fertilizer application, optimal pesticide application, adjusting planting/harvesting dates, shade tree management, crop diversification, non-crop diversification, and off-farm economic diversification. We further observed that farmers’ adaptation choices were significantly influenced by climate change and adaptation-related variables such as rainfall variability index, temperature variability index, climate change impact perception index, and CSA awareness as well as agroclimatic zone effects. Concerning the influence of farmer and farm-specific variables, the study identifies that sex, age, education, farm size, quality of extension services delivery, access to credit, and membership in farmer groups were significant predictors of farmers’ CSA decision choices. This study offers beneficial insights for policymakers and stakeholders on how to promote climate-smart adaptation methods among cocoa farmers in Ghana.

Multistoried woodlot based agroforestry system for improved resource utilization and incomes for farmer

Diversification of cropping pattern coupled with the development of suitable technology packages is crucial to meet the ever-increasing demand for diversified products and sustained farmers’ incomes. We evaluated different woodlot-based multistoried agroforestry systems for their effectiveness to mitigate the devastating effects of climate change by offering multifaceted benefits. Specifically, the present study aimed to assess the yield and probability of woodlot based multistoried agroforestry system with two vegetables, i.e., potato and brinjal during the period of 2019–2020. The vegetables were planted on the floor of the orchard where pineapple were planted in the same row with the trees. The experiment was laid out in a Randomized Complete Block Design (RCBD) with three replications. The results revealed that the upper-storied woody plants and sole vegetables received 100 % Photosynthetically Active Radiation (PAR) but incident light gradually decreased for brinjal and potato, which were grown at the floor of woody trees. The vegetables experienced 55.85(T3), 60.70(T2), 66.38(T1), and 100 (T4) % PAR under different tree crop combinations respectively. In both cases the highest BCR (3.75) and (3.09) was obtained in the ghoraneem + pineapple based multistoried agroforestry system for potato and brinjal production, respectively, which may considered as the best technique for higher production, crop diversification, and maximization of land use efficiency.

Transcriptome and weighted gene co-expression network analyses reveal key genes and pathways involved in early fruit ripening in Citrus sinensis

BackgroundThe fruit ripening period is an important target trait in fruit tree crop breeding programs. Thus, citrus tree breeders seek to develop extreme early ripening cultivars that allow optimization of citrus maturation periods. In this study, we explored the regulatory network involved in fruit ripening in Citrus sinensis using the ‘Newhall’ navel orange variety and its early-ripening mutant, ‘Gannanzao’. This research will provide a basis for further research on important signaling pathways, gene functions and variety breeding of Citrus sinensis related to fruit ripening period.ResultsPhysiological analyses suggested that early fruit ripening in ‘Gannanzao’ is regulated by early accumulation of abscisic acid (ABA), persistently high levels of jasmonic acid (JA), and higher sucrose content in the pericarp. Pericarp samples from ‘Gannanzao’ and ‘Newhall’ navel oranges were sampled for RNA sequencing analysis at 180, 200, and 220 days after flowering; 1430 differentially expressed genes (DEGs) were identified. Functional enrichment analysis indicated that these DEGs were mainly enriched in the plant hormone signal transduction and sugar metabolism pathways, as well as other pathways related to fruit ripening. Important DEGs associated with fruit ripening in ‘Gannanzao’ included genes involved in ABA and JA metabolism and signal transduction, as well as sugar metabolism. Weighted gene co-expression network analysis showed that the deep pink module had the strongest correlations with ABA content, JA content, and early ripening. Based on gene functionality and gene expression analyses of 37 genes in this module, two candidate hub genes and two ethylene response factor 13 (ERF13) genes (Cs_ont_5g000690 and Cs_ont_5g000700) were identified as key genes regulated by ABA and JA signaling. These findings will help to clarify the mechanisms that underlie early citrus fruit ripening and will lead to the development of excellent genetic resources for further breeding of extreme early-ripening varieties.ConclusionsThrough analyses of the ‘Newhall’ navel orange cultivar and its early-ripening mutant ‘Gannanzao’, we identified genes involved in ABA and JA metabolism, signal transduction, and sugar metabolism that were related to fruit ripening. Among these, two ERF13 genes were inferred to be key genes in the regulation of fruit ripening. These findings provide insights into the genetic architecture related to early fruit ripening in C. sinensis.

Growth and Yield of Okra (<i>Abelmoschus esculentus</i> (L.) Moench) as Affected by Weeding Regimes in Mubi, Adamawa State

The two-year experiments were conducted to evaluate the effect of weeding regimes on the growth and yield of okra (Abelmoschus esculentus L. Moench) in Mubi Adamawa State, Northern Guinea Savannah, grown at the Tree Crop Plantation (TCP) Farm, School of Agriculture, Federal polytechnic, Mubi, during 2022 and 2023 rain cropping season. Mubi is located in the North-eastern part of Adamawa State laid between Latitude 90 26ʹ and100 10ʹN and Longitude 130 10ʹ and 130 44ʹE. at an Altitude of 696m above sea level. The experiments were laid out in Split Plot Design with four (4) treatments: No weeding (W1), 1 Weeding at 3 weeks after sowing (WAS) (W2), 2 weeding at 3, and 6 WAS (W3) and 3 weeding at 3, 6 and 9 WAS (W4), replicated 3 times. Data were collected on plant height, Number of leaves, stem diameter, days to 50 % flowering, fruit length, fruit diameter, fresh fruit yield per plot, fresh fruit yield per hectare and dried fruit yield per hectare. The data on growth and yield parameters were subjected to analysis of variance (ANOVA) using Statistical Analysis System (SAS), (SAS, 2000) and means that showed significant differences were separated by F-test using Duncan Multiple Range Test (DMRT). The results revealed that weeding regimes significantly influenced plant height, number of leaves, and stem diameter, at 3, 6 and 9 WAS. On the response of phonological traits and yield components of okra, to weeding regimes and significant influences were observed in days to 50 % flowering, fruit length, fruit diameter, fresh fruit yield per plot, fresh fruit yield per hectare and dried fruit yield per hectare, accordingly. Treatment W4 performed significantly higher than the other treatments. The study therefore recommends 3 times weeding at an interval of 3 WAS to okra farmers in Mubi and its environs for optimum fruit yield.

Identifying the Traditional and Existing Tree–Crop Combination of Agroforestry System in Southern Part of Chhattisgarh, India

The present study was conducted in Bastar district of Chhattisgarh to identify the traditional and existing agroforestry practices used by farmers. The data were collected through survey of field visits and filled out of pre-prepared questionnaires in four blocks of Bastar district, namely Jagdalpur, Bastar, Tokapal and Bakawand. The survey revealed six different types of agroforestry system practices i.e., agrisilvihorticulture, agrisilviculture, silvihorticulture, agrisilvipastoral, silvihortipastoral, and agrisilvihortipastoral. Among these, 67% of farmers were practiced agrisilvihorticulture-type agroforestry systems. Farmers in Bastar were found to use 29 different tree crops, 17 horticultural crops, 20 vegetable crops, and 11 agricultural crops in their fields.

Unraveling the difference of sensitivity to ozone between non-hybrid native poplar and hybrid poplar clones: A flux-based dose-response analysis

Poplars are economically important tree crops and biologically important model plants, which are known to be sensitive to ozone (O3). Although surface O3 is considered as a significant global environmental issue because of its phytotoxicity and greenhouse effect, the knowledge of the dose-response (DR) relationships in poplars for the assessment of O3 risk is still limited. Hence, this study aimed at collecting data of studies with manipulative O3 exposures of poplars within FACE (Free Air Concentration Enhancement) and OTC (Open-Top Chamber) facilities. The datasets contain studies on hybrid poplar clones and a non-hybrid native poplar (Populus nigra L.) reporting both AOT40 (Accumulated exposure Over a Threshold of 40 ppb) and POD1 (Phytotoxic Ozone Dose above a threshold of 1 nmol m−2 Projected Leaf Area [PLA] s−1) to compare exposure- and flux-based indices. As a result, linear regression analysis showed that the flux-based POD1 was better than the exposure-based AOT40 to explain the biomass response of poplars to O3. From the DR relationships, a critical level (CL) of 5.7 mmol m−2 POD1 has been derived corresponding to 4% biomass growth reduction for hybrid poplar clones, which can be considered very sensitive to O3, while the non-hybrid native poplar was less sensitive to O3 (CL: 10.3 mmol m−2 POD1), although the potential risk of O3 for this taxon is still high due to very high stomatal conductance. Moreover, the different experimental settings (OTC vs. FACE) have affected the AOT40-based DR relationships but not the POD1-based DR relationships, suggesting that poplar responses to O3 were principally explained by stomatal O3 uptake regardless of the different experimental settings and exposure patterns. These results highlight the importance of the flux-based approach, especially when scaling up from experimental datasets to the O3 risk assessment for poplars at the regional or global scale.