Plants In Plots Research Articles

Pre-Harvest Corn Grain Moisture Estimation Using Aerial Multispectral Imagery and Machine Learning Techniques

Corn grain moisture (CGM) is critical to estimate grain maturity status and schedule harvest. Traditional methods for determining CGM range from manual scouting, destructive laboratory analyses, and weather-based dry down estimates. Such methods are either time consuming, expensive, spatially inaccurate, or subjective, therefore they are prone to errors or limitations. Realizing that precision harvest management could be critical for extracting the maximum crop value, this study evaluates the estimation of CGM at a pre-harvest stage using high-resolution (1.3 cm/pixel) multispectral imagery and machine learning techniques. Aerial imagery data were collected in the 2022 cropping season over 116 experimental corn planted plots. A total of 24 vegetation indices (VIs) were derived from imagery data along with reflectance (REF) information in the blue, green, red, red-edge, and near-infrared imaging spectrum that was initially evaluated for inter-correlations as well as subject to principal component analysis (PCA). VIs including the Green Normalized Difference Index (GNDVI), Green Chlorophyll Index (GCI), Infrared Percentage Vegetation Index (IPVI), Simple Ratio Index (SR), Normalized Difference Red-Edge Index (NDRE), and Visible Atmospherically Resistant Index (VARI) had the highest correlations with CGM (r: 0.68–0.80). Next, two state-of-the-art statistical and four machine learning (ML) models (Stepwise Linear Regression (SLR), Partial Least Squares Regression (PLSR), Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbor (KNN)), and their 120 derivates (six ML models × two input groups (REFs and REFs+VIs) × 10 train–test data split ratios (starting 50:50)) were formulated and evaluated for CGM estimation. The CGM estimation accuracy was impacted by the ML model and train-test data split ratio. However, the impact was not significant for the input groups. For validation over the train and entire dataset, RF performed the best at a 95:5 split ratio, and REFs+VIs as the input variables (rtrain: 0.97, rRMSEtrain: 1.17%, rentire: 0.95, rRMSEentire: 1.37%). However, when validated for the test dataset, an increase in the train–test split ratio decreased the performances of the other ML models where SVM performed the best at a 50:50 split ratio (r = 0.70, rRMSE = 2.58%) and with REFs+VIs as the input variables. The 95:5 train–test ratio showed the best performance across all the models, which may be a suitable ratio for relatively smaller or medium-sized datasets. RF was identified to be the most stable and consistent ML model (r: 0.95, rRMSE: 1.37%). Findings in the study indicate that the integration of aerial remote sensing and ML-based data-run techniques could be useful for reliably predicting CGM at the pre-harvest stage, and developing precision corn harvest scheduling and management strategies for the growers.

Tree Crown Affects Biomass Allocation and Its Response to Site Conditions and the Density of Platycladus orientalis Linnaeus Plantation

Tree crown plays a crucial role in the process of photosynthesis and the formation of biomass. The site conditions and stand density have a significant impact on tree and crown growth, as well as biomass formation. Understanding crown growth and its influence on the allometric growth of the biomass of various organs under diverse site conditions and densities is critical to comprehending forest adaptation to climate change and management. This study examined the growth of trees, crown, and biomass in 36 plots of young Platycladus orientalis plantations across three site conditions (S1: thin soil on the sunny slope; S2: thick soil on the sunny slope; S3: thin soil on the shady slope) and four densities (D1: ≤1500 plants/hm2; D2: 1501–2000 plants/hm2; D3: 2001–3000 plants/hm2; and D4: ≥3001 plants/hm2). The findings of this study showed that S3 demonstrated the best tree growth, with considerably higher DBH and V than S1 and S2. In addition, as the number of trees grew, the average diameter at breast height (DBH), height (H), and volume (V) all decreased greatly. Poor site (S1) suppressed the canopy, decreasing crown width (CW), crown length (CL), crown ratio (CR), crown surface area (CCSA), and crown volume (CCV), while increasing crown efficiency (CEFF). This same trend was seen in D4, where CR, CCSA, and CCV were all much smaller than the other densities, but CEFF was the highest. Subjective and objective indicators were less responsive to changes in crown growth than crown composite indicators like CCSA, CCV, CEFF, and CR. Site condition and density had a major impact on biomass accumulation, with S1 and D4 having a much lower biomass than S2, S3, D1, D2, and D3. More biomass was allocated to the stem in S3 and D1, and more biomass was allocated to branches and leaves in S2, S3, D1, D2, and D3, resulting in a nearly isotropic growth of branches and leaves. The effect of crown indicators on the biomass of each organ varied according to site condition and density. In varied site conditions, crown and DBH ratio (RCD) contributed the most to stem biomass, whereas CL contributed the most to branch and root biomass. CL had the largest effect on biomass accumulation at various densities. This study demonstrates how site condition and density affect tree and crown development and biomass accumulation, providing theoretical guidance for plantation management under climate change.

Influence of stand and environmental factors on forest productivity of Platycladus orientalis plantations in Beijing’s mountainous areas

The purpose of forest management is to establish a forest ecosystem with multifunction in Beijing’s mountainous areas, and the priority is to increase forest productivity aiming to achieve carbon neutrality. In this study, we investigated 62 sample plots of Platycladus orientalis plantations and compared the relative contributions of stand and environmental factors to forest productivity by using variance partitioning analysis, the direct and indirect effects of these factors were explored by using structural equation model. And the geographical distribution of areas with higher forest productivity of Platycladus orientalis plantations was simulated and the contributions of these factors to the greater productivity was analyzed by using maximum entropy model (MaxEnt). The results indicated that topography was the dominant factors affecting the forest productivity of Platycladus orientalis plantations, followed by stand and soil nutrient factors. The results of structural equation model indicated that both topography and stand factors not only directly affect forest productivity, but also indirectly affect it by influencing soil nutrients. Soil nutrients had only direct impact on forest productivity. Forest productivity of Platycladus orientalis plantations was higher in areas with low altitude (168–252 m), gentle slopes (5–13 degrees), sunny slopes or semi-sunny slopes, soil total nitrogen content (>1.5 g/kg), and soil organic matter content (>38 g/kg). By changing the slopes to 5–13 degrees, increasing soil total nitrogen content to 1.5 g/kg and soil organic matter content to 38 g/kg, the average existence probability of higher forest productivity areas increased from 0.32 to 0.46, and amount of areas with higher productivity will be increased by approximately 43.8 %.

Site Factors Related to Dry Farm Vegetable Productivity and Quality in the Willamette Valley of Oregon

Dry farming has been defined as rainfed crop production in a climate with more than 20 inches of annual precipitation, but where most precipitation falls outside the growing season. Dry farming is garnering interest in the western United States because it allows farmers to produce crops despite a lack of access to irrigation or water rights or to eliminate the infrastructure, labor, and energy costs of irrigation systems. Sites have differing suitability for dry farming, and some sites that can be farmed with irrigation will perform poorly when dry-farmed. To determine site factors associated with dry farm yield and fruit quality, trials of ‘Early Girl’ tomato (Solanum lycopersicum) and ‘North Georgia Candy Roaster’ winter squash (Cucurbita maxima) were conducted at 17 participant farms in the Willamette Valley in Oregon, USA, in 2018 and 2019. The mean blossom-end rot (BER) incidence was higher in the Willamette Valley than in coastal California; this was probably because of the Willamette Valley’s hotter and drier climate. Increasing the available water-holding capacity of soil, total available water (available water-holding capacity of the soil plus in-season rainfall), native productivity rating, soil pH (0–6 inches and 24–36 inches), soil nutrient concentrations (0–6 inches and 24–36 inches), and in-season rainfall were positively associated with at least one measure of tomato or winter squash yield, fruit number, or average fruit weight. An earlier planting date was positively associated with winter squash total yield and total fruit number in 2019. The water-limited yield potential (the total yield potential if water was the only limiting factor) for 20-ft2/plant plots was estimated to be 2.2 tons/acre per inch for tomato and 2.8 tons/acre per inch for winter squash. In 2019, high-density plantings (20 ft2/plant) had higher tomato and winter squash mean total yields, mean total fruit numbers, and mean tomato unblemished yield than low-density plantings (40 ft2/plant). In 2019, planting tomato at 20 ft2/plant decreased the mean BER incidence by 15.6% when compared with planting tomato at 40 ft2/plant.

Integrating extraction framework and methods of individual tree parameters based on close-range photogrammetry

The forest plots survey's primary measurement factors are the diameter at breast height (DBH), tree height, and the individual tree volume. The reconstruction of a 3D forest scene based on dense images can contribute to the automatic extraction of individual tree parameters. Close-range photogrammetry (CRP) can achieve the reconstruction of a 3D scene from the sequence images at a highly efficient and low cost. However, the reconstructed point clouds often miss the trees' upper part, resulting in the tree height and volume not being measured directly. This paper proposes an integrating extraction framework and methods of the DBH, tree height, and individual tree volume for achieving automatic measurement of the individual tree parameters with high accuracy based on CRP. Four plantation plots in Wangyedian Forest Farm, Inner Mongolia, and Gaofeng Forest Farm, Guangxi Zhuang, are selected to obtain sequence close-up photographs and construct 3D scenes. The DBH, tree height, and trunk volume of the individual tree are extracted using circle fitting, stem curve fitting, growth equation, and segmentation measurement. The extracted individual tree parameters from Terrestrial laser scanning (TLS) are used as validation data to evaluate the accuracy. It shows a good performance in two Larix gmelinii plots, one Pinus tabulaeformis plot, and one Eucalyptus grandis plot with the accuracy of extracted DBH above 90%, which is 90.18%, 96.54%, 90.17%, and 95.00%, respectively. The accuracy of extracted tree height of the four plots is all above 85%, which is 93.34%, 91.71%, 90.32%, and 85.96%, respectively, and the accuracy of trunk volume is 91.55%, 91.94%, 89.86%, and 89.6%, respectively. The results show that our proposed integrated parameter extraction frame and methods can achieve high accuracy economically, efficiently, and conveniently, and be used for automatic measurements of individual tree factors in forest plot surveys.

Changes in Genotype Composition and Morphology at an Experimental Site of Common Reed (Phragmites australis) Over a Quarter of a Century

The cultivation of common reed (Phragmites australis) is one of the most promising practices of paludiculture on fen peatlands. This highly productive grass has a high adaptation capacity via high levels of genetic diversity and phenotypic plasticity. In this study, a reed experimental site established on a degraded fen in 1996/97 with a mixture of monoclonally (meristematically propagated plantlets) and polyclonally (pre-grown seedlings) planted plots was investigated by microsatellite genotyping. All nine genotypes of the monoclonal planted plots were recovered and could be genetically characterized; invasion by other genotypes was negligible. Similarly, the polyclonal plots sustained high clonal diversity with no prevalence of a single genotype. The growth characteristics of the five quantitatively investigated genotypes significantly differed from each other (α = 0.05): dry biomass per stem 5–18 g, panicles per m2 20–60, average stem diameter 3.5–6 mm, height 170–250 cm. Similarly, the persistence of genotypes at the planted plots and their invasiveness (ability to invade neighboured plots) varied. These results show that common reed stands are extremely persistent even if established with genotypes that are likely not to be locally adapted. Their genetic structure remained stable for at least 24 years regardless of the planting density (1, 4, and 10 plants per m2). Our results indicate that farmers may be able to maintain favourable genotypes for many years, thus the selection and breeding of common reed as a versatile crop for rewetted peatlands is a promising objective for paludiculture research.

The green economy as plantation ecology: When dehumanization and ecological simplification go 'green

The green economy is proposed as a solution to address growing and potentially irreversible ecological crises. But what happens when environmental solutions are premised on the same logics of brutal simplification and dehumanization that sustain and reinforce systems of oppression and ecological breakdown? In this article, we describe the transformation of the biophysical landscape of the planet into replicable blueprints of the plantation plot. The plantation as a colonial-era organizational template is an ongoing ecological process premised on disciplining bodies and landscapes into efficient, predictable, calculable, and controllable plots to optimize commodity production and is dependent on racialized and gendered processes of dehumanization. The visible cultural, physical, aesthetic, and political singularity of the plot, under the guise of objectivity and neutrality, permits a tangible depiction of the way ecological breakdown takes place. We interrogate the notion of "greening" as a strategy to combat the unintended impacts of colonial plantation ecology, arguing that such tactics further reinforce the template of plantation ecology rather than dismantle it. We first conceptualize the historical plantation and its biophysical, cognitive, and corporeal organizational principles. We then offer examples of "greening" as new, more inclusive (but equally detrimental) forms of plantation logics, and crucially identify how these extensions of plantation logic get co-opted by resistance agents, from social movements to disease and pestilence. We consider sustainability certifications of palm oil through the Roundtable on Sustainable Palm Oil (RSPO) in Colombia and compensatory afforestation programs designed to offset forest destruction through monoculture plantations in India. We conclude by highlighting how abolition ecologies can serve as an antidote to plantation logic and highlight necessary relationships of self-reflexivity, repair and collective solidarity required to disinvest in plantation ecology.

Stability and Spatial Structure of Chinese Pine (Pinus tabuliformis Carr.) Plantations in Loess Hilly Region: A Case Study from Huanglong Mountain

In contrast to intensive management practices focused on wood production, plantations designed to safeguard fragile environments prioritize the sustainable fulfillment of ecological functions. To assess the potential for Chinese pine (Pinus tabuliformis Carr.) plantations in the Loess Hilly Region to effectively serve their ecological protection role over the long term, we selected nine indices representing biological stability, resistance stability, and functional stability. Employing a novel unit circle method, we evaluated the total stability (sum of the three stability components) of 44 plantation plots in Huanglong Mountain. We also explored the connections between total stability and standing spatial structure parameters to offer insights for promptly enhancing stability through thinning. The findings revealed that 79.5% of Chinese pine plantations exhibited moderate total stability, with 20.5% demonstrating good stability. Most plots displayed a random distribution pattern, moderate size differentiation, low species spatial mixing, and high stand crowding. Among the correlations analyzed, mingling exhibited the highest coefficient, followed by differentiation, while the uniform angle index showed the weakest correlation, and crowding displayed an insignificant correlation. While the presence of good functional stability contributed to the moderate total stability, addressing inadequate biological and resistance stability necessitates thinning measures. This study identifies spatial structure types negatively linked to total stability, offering targeted management insights for enhancing the stability of Chinese pine plantations. The stability assessment methodology and indicators presented in this study can serve as a valuable reference for similar plantations with comparable functions and planting conditions.

Soil water dynamics and biomass production of young rooibos (Aspalathus linearis) plants

Rooibos (Aspalathus linearis) is endemic to certain regions of the Western- and Northern Cape of South Africa, where it is also commercially grown. Being low-rainfall regions, information on the soil water balance of rooibos is essential, but such data is limited. Consequently, the effect of inorganic fertilisation and soil depth on soil water dynamics in a young rooibos plantation at Nardouwsberg, Western Cape were studied. Soil water content of plots planted to unfertilised and fertilised plants as well as that of bare soil were determined over the duration of the 2016/17 season. All treatments were replicated on shallow and deep soils sites and plant growth was determined at the end of the season. At the end of the study, the profile soil water content and evapotranspiration of the bare and planted plots were similar which prove that fallowing (water harvesting) is not an option in the sandy soils of this region. With the exception of the 20−30 cm root zone of the planted plots at the deep site, the water content decreased to levels below the permanent wilting point in the soil profile during summer. It was concluded that rooibos plants could survive through an adapted root system. A further survival method was proposed, involving moisture moved through evaporation from the deeper soil layers into the drying-front in the ~ 10−30 cm soil layer where a condensation-evaporation cycle enables rooibos to harvest small amounts of water. The highest shoot biomass with the longest taproot resulted from the unfertilised treatment on the deep soil thanks to higher soil water content, whereas the shoot and root biomass of the fertilised treatment at both sites were low due to high P soil concentration. This study revealed that unfertilised plants on deeper soils result in higher rooibos production under drought conditions.

Ex-Ante Co-Benefit of Orchard Cropping as Climate Resilient Agriculture Practice in Drought Prone Area, Jalna District, Maharashtra, India

A Project on Climate Resilient Agriculture (PoCRA) in drought prone regions of Maharashtra is intending to increase farm productivity and income of small land holding farmers. Horticulture plantation activity under project is one of climate resilient agriculture practice supported by PoCRA. About 93 farm plots of horticulture plantation and its co-benefits in Jalna district of Maharashtra have studied. A biomass estimation method was used for the measure of carbon sequestration. This method is essentially requiring plant density, height and girth diameter. It has observed that larger the plant biomass highest will be the carbon sequestered. Also, the number of plants per hectare has impact on biomass accounting. As per the observations, study shows highest to lowest carbon sequestration in plants in following order Pomegranate > Sweet lime > Mango > Guava > Custard apple i.e., respectively 66.38, 65.11, 33.24, 25.68 and 14.9 Kg of carbon sequestered per plant per year. This study primarily focuses on potential of carbon sequestration of horticulture plantation and ex-ante co-benefits in conservation of soil, water, nutrient. From the (PoCRA project) data it has observed that about 2215 ha of land is under fruit crop plantation (till September 2021) sequestering about 52,473.35 tons of CO2 per year. Also, it is expected that soil is conserve directly at these 2215 ha of orchard plantation plots, and 50% area covering drip irrigation conserve the water and nutrient, figured through farmer’s application on portal i.e., for both drip irrigation and plantation. Therefore, it is benefitting farmers economically and sequestering carbon and conserving environment as co-benefit.

Determination in Forage Yield and Quality of Chicory and Different Plants Mixtures in Grazing Maturity Period

This study was conducted to determine forage yield and quality of chicory (Cichorium inthybus L.) in a pure stand and a simple pasture (two-species) in the grazing maturity period. The experiment design was a Randomized Block Design with 3 replications. The experimental site was located on the grounds of the Ondokuz Mayıs University Agricultural Faculty during the 2017 and 2018 growing periods. In this study, chicory (C), orchardgrass (OG), and red clover (RC) were grown as forage plant materials in a rainfed cropping system in North Türkiye. Simple pastures comprised of 80%C + 20%OG, 60%C +40%OG, 40%C + 60%OG, 20%C + 80%OG, 80%C + 20%RC, 60%C + 40%RC, 40%C + 60%RC, 20%C + 80%RC. Five sequential harvests were made when chicory plants reached 25 cm of plant height in both years. The average plant height ranged from 17.3 to 35.6 cm, and 29.1 to 38.3 cm in 2017 and 2018 respectively. The highest fresh forage yield was determined in red clover mixtures (6519-5443 kg/da) in 2017 and 80%C+20%RC mixture (as 7137 kg/da) in 2018. Total dry matter production was ranged from 216 to 1238 and 279 to 1164 kg/da in 2017 and 2018, respectively. In pure stand chicory pasture, dry matter production was evaluated 216 kg/da in 2017 and 908 kg/da in 2018. Considering the calculated area equivalence ratios (LER) of mixed planting plots in both years and in all forms, it was determined that all mixtures were superior to plain plantings (LER≥1).

Decision-Tree Application to Predict and Spatialize the Wood Productivity Probabilities of Eucalyptus Plantations

Brazil is one of the world’s wood short-fiber producers, cultivating 7.5 million hectares of eucalypt trees. Foresters and resource managers often face difficulties in surveying reliable Eucalyptus productivity levels for the purpose of purchasing and prospecting lands. Spatial data science (DS) and machine learning (ML) provide powerful approaches to make the best use of the large datasets available today. Agriculture has made great use of these approaches, and in this paper, we explore how forestry can benefit as well. We hypothesized that both DS and ML techniques can be used to improve Eucalyptus productivity zoning based on multiple operational datasets of tree growth and environment. Based on more than 12,000 permanent forest inventory plots of commercial Eucalyptus plantations and the climate, soil, and altitude variables associated with them, a supervised ML approach was adjusted to model the forest plantation productivity. A multi-tuning of the decision-tree (DT) algorithm hyperparameters was prepared to yield 450 DT models, with a better one delivering an RMSE of 53.5 m3 ha−1, split in 35 terminal nodes, here interpreted as Eucalyptus productivity zones. The DT model showed an optimum performance index of 0.83, a coefficient of determination of 0.91, a root mean squared error of 12.3 m3 ha−1, and a mean absolute percentage error only of 3.1% in predicting the testing dataset throughout the study area. The DT rule set was interpreted in a user-friendly table and was prepared to classify any location within the study area in each one of the 35 productivity zones based on the required environment variables of the DT algorithm. The high quality of the model obtained made it possible to spatialize the DT rules, providing a reliable cartographic visualization of the probability levels of true Eucalyptus productivity for a huge region of forest-based industries in Brazil. These data-science techniques also provided a yield gap analysis using a very down-to-earth approach. We estimated a yield gap by an amount of 4.2 × 107 m3, representing a few more than 113,000 ha, or 15% of the current forest base. This is the amount of avoided area expansion to accumulate the same wood stock in case the productivity is raised to the attainable level in each zone. This present study provided deeper analysis and reproducible tools to manage forest assets sustainably.

Efficacy of Several Fungicides Against Root Rot Disease (Phytophthora capsici Leonian) on Pepper

Root rot disease caused by the fungus Phytophthora capsici can cause up to 60% yield loss of pepper in West Kalimantan, which is spread across Singkawang, Bengkayang, Pontianak, Sintang, and Sekadau Regencies. Control of BPB chemically with fungicide is considered to be effective enough to suppress BPB both in vitro and in the field. This study aims to examine the effectiveness of several fungicide active ingredients that are widely used in BPB control, namely Chlorotalonil, Azoxystrobin, Mankozeb, and Phosphoric Acid. Efficacy tests were carried out on sample plant plots consisting of 25 sample trees for each treatment of the active ingredient of the fungicide. Fungicide application was carried out 3 times (2-week intervals) within 3 months. BPB attack intensity was calculated to obtain the Efficacy Level (TE) category of the active ingredients used. The fungicide with the active ingredient phosphite acid showed the highest efficacy level of 30.06%, while the active ingredients Azoxystrobin and Mankozeb had TE values of 29.01% and 28.23%, respectively. The lowest result was the function with the active ingredient Chlorotalonil with a TE percentage of only 4.13%.

Forest canopy interception can reduce flood discharge: Inferences from model assumption analysis

Some interception (IC) models assume proportionality between the IC and rainfall amount during heavy rainfall, while others do not. Although differences in the assumptions of the IC model can significantly impact water balance and runoff prediction, quantitative analysis has not yet been conducted. In this study, we investigated the influence of IC model selection on runoff prediction and its parameter estimation in aforested catchment in Japan. First, an IC model was presented as a function that can continuously represent the case where the IC increases with rainfall but asymptotically reaches a flat plateau and the case where IC is completely proportional to rainfall. The IC estimation using the model was compared with the IC data observed in 2020–2021 at three coniferous plantation plots within the catchment. Second, the IC model was incorporated into a catchment-scale water balance model (TOPMODEL-based tank model), and then the IC model that optimally reproduced the runoff observed in 2010–2015 was determined. The results showed that the observed IC and runoff were optimally reproduced when the IC was completely proportional to rainfall. However, it was observed that the assumption of the IC was not as influential on runoff predictability as the water retention capacity parameter of the catchment water balance model. Meanwhile, once the appropriate water retention capacity parameter was fixed, the impact of the difference in IC models on runoff prediction was significant at high-flow periods. Moreover, estimated high flow became large without the assumption that the IC was somehow proportional to rainfall, suggesting the importance of adequately representing the occurrence of IC, especially during heavy rainfall events. This implies that the IC by the forest canopy plays a significant role in controlling flood discharge from forested watersheds.

Program Bina Desa Pengembangan Peternakan Kambing di Kelurahan Anggoeya Kecamatan Poasia Kota Kendari

This village development program aims to increase the knowledge and skills of breeders in optimizing the utilization of the economic potential of goat livestock production in the Anggoeya Village, Poasia District, Kendari City. The implementation of the village development program uses a participatory method through several stages of activity, namely program socialization and FGD, demonstration of forage planting plots for livestock, feed processing, and composting using goat manure. The results of the implementation of the village development program show that goat breeders are very enthusiastic about participating in all stages of the activity and can feel the benefits of this community service program in the form of additional goat husbandry knowledge and technology. Goat farmers now have forage gardens using quality Odot grass seeds as a solution for providing the sustainable feed. In addition, goat breeders can provide goat feed by making silage using agricultural waste such as banana cobs and straw from other plants. Goat farmers can also produce compost using good quality goat manure which is useful for fertilizing forage crops, developed and or sold as a supplement to their income.

Floral presence and flower identity alter cereal aphid endosymbiont communities on adjacent crops.

Floral plantings adjacent to crops fields can recruit populations of natural enemies by providing flower nectar and non-crop prey to increase natural pest regulation. Observed variation in success rates might be due to changes in the unseen community of endosymbionts hosted by many herbivorous insects, of which some can confer resistance to natural enemies, for example, parasitoid wasps. Reduced insect control may occur if highly protective symbiont combinations increase in frequency via selection effects, and this is expected to be stronger in lower diversity systems.We used a large-scale field trial to analyse the bacterial endosymbiont communities hosted by cereal aphids Sitobion avenae collected along transects into strip plots of barley plants managed by either conventional or integrated (including floral field margins and reduced inputs) methods. In addition, we conducted an outdoor pot experiment to analyse endosymbionts in S. avenae aphids collected on barley plants that were either grown alone or alongside one of three flowering plants, across three time points.In the field, aphids hosted up to four symbionts. The abundance of aphids and parasitoid wasps was reduced towards the middle of all fields while aphid symbiont species richness and diversity decreased into the field in conventional, but not integrated, field-strips. The proportion of aphids hosting different symbiont combinations varied across cropping systems, with distances into the fields, and were correlated with parasitoid wasp abundances.In the pot experiment, aphids hosted up to six symbionts. Flower presence increased natural enemy abundance and diversity, and decreased aphid abundance. The proportion of aphids hosting different symbiont combinations varied across the flower treatment and time, and were correlated with varying abundances of the different specialist parasitoid wasp species recruited by different flowers. Synthesis and applications. Floral plantings and flower identity had community-wide impacts on the combinations of bacterial endosymbionts hosted by herbivorous insects, which correlated with natural enemy diversity and abundance. We recommend that integrated management practices incorporate floral resources within field areas to support a more functionally diverse and resilient natural enemy community to mitigate selection for symbiont-mediated pest resistance throughout the cropping area.

Stand-level habitat characteristics and edge habitats drive biological pest control services in the understory of oil palm plantations

The expansion of oil palm agriculture in the tropics has gone hand in hand with a sharp increase in synthetic pesticide application in the region. Due to associated negative ecological impacts, there is growing pressure on the oil palm industry to reduce chemical usage and revert to natural pest control methods. However, knowledge of the mechanisms that govern how successful natural predators are at controlling pest insect species in the understory of oil palm plantations is scarce. By using an artificial caterpillar bait method this study examines the effectiveness of three animal taxa (i.e., arthropods, birds, and mammals) as within-plantation insect predators. Caterpillars were deployed across three different aged oil palm plantation plots in Selangor, Malaysia. Data for height and coverage of understory vegetation, plot location, elevation, and canopy cover were collected. Of the three taxa studied, mammals were responsible for the highest levels of predation, followed by arthropods and then birds. Arthropod predation was higher at edge locations, in abandoned habitats and in elevated areas. Mammal predation was shown to increase with increasing understory coverage and decrease with increasing elevation. Bird predation was not shown to be associated with any of the habitat quality characteristics studied. We found that overall predation pressure was higher at the edge of plantations compared to within plantation interiors, and that overall predation positively correlated with an increase in understory vegetation coverage. Management strategies that enhance undergrowth coverage and maximise edge habitats have the potential to boost the effectiveness of natural predators in the understory of oil palm plantations.

Rice straw mulch and organic fertilizer effect on growth and production of lettuce (Lactuca sativa L.)

Lettuce is one of the most popular horticultural crops. It is necessary to make an effort to increase lettuce production to meet market demand. One of the efforts is engineering cultivation systems through rice straw mulch and organic fertilizers application. The aims of studied to determine the effect of rice straw mulch and organic fertilizer on growth and production of lettuce. The research was conducted at Nudira Fresh Green House, PT. Nudira Sumber Daya Indonesia, Warnasari Village, Pangalengan Subdistrict, Bandung District, West Java. This study used factorial randomized block design with 3 replications. There were 2 factors with 8 treatment combinations. Factor I was mulch dose: control, 4 t ha−1 rice straw mulch, 6 t ha−1 rice straw mulch, 8 t ha−1 rice straw mulch. Factor II was organic fertilizer types: 20 t ha−1 cow manure, and 20 t ha−1 compost. The results showed that the rice straw mulch dose and organic fertilizer type did not significantly effect on plant height, leaves number, production per plant sample, and production per plant plot. Application of 8 t ha−1 rice straw mulch was able to increase plant height, production per plant sample, and production per plant plot. The cow manure application was able to increase plant height, leaves number, production per plant plot, and production per plant sample compared to using compost.

Effects of Climate on Stand-Level Biomass for Larch Plantations in Heilongjiang Province, Northeast China

Climate change affects forest resource availability, growing season length, and thus forest biomass accumulation. However, only a limited number of studies have been conducted on forest biomass management based on climate effects, particularly at the stand-level. Thus, an allometric biomass equation based on conventional and climate-based stand biomass models, was developed and compared for larch trees (Larix spp.). A total of 160 experimental plots of larch plantations have been collected in Heilongjiang Province, Northeast China. In this study, we developed four types of additive model systems for stand-level biomass: two types of the stand-level biomass basic models (M-1 and M-2) with stand variables (stand basal area (BA) and stand mean height (Hm)) as the predictors, and two types of the proposed stand-level biomass climate-based models (M-3 and M-4) with stand variables (BA and Hm) and climatic variables (mean annual temperature (MAT) and annual precipitation (AP)) as the predictors. Accordingly, this study evaluated the effects of climatic variables (MAT and AP) and stand variables (BA and Hm) on the model’s performance. Model fitting and validation results revealed that the climatic variables significantly improved the model performance of the fitted equation by increasing the coefficient of determination (R2) values and reducing the root mean square error (RMSE) values. A higher R2 and a lower RMSE were consistently generated by M-2 and M-4, whereas M-1 and M-3 consistently generated a lower R2 and a higher RMSE. We found that the proposed stand-level biomass climate-based model type 4 (M-4) performed better than the other models and slightly better than in previous studies of climate-sensitive models. This study provided an additional and beneficial method of analyzing climate effects on stand-level biomass estimation.

The productive performance of soybean genotypes depends on the distribution of plants in the field

This study aims to evaluate the effect of the distribution of plants in the field on the productive performance of soybean genotypes. The test was developed in the field, in two agricultural crops, on a farm located in the District of Monte Bonito - Pelotas (RS, Brazil), in eutrophic haplic planosol soil, with geographic coordinates 31° 40' 27"S and 52°23' 28 "W. The experiment consisted of twelve treatments involving two factors: factor A - 3 soybean genotypes (NA 5909 RR (super early, growth indeterminate and maturation group A), NS 6006 IPRO (high grain weight, growth indeterminate and maturation group B 5.9), and NS 5959 IPRO (precocity, indeterminate growth and maturation group C) and factor B - 4 line spacing (0.17; 0.30; 0.45 and 0.60 meters). The experimental design used was randomized blocks in a factorial scheme (3x4) with four blocks. The plant population used was 330.000 plants ha-1. Five random plants plot, except for grain yield, were evaluated per plot. To evaluate the productive performance the main stem diameter, final plant height, number of branches per plant, number of pods per plant, number of seeds per pod, the weight of a thousand seeds, and yield were measured. Soybean plants better distributed in the cultivation area, in the spacing of 0,17 and 0,30 meters, have higher plant height, stem diameter, and productive performance. The genotypes of soybean performance are influenced by the distribution of plants, and this response depends on the genotype and the production environment