Effect of Planting Date on Yield and Yield Components of Grain Sorghum Hybrids

In Kansas, productivity of grain sorghum [Sorghum bicolor (L.) Moench] is affected by weather conditions at planting and during pollination. Planting date management and selection of hybrid maturity group can help to avoid severe environmental stresses during these sensitive stages. The hypothesis of the study was that late May planting improves grain sorghum yield and yield components compared with late June planting. The objectives of this research were to investigate the influence of planting dates yield and yield components of different grain sorghum hybrids, and to determine the optimal planting date and hybrid combination for maximum biomass and grains production. Three sorghum hybrids (early, medium, and late maturing) were planted in late May and late June without irrigation in Kansas at Manhattan/Ashland Bottom Research Station, and Hutchinson in 2010;and at Manhattan/North Farm and Hutchinson in 2011. Data on dry matter production, yield and yield components were collected. Grain yield and yield components were influenced by planting date depending on environmental conditions. At Manhattan (2010), greater grain yield, number of heads per plant, were obtained with late-June planting compared with late May planting, while at Hutchinson (2010) greater yield was obtained with late May planting for all hybrids. The yield component most affected at Hutchinson was the number of kernels∙panicle−1 and plant density. Late-May planting was favorable for late maturing hybrid (P84G62) in all locations. However, the yield of early maturing hybrid (DKS 28-05) and medium maturing hybrid (DKS 37-07) was less affected by delayed planting. The effects of planting dates on yield and yield components of grain sorghum hybrids were found to be variable among hybrid maturity groups and locations.

Effect of Inorganic and Organic Fertilizers on Growth and Yield of Two Industrial Potato Varieties (Asterix and Courage) in Bangladesh

Potato is one of the most important vegetable crops, which contributes more than half of the total vegetable production in Bangladesh. Four field experiments were conducted in two different locations in Bangladesh to develop integrated nutrient management practices to produce quality potato seed in industrial processing varieties Asterix and Courage. For the inorganic trial, Factorial Randomized Complete Block Design (RCBD) including 2 potato varieties, 5 treatments with 4 replications, and in the organic fertilizer trial, Factorial RCBD including 2 potato varieties, 6 treatments with 4 replications were used. In the inorganic fertilizer trail, the highest yield was obtained in the variety Asterix due to Nitrogen, Phosphorus, Potassium, and Sulfur (NPKS) plus Magnesium treated plot in Domar BADC farm and due to NPKS plus Boron, Zinc, and Magnesium treated plots in Kashimpur Farm. In the case of variety Courage, the highest yield was found in the treatment of NPKS plus Zinc in Domar BADC farm while in Kashimpur farm, NPKS plus Mg treated plots had the highest yield of potato variety-Courage. In the organic fertilizer trail, the highest tuber yield per hill was obtained by applying the government-approved commercial brand Northern organic fertilizer in variety Asterix and by organic fertilizer brand Chook Chook in variety Courage. Parameters such as days to tuber initiation, number of stems per hill, plant height, and number of tubers per hill were found statistically different among the treatments and between the two varieties. Treatments namely Northern organic fertilizer and Cowdung combined with mustard oil cake performed better considering standard grade tuber yield (grade A and B) compared to other treatments. Hence, the combination of NPKS MgZn and either Northern organic or Chook Chook or Cowdung plus mustard oil cake could be used to grow the varieties Asterix and Courage.

The Yield and Diseases-Pest Performance of Breeding Materials for Tomatoes (Lycopersicon esculentum) Sourced from Different Exotic Sources

A study was conducted with 36 tomato germplasm [PGRC (19), The Netherlands (7), Japan (2), and Bangladesh (9)] with 3 check varieties in the research field of the Olericulture Division of Horticulture Research Centre (HRC), Bangladesh Agricultural Research Institute (BARI), Gazipur during the winter season of 2022-23 to identify promising tomato breeding germplasm. All the germplasm showed differences in most of the parameters studied. Considerable variation was observed for fruit yield per hectare varied from 39 to 144 tons, while the highest fruit yield per hectare was harvested from the germplasm viz., BD 7759B, BD 7757, BD 7751, BD 7301, QM, BD 7759A, BD 7762, QF, BD 7753, BD 8886, BD 10351, NL-1A, SLA-19. The number of locules, total soluble solids (TSS) and plant height at last harvest varied from 2 to 6.6, 2.6 to 5.9%, and 66 to 154cm, respectively. The TYLCV infection (%) and leaf-sucking pest infestation (%) were observed with a 1 to 20% range in the field condition in both cases. So, we can select that germplasm has zero per cent infestation. Considering the plant growth habit, earliness, different yield contributing horticultural traits, virus and pest infestation thirteen germplasm viz., BD 7759B, BD 7757, BD 7751, BD 7301, QM, BD 7759A, BD 7762, QF, BD 7753, BD 8886, BD 10351, NL-1A, SLA-19 were selected as breeding materials for further tomato improvement program.

Yield and Nutritive Values of Semi- and Non-Fall Dormant Alfalfa Cultivars under Late-Cutting Schedule in California’s Central Valley

California is one of the major alfalfa (Medicago sativa L) forage-producing states in the U.S, but its production area has decreased significantly in the last couple of decades. Selection of cultivars with high yield and nutritive value under late-cutting schedule strategy may help identify cultivars that growers can use to maximize yield while maintaining area for sustainable alfalfa production, but there is little information on this strategy. A field study was conducted to determine cumulative dry matter (DM) and nutritive values of 20 semi- and non-fall dormant (FD) ratings (FD 7 and FD 8 - 10, respectively) cultivars under 35-day cut in California’s Central Valley in 2020-2022. Seasonal cumulative DM yields ranged from 6.8 in 2020 to 37.0 Mg·ha−1 in 2021. Four FD 8 - 9 cultivars were the highest yielding with 3-yrs avg. DM greater than the lowest yielding lines by 46%. FD 7 cultivar “715RR” produced the highest crude protein (CP: 240 g·Kg−1) while FD 8 cultivar “HVX840RR” resulted in the highest neutral detergent fiber digestibility (NDFD: 484 g·Kg−1, 7% greater than the top yielding cultivars) but with DM yield intermediate. Yields and NDFD correlated positively but weakly indicating some semi- and non-FD cultivars performing similarly. These results suggest that selecting high yielding cultivars under 35-day cutting schedule strategy can be used as a tool to help growers to maximize yield while achieving good quality forages for sustainable alfalfa production in California’s Central Valley.

Effect of Different Mulch Materials on Yield and Nutrition Profile of Common Capsicum (Capsicum annuum) Cultivars in Bangladesh

Capsicum is a nutritious vegetable and its cultivation in farms is getting popular in Bangladesh. Although many efforts have lain to explore better yielding and nutritionally rich cultivars with suitable modern cultivation techniques but still have to find the desired outcome. Thus, it’s necessary to conduct further research to identify the high-yielding and nutritious capsicum cultivars in Bangladesh. An experiment was conducted from July 2021 to June 2022 at the Bangladesh Institute of Research and Training on Applied Nutrition (BIRTAN) research field with three cultivars of capsicum: B0 = California Wonder, B1 = BARI Misti Morich-1 and B2 = BARI Misti Morich-2 and three mulching: T0 = No mulching, T1 = Water hyacinth, T2 = Poly Mulching in randomized complete block design with three replications to identify better quality capsicum cultivar and suitable mulching material. Among cultivars the BARI Misti Morich-2 (B2) showed increased agronomic parameters like number of branches and effective branches per plant, leaves length and width, consequently yield and yield contributing traits were also enhanced like fruits per plant, fruit length, fruit diameter and yield per plant (25.97%, 4.54%, 3.64% and 21.43%, respectively). Poly Mulching (T2) increased agronomic traits, yield traits and yield (0.61 kg) than BARI Misti Morich-1 (T1). The combined effect of B2T2 increased the number of branches per plant, effective branches per plant, leaves length and breadth by 40%, 90%, 15.57% and 26.22%, respectively, hence resulting in an increased yield of 20%. BARI Misti Morich-2 cultivar showed an increase in Fe, Zn and Vitamin-C content of 26.24% and 23.10%, 8.82% and 5.14%, and 6.03% and 5.74% than B0 and B1 cultivars, respectively. Therefore, BARI Misti Morich-2 exhibited the improved agronomic, yield and nutritional traits of capsicum under poly mulching among other cultivars in Bangladesh.

Genetic and Agronomic Parameter Estimates of Growth, Yield and Related Traits of Maize (Zea mays L.) under Different Rates of Nitrogen Fertilization

This study evaluated the genetic and agronomic parameter estimates of maize under different nitrogen rates. The trial was established at the Njala Agricultural Research Centre experimental site during 2021 and 2022 in a split block design with three maize varieties (IWCD2, 2009EVDT, and DMR-ESR-Yellow) and seven nitrogen (0, 30, 60, 90, 120, 150 and 180 kg∙N∙ha−1) rates. Findings showed that cob diameter and anthesis silking time (ASI) had intermediate heritability, ASI had high genetic advance, ASI and grain yield had high genotypic coefficient of variation (GCV), while traits with high phenotypic coefficient of variation (PCV) were plant height, ASI, grain yield, number of kernel per cob, number of kernel rows, ear length, and ear height. The PCV values were higher than GCV, indicating the influence of the environment in the studied traits. Nitrogen rates and variety significantly (p < 0.05) influenced grain yield production. Mean grain yields and economic parameter estimates increased with increasing nitrogen rates, with the 30 and 180 kg∙N∙ha−1 plots exhibiting the lowest and highest grain yields of 1238 kg∙ha−1 and 2098 kg∙ha−1, respectively. Variety and nitrogen effects on partial factor productivity (PFPN), agronomic efficiency (AEN), net returns (NR), value cost ratio (VCR) and marginal return (MR) indicated that these parameters were significantly affected (p < 0.05) by these factors. The highest PFPN (41.3 kg grain kg−1∙N) and AEN (29.4 kg grain kg−1∙N) were obtained in the 30 kg∙N∙ha−1 plots, while the highest VCR (2.8) and MR (SLL 1.8 SLL−1 spent on N) were obtained in the 180 kg∙N∙ha−1. The significant influence of variety and nitrogen on traits suggests that increasing yields and maximizing profits require use of appropriate nitrogen fertilization and improved farming practices that could be exploited for increased productivity of maize.

Effect of Variety and Plant Spacing on Growth and Yield of Groundnuts (Arachis hypogaea L.)

A field experiment was carried out to determine the effect of variety and plant spacing on yield and growth of groundnuts. The field experiment was laid in a 3 × 3 factorial experiment in a Randomized Complete Block Design (RCBD) with three (3) replications. The factor A included three (3) groundnut varieties (Nkatie Sari, Sum Nutt 22 and Yenyawoso) and Factor B was the three (3) spacing of 30 cm × 15 cm, 30 cm × 30 cm and 30 cm × 40 cm. All recommended agronomic practices were followed. Data was collected from eight (8) tagged plants. Growth data were recorded on plant height, number of branches, number of leaves, and the number of flowers while yield data were collected on the number of flowers, number of pods per plant, 100 seeds weight and the pod yield (kg/ha). The plant spacing significantly influenced (P < 0.05) the growth and yield parameters. Groundnut grown at a spacing of 30 cm × 15 cm produced the maximum plant height, whereas the maximum number of leaves, number of branches and number of flowers were produced from 30 cm × 40 cm. Yenyawoso variety with a wider plant spacing performed better vegetatively among all the varieties. The Yenyawoso variety produced the highest number of pods, 100 seeds weight and pod yield as compared to the other varieties. Also, Yenyawoso at 30 cm × 40 cm spacing and Nkatie Sari at 30 cm × 15 cm spacing produced the maximum pod yield.

Sustainable Management of Biodegradable Waste in Guinea: Effect of Compost on Eggplant and Chilli Crop Yields Pepper

The fight against insalubrity in large urban and peri-urban agglomerations is a major challenge in developing countries. This problem is compounded by that of sustainable waste management mechanisms. Indeed, the current waste collection system in Guinea has proved inadequate, as moving garbage from point “A” to point “B” is tantamount to “moving the problem”. The aim of this experimental work is to demonstrate the cost-effectiveness and benefits of sustainable waste management. As part of this drive to valorize biodegradable waste, the Waste Management Research Center has undertaken a series of activities ranging from composting organic waste to testing compost on certain crop varieties. An experimental field of 8024 m2 was laid out and treated with 1500 Kg of fine compost in doses ranging from 2.5 to 5 T/ha. Two crop varieties, eggplant and chili, were tested. Compost application increased production yields: 15 to 21 tonnes of eggplant and 10.4 to 11.1 tonnes of chili per hectare. Growth rates compared with usual yields varied from 50% to 64% and from 11% to 17% for eggplant and chili, respectively. This study resulted in an optimum compost dose of 2.5 T/ha for this phase.

Application of Predictive Model for Efficient Cassava (Manihot esculenta Crantz) Yield in the Face of Climate Variability in Enugu State, Nigeria

Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate variability incidence which can be communicated to local farmers by agro-meteorological extension officers, research on crops that can grow with little or no rain, planning irrigation scheme, and improving tree planting culture in the study area.

Stresses in the Scapular Fossa Do Not Exceed the Yield Stress When Elevated up to 135 Degrees of Abduction after Reverse Shoulder Arthroplasty

Reverse shoulder arthroplasty (RSA) is an effective treatment for rotator cuff tears. Despite its advantages, complications occur at a high rate. Complications requiring revision include a high rate of base plate failure, 38% of which are due to instability. The primary stability the base plate ensures is a crucial factor and, thus, is the subject of much debate in clinical studies and biomechanical research. This study is aimed to provide data that will contribute to the base plate’s pri-mary stability and glenoid longevity by clarifying the stresses at the scapular fossa and base plate interface associated with elevation after RSA. A 3D finite element model was created from the DICOM data for the scapulohumeral joint and SMR shoulder system. For loading conditions, 30 N was applied for each posi-tion with abduction angles of 0, 45, 90, and 135 degrees. A three-dimensional fi-nite element analysis was performed using the static implicit method with LS-DYNA. The von Mises stresses in the scapular fossa were found not to exceed the yield stress on the bone even after elevation to an abduction angle of 135 de-grees after RSA. It is rough to uniformly compare the yield stress and the von Mises stress, but it was inferred that the possibility of fracture is low unless a large external force is applied. A maximum von Mises stress showed 0 degrees of abduction, suggesting that the lowered position is in a more severe condition than the elevated position. If better improvement is desired, it may be necessary to devise ways to reduce the stress on the upper screw. .

Effect of Supplementary Irrigation on the Yield of Sorghum (Sorghum bicolor L. Moench) in the Context of Climate Change in the Dry Savannahs of Togo

Under the current context of climate change, supplementary irrigation may be needed for crop production resilience. We determined the effects of supplementary irrigation on sorghum grain yield in the dry Savannah region of Togo. A two-year trial was conducted in a controlled environment at AREJ, an agro-ecological center in Cinkassé. The plant material was sorghum variety Sorvato 28. The experimental design was a Completely Randomized Block with three replications and three treatments as follows: T0 control plot (rainfed conditions);T1 (supplementary irrigation from flowering to grain filling stage) and T2 (supplementary irrigation from planting to grain filling stage). Two irrigation techniques (furrow and Californian system) were used under each watering treatment. The results showed that irrigation technique significantly affected panicle length with no effect on 1000 grains mass. Panicle length and grain yields varied from 15.59 to 25.71 cm and 0.0 to 2.06 t∙h−1, respectively, with the highest values (25.66 cm and 2.06 t∙h−1, respectively) under the T2 treatment with the California system-based supplementary irrigation. The comparison of results obtained on treatment T0 and T2, shows that supplementary irrigation increased the yields by at least 68.62%. Supplementary irrigation during sowing and growing season (T2) improved sorghum yields in the dry savannahs of Togo, with a better performance of the California irrigation system.

Growth, Development and Yield of Kenaf as Affected by Planting Dates and N Fertilization

Kenaf (Hibiscus cannabinus L) consists of various beneficial components like stalks, seeds, leaves, fibers, oils, proteins, allelopathic chemicals, and fiber strands, among other things. Despite the numerous uses of the crop, there is little or no information on optimum agronomic practices such as planting date and N fertilization of the crop in the Upper East Region (UER) of Ghana where the crop is widely cultivated by smallholder farmers. Field experiments were therefore carried out in 2020 and repeated during the 2021 cropping season in the study area. The objective of the study was to determine appropriate planting date and N fertilization for increased kenaf productivity. In each year, the treatments consisted of 3 × 5 factorial combinations of three planting dates (1st July, 7th July and 14th July) and five levels of N (0, 20, 40, 60 and 80 kg/ha) replicated three times. The design of the experiment was a split-plot with the N fertilizer as the main plot and the planting date assigned to sub plot. The results showed that, planting kenaf in early (1st) July or N fertilization at the rate of 60 kg/ha increased plant density, stem height, stem diameter, dry bast and core yields in both cropping seasons.

Estimating the Drought-Induced Yield Loss for Winter Wheat in a Semi-Arid Region of the Southern United States Using a Drought Index

The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.

Sustainability Assessment of Banana (Musa spp.) Yield Gap Reduction through Value Chain Development Interventions in Smallholder Farming Systems in Manicaland, Zimbabwe

This study evaluated the effectiveness of donor supported agricultural value chain development projects in sustainably narrowing yield gaps for banana smallholder farmer producers in Manicaland, Zimbabwe. The study used a mixed methods research design that relied on farmers records for the quantitative analysis and focus group discussion and in-depth interviews for key experts for the qualitative aspects. A mix of regression analysis, t-tests, Pearsons’s correlation and analysis of variance statistical methods were used for the quantitative analysis while thematic response analysis was used for the qualitative engagements. The findings showed that by the end of the activity, the project had successfully narrowed the banana yield gaps to 18.66 tons per hectare working with a potential yield base of 40 tons. However, 5 years after the project closure the yield gap had fallen to 24.7 tons indicating a lack of sustainability of yield gap reduction. However, the yield gap slump does not override the fact that farmers on average were still able to sell approximately 5 tons per every 6 months after 5 years from the project closure which is beyond any poverty threshold. This suggests genuine upward economic mobility. Additionally, in analyzing what factors had the greatest influence on yield gap reduction, the access to fertilizer ranked highest where genetics, irrigation and improved agronomy followed in that respective order. The study further showed that farmers who receive value chain development support whilst at an already commercialized state tend to maintain productivity thresholds higher in comparison to those who are at a pre commercial state. This is evidenced by the fact that the pre commercial farmers had a yield reduction of 30.83 percent after 5 years of the project closure whereas the former realized a productivity growth of 7.84%. In conclusion, whilst the intervention was successful in transitioning farmers out of poverty, more investment should be made towards transitioning smallholder farmers to integrated soil fertility management practices and improvement of agronomic efficiency through stronger on field collaboration between research institutions, the government and development institutions.

Estimating the Yield Loss of Winter Wheat from Drought in the United States Southern Plains Region as Influenced by El Niño-Southern Oscillation (ENSO)

Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.

Analyzing the Impact of Feature Selection on Crop Yield Prediction

In agriculture sector, machine learning has been widely used by researchers for crop yield prediction. However, it is quite difficult to identify the most critical features from a dataset. Feature selection techniques allow us to remove the extraneous and noisy features from the original feature set. The feature selection techniques help the model to focus only on the important features of the data, thus reducing execution time and improving efficiency of the model. The aim of this study is to determine relevant subset features for achieving high predictive performance by using different feature selection techniques like Filter methods, Wrapper methods and embedded methods. In this work, different feature selection techniques like Rank-based feature selection technique, weighted feature selection technique and Hybrid Feature Selection Technique have been applied to the agricultural data. The optimal feature set returned by different feature selection techniques is used for yield prediction using Linear regression, Random Forest, and Decision Tree Regressor. The accuracy of prediction obtained using the above three methods has been analyzed by using different evaluation parameters. This study helps in increasing predictive accuracy with the minimum number of features.

Efficiency of Legumes in Increasing Yam Yield under Sandy Ferrasol in the Forest Zone of Southwestern Côte d’Ivoire

The cropping system is based on traditional farming in rural areas. In this way, yields of some food crops like yam are very low considering their high need for nutrients. The nutrient-rich land is under high land pressure as it is occupied by cash crops such as oil palm and rubber at the expense of food crops and soil fertility is declining. The study was conducted in Grand-Lahou to assess the effect of organic matter provided by legumes in increasing yam yield. The randomized complete block design included four (4) treatments: Arachis hypogaea + yam association (T1), Acacia mangium + yam association (T2), Arachis + Acacia mangium + yam association (T3) and pure yam crop (T0). The parameters measured were: the soil nutrients content, the rate of mineralization of organic matter through the C/N ratio as well as the yield of yam through different techniques that allowed the objective of the study to be achieved. It was noted a slight improvement of nitrogen and organic carbon in all treatments with a higher value recorded in the T2 treatment. The C/N ratio decreased to 12 in all treatments compared to the control, which reflects a normal decomposition of the organic matter. Treatment T1 increased yam yield (8.4 t/ha) in contrast to treatments T2 (4.1 t/ha) and T3 (2.8 t/ha). Legume-based treatments T2 and T3 were associated with a significant decrease in yam yield, resulting in losses of −46.34% to −25.09%, while treatment T1 resulted in a gain of 28.57%. As a result, the treatments involving legumes contributed to normalizing the organic matter content of the soil. The simultaneous association of these two legumes led to a decrease in yam production, contrary to the treatment associating only groundnut.

Evaluation of global gridded crop models in simulating sugarcane yield in China

中国是全球第三大甘蔗生产国,中国甘蔗产量模拟可服务于全球食糖和乙醇的生产和贸易.全球格点作物模式CLM5-crop和LPJmL已实现对甘蔗的模拟,但它们在中国的模拟能力未知.本文评估结果表明:两个模式均严重低估了甘蔗产量,模拟均不足观测的1/4.CLM5-crop能有技巧地模拟产量的空间分布特征,而LPJmL不能.两个模式均不能合理模拟产量的年际变化,且低估了产量的上升趋势.模式低估甘蔗产量的部分原因是模式假设收割的是甘蔗的穗而非茎.

不同气象条件对高油酸花生产量的影响

以河南、山东等5个花生主要产区培育的19个高油酸花生新品种为材料,于2019年~2021年连续3年在郑州种植,采集3年间花生关键生育期(6月~9月)的旬平均气温、旬降水量和旬日照时数等气象数据,结合各个品种的产量数据进行综合分析。研究结果表明,不同的品种对于气温、降水量和日照时数的敏感程度不同,冀花16、冀花11对开花下针期的温度和日照时数比较敏感,该时期的异常高温会致使其产量明显下降。中花413、中花412和花育917的产量与旬降水量成显著负相关,耐涝程度较差。对品种的稳定性分析表明,开农1768、南充1704、冀农16、开选016、花育961、郑农花25、郑农花23、冀农11、花育633和1508G等10个高油酸品种为年际间稳定性较好的品种,研究结论为高油酸品种的培育及深入利用提供了指导。

中糖2号在国家第13轮甘蔗品种区试的综合评价

为研究甘蔗新品种中糖2号在全国各个蔗区的适应性,中糖2号参加了2018—2020年在全国5省区18个区试点开展全国甘蔗新品种第13轮联合区试1年新植2年宿根区域试验。结果表明,以全国18个区试点的数据结果统计,1年新植2年宿根平均蔗产量6734 kg/667 m^(2),比对照ROC22增产11.16%,14点次增产;平均含糖量957 kg/667 m^(2),比对照ROC22增产7.29%,12点次增产;11—12月平均甘蔗蔗糖分为13.67%,1—3月平均甘蔗蔗糖分为15.30%,全期平均甘蔗蔗糖分为14.52%,比ROC22低0.20个百分点。第1年新植蔗产量6598 kg/667 m^(2),平均含糖量900 kg/667 m^(2),全期平均甘蔗蔗糖分13.57%;第1年宿根平均蔗产量6693 kg/667 m^(2),比ROC22增产15.66%,平均含糖量1017 kg/667 m^(2),比ROC22增产13.25%,全期平均甘蔗蔗糖分15.28%;第2年宿根平均蔗产量6963 kg/667 m^(2),比ROC22增产26.53%,平均含糖量952 kg/667 m^(2),比对照ROC22增产17.10%,全期平均甘蔗蔗糖分为14.75%。平均甘蔗纤维分为11.80%,比对照ROC22高0.70个百分点。通过人工接种鉴定对黑穗病的抗性级别为1级,抗性反应型为高抗;对花叶病的抗性级别为2级,抗性反应型为高抗。中糖2号高抗黑穗病,适宜机械收获。